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ORCIDHonglak Lee
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2024
[c184]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers. AAAI 2024: 11186-11194- [c183]Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee:
Unsupervised Object Interaction Learning with Counterfactual Dynamics Models. AAAI 2024: 11570-11578 - [c182]Nakyeong Yang, Taegwan Kang, Stanley Jungkyu Choi, Honglak Lee, Kyomin Jung:
Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination. ACL (1) 2024: 9061-9073 - [c181]Janghoon Han, Changho Lee, Joongbo Shin, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning. ACL (Findings) 2024: 15436-15452 - [c180]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang:
Small Language Models Need Strong Verifiers to Self-Correct Reasoning. ACL (Findings) 2024: 15637-15653 - [c179]Byoungjip Kim, Dasol Hwang, Sungjun Cho, Youngsoo Jang, Honglak Lee, Moontae Lee:
Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning. CVPR Workshops 2024: 1808-1817 - [c178]Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd C. Hollon:
Super-resolution of biomedical volumes with 2D supervision. CVPR Workshops 2024: 6966-6977 - [c177]Taehoon Kim, Pyunghwan Ahn, Sangyun Kim, Sihaeng Lee, Mark Marsden, Alessandra Sala, Seung Hwan Kim, Bohyung Han, Kyoung Mu Lee, Honglak Lee, Kyounghoon Bae, Xiangyu Wu, Yi Gao, Hailiang Zhang, Yang Yang, Weili Guo, Jianfeng Lu, Youngtaek Oh, Jae-Won Cho, Dong-Jin Kim, In So Kweon, Junmo Kim, Wooyoung Kang, Won Young Jhoo, Byungseok Roh, Jonghwan Mun, Solgil Oh, Kenan Emir Ak, Gwang-Gook Lee, Yan Xu, Mingwei Shen, Kyomin Hwang, Wonsik Shin, Kamin Lee, Wonhark Park, Dongkwan Lee, Nojun Kwak, Yujin Wang, Yimu Wang, Tiancheng Gu, Xingchang Lv, Mingmao Sun:
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning. CVPR Workshops 2024: 7356-7365 - [c176]Tiange Luo, Justin Johnson, Honglak Lee:
View Selection for 3D Captioning via Diffusion Ranking. ECCV (31) 2024: 180-197 - [c175]Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, Moontae Lee:
Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking. EMNLP (Findings) 2024: 14958-14976 - [c174]Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee:
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents. EMNLP (Findings) 2024: 16531-16541 - [c173]Changho Lee, Janghoon Han, Seonghyeon Ye, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks. EMNLP 2024: 18620-18642 - [c172]Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee, Moontae Lee:
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration. ICML 2024 - [c171]Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea:
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense. NAACL-HLT 2024: 5668-5680 - [c170]Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee:
Code Models are Zero-shot Precondition Reasoners. NAACL-HLT 2024: 5681-5697 - [i152]Xinhai Hou, Cheng Jiang, Akhil Kondepudi, Yiwei Lyu, Asadur Zaman Chowdury, Honglak Lee, Todd C. Hollon
:
A self-supervised framework for learning whole slide representations. CoRR abs/2402.06188 (2024) - [i151]Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee:
AutoGuide: Automated Generation and Selection of State-Aware Guidelines for Large Language Model Agents. CoRR abs/2403.08978 (2024) - [i150]Yiwei Lyu, Sung Jik Cha, Cheng Jiang, Asadur Chowdury, Xinhai Hou, Edward S. Harake, Akhil Kondepudi, Christian W. Freudiger, Honglak Lee, Todd C. Hollon:
Step-Calibrated Diffusion for Biomedical Optical Image Restoration. CoRR abs/2403.13680 (2024) - [i149]Muhammad Khalifa, David Wadden, Emma Strubell, Honglak Lee, Lu Wang, Iz Beltagy, Hao Peng:
Source-Aware Training Enables Knowledge Attribution in Language Models. CoRR abs/2404.01019 (2024) - [i148]Tiange Luo, Justin Johnson, Honglak Lee:
View Selection for 3D Captioning via Diffusion Ranking. CoRR abs/2404.07984 (2024) - [i147]Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd C. Hollon:
Super-resolution of biomedical volumes with 2D supervision. CoRR abs/2404.09425 (2024) - [i146]Changho Lee, Janghoon Han, Seonghyeon Ye, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Instruction Matters, a Simple yet Effective Task Selection Approach in Instruction Tuning for Specific Tasks. CoRR abs/2404.16418 (2024) - [i145]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang:
Small Language Models Need Strong Verifiers to Self-Correct Reasoning. CoRR abs/2404.17140 (2024) - [i144]Siqi Shen, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Soujanya Poria, Rada Mihalcea:
Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsense. CoRR abs/2405.04655 (2024) - [i143]Xingjian Zhang, Yutong Xie, Jin Huang, Jinge Ma, Zhaoying Pan, Qijia Liu, Ziyang Xiong, Tolga Ergen, Dongsub Shim, Honglak Lee, Qiaozhu Mei:
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows. CoRR abs/2406.06357 (2024) - [i142]Janghoon Han, Changho Lee, Joongbo Shin, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning. CoRR abs/2406.08796 (2024) - [i141]Soyoung An, Kyunghoon Bae, Eunbi Choi, Stanley Jungkyu Choi, Yemuk Choi, Seokhee Hong, Yeonjung Hong, Junwon Hwang, Hyojin Jeon, Gerrard Jeongwon Jo, Hyunjik Jo, Jiyeon Jung, Yountae Jung, Euisoon Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Youchul Kim, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lee, Moontae Lee, Seungjun Lee, Woohyung Lim, Sangha Park, Sooyoun Park, Yongmin Park, Boseong Seo, Sihoon Yang, Heuiyeen Yeen, Kyungjae Yoo, Hyeongu Yun:
EXAONE 3.0 7.8B Instruction Tuned Language Model. CoRR abs/2408.03541 (2024) - [i140]Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee:
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents. CoRR abs/2410.22552 (2024) - 2023
- [j5]Tiange Luo, Honglak Lee, Justin Johnson:
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program. Trans. Mach. Learn. Res. 2023 (2023) - [c169]Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Simple and Effective Synthesis of Indoor 3D Scenes. AAAI 2023: 1169-1178 - [c168]Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee:
Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters. AAAI 2023: 8334-8342 - [c167]Lajanugen Logeswaran, Wilka Carvalho, Honglak Lee:
Learning Compositional Tasks from Language Instructions. AAAI 2023: 13300-13308 - [c166]Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee:
Unsupervised Task Graph Generation from Instructional Video Transcripts. ACL (Findings) 2023: 3392-3406 - [c165]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Few-shot Reranking for Multi-hop QA via Language Model Prompting. ACL (1) 2023: 15882-15897 - [c164]Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
Hierarchical Discriminative Learning Improves Visual Representations of Biomedical Microscopy. CVPR 2023: 19798-19808 - [c163]Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Lajanugen Logeswaran, Dong-Ki Kim, Dongsub Shim, Honglak Lee:
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues. EMNLP 2023: 3355-3371 - [c162]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Merging Generated and Retrieved Knowledge for Open-Domain QA. EMNLP 2023: 4710-4728 - [c161]Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai:
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning. EMNLP 2023: 7354-7379 - [c160]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
GRACE: Discriminator-Guided Chain-of-Thought Reasoning. EMNLP (Findings) 2023: 15299-15328 - [c159]Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee:
A Picture is Worth a Thousand Words: Language Models Plan from Pixels. EMNLP 2023: 16450-16459 - [c158]Hyungjun Lim, Younggwan Kim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee:
Lightweight Feature Encoder for Wake-Up Word Detection Based on Self-Supervised Speech Representation. ICASSP 2023: 1-5 - [c157]Daechul Ahn, Daneul Kim, Gwangmo Song, Seung Hwan Kim, Honglak Lee, Dongyeop Kang, Jonghyun Choi:
Story Visualization by Online Text Augmentation with Context Memory. ICCV 2023: 3102-3112 - [c156]Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh:
Composing Task Knowledge With Modular Successor Feature Approximators. ICLR 2023 - [c155]Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
Preference Transformer: Modeling Human Preferences using Transformers for RL. ICLR 2023 - [c154]Yao Fu, Run Peng, Honglak Lee:
Go Beyond Imagination: Maximizing Episodic Reachability with World Models. ICML 2023: 10405-10420 - [c153]Younggwan Kim, Hyungjun Lim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee:
Investigation of Training Mute-Expressive End-to-End Speech Separation Networks for an Unknown Number of Speakers. INTERSPEECH 2023: 3764-3768 - [c152]Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran:
Combining Behaviors with the Successor Features Keyboard. NeurIPS 2023 - [c151]Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee:
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. NeurIPS 2023 - [c150]Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee:
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. NeurIPS 2023 - [c149]Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee:
Guide Your Agent with Adaptive Multimodal Rewards. NeurIPS 2023 - [c148]Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson:
Scalable 3D Captioning with Pretrained Models. NeurIPS 2023 - [c147]Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai:
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation. NeurIPS 2023 - [c146]Yiwei Lyu, Tiange Luo, Jiacheng Shi, Todd C. Hollon, Honglak Lee:
Fine-grained Text Style Transfer with Diffusion-Based Language Models. RepL4NLP@ACL 2023: 65-74 - [c145]Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim:
Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution. WACV 2023: 4945-4954 - [i139]Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee:
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. CoRR abs/2301.02903 (2023) - [i138]Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee:
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers. CoRR abs/2301.11578 (2023) - [i137]Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh:
Composing Task Knowledge with Modular Successor Feature Approximators. CoRR abs/2301.12305 (2023) - [i136]Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee:
Multimodal Subtask Graph Generation from Instructional Videos. CoRR abs/2302.08672 (2023) - [i135]Lajanugen Logeswaran, Sungryull Sohn, Yunseok Jang, Moontae Lee, Honglak Lee:
Unsupervised Task Graph Generation from Instructional Video Transcripts. CoRR abs/2302.09173 (2023) - [i134]Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
Preference Transformer: Modeling Human Preferences using Transformers for RL. CoRR abs/2303.00957 (2023) - [i133]Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
Hierarchical discriminative learning improves visual representations of biomedical microscopy. CoRR abs/2303.01605 (2023) - [i132]Hyungjun Lim, Younggwan Kim, Kiho Yeom, Eunjoo Seo, Hoodong Lee, Stanley Jungkyu Choi, Honglak Lee:
Lightweight feature encoder for wake-up word detection based on self-supervised speech representation. CoRR abs/2303.07592 (2023) - [i131]Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee:
A Picture is Worth a Thousand Words: Language Models Plan from Pixels. CoRR abs/2303.09031 (2023) - [i130]Todd C. Hollon, Cheng Jiang, Asadur Chowdury, Mustafa Nasir-Moin, Akhil Kondepudi, Alexander Aabedi, Arjun Adapa, Wajd Al-Holou, Jason Heth, Oren Sagher, Pedro Lowenstein, Maria Castro, Lisa Irina Wadiura, Georg Widhalm, Volker Neuschmelting, David Reinecke, Niklas von Spreckelsen, Mitchel S. Berger, Shawn Hervey-Jumper, John G. Golfinos, Matija Snuderl, Sandra Camelo-Piragua, Christian W. Freudiger, Honglak Lee, Daniel A. Orringer:
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging. CoRR abs/2303.13610 (2023) - [i129]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Discriminator-Guided Multi-step Reasoning with Language Models. CoRR abs/2305.14934 (2023) - [i128]Yiwei Lyu, Tiange Luo, Jiacheng Shi, Todd C. Hollon, Honglak Lee:
Fine-grained Text Style Transfer with Diffusion-Based Language Models. CoRR abs/2305.19512 (2023) - [i127]Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson:
Scalable 3D Captioning with Pretrained Models. CoRR abs/2306.07279 (2023) - [i126]Daechul Ahn, Daneul Kim, Gwangmo Song, Seung Hwan Kim, Honglak Lee, Dongyeop Kang, Jonghyun Choi:
Story Visualization by Online Text Augmentation with Context Memory. CoRR abs/2308.07575 (2023) - [i125]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Exploring Demonstration Ensembling for In-context Learning. CoRR abs/2308.08780 (2023) - [i124]Yao Fu, Run Peng, Honglak Lee:
Go Beyond Imagination: Maximizing Episodic Reachability with World Models. CoRR abs/2308.13661 (2023) - [i123]Taehoon Kim, Pyunghwan Ahn, Sangyun Kim, Sihaeng Lee, Mark Marsden, Alessandra Sala, Seung Hwan Kim, Bohyung Han, Kyoung Mu Lee, Honglak Lee, Kyounghoon Bae, Xiangyu Wu, Yi Gao, Hailiang Zhang, Yang Yang, Weili Guo, Jianfeng Lu, Youngtaek Oh, Jae-Won Cho, Dong-Jin Kim, In So Kweon, Junmo Kim, Woo-Young Kang, Won Young Jhoo, Byungseok Roh, Jonghwan Mun, Solgil Oh, Kenan Emir Ak, Gwang-Gook Lee, Yan Xu, Mingwei Shen, Kyomin Hwang, Wonsik Shin, Kamin Lee, Wonhark Park, Dongkwan Lee, Nojun Kwak, Yujin Wang, Yimu Wang, Tiancheng Gu, Xingchang Lv, Mingmao Sun:
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning. CoRR abs/2309.01961 (2023) - [i122]Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee:
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. CoRR abs/2309.04062 (2023) - [i121]Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee:
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning. CoRR abs/2309.04082 (2023) - [i120]Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee:
Guide Your Agent with Adaptive Multimodal Rewards. CoRR abs/2309.10790 (2023) - [i119]Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai:
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation. CoRR abs/2310.13165 (2023) - [i118]Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
Merging Generated and Retrieved Knowledge for Open-Domain QA. CoRR abs/2310.14393 (2023) - [i117]Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew Kyle Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo J. Rezende, Daniel Zoran:
Combining Behaviors with the Successor Features Keyboard. CoRR abs/2310.15940 (2023) - [i116]Dong-Ki Kim, Sungryull Sohn, Lajanugen Logeswaran, Dongsub Shim, Honglak Lee:
MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning. CoRR abs/2310.16730 (2023) - [i115]Zheyuan Zhang, Shane Storks, Fengyuan Hu, Sungryull Sohn, Moontae Lee, Honglak Lee, Joyce Chai:
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning. CoRR abs/2310.18364 (2023) - [i114]Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Zhe Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee:
Code Models are Zero-shot Precondition Reasoners. CoRR abs/2311.09601 (2023) - [i113]Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee:
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models. CoRR abs/2312.02615 (2023) - [i112]Sungryull Sohn, Yiwei Lyu, Anthony Z. Liu, Lajanugen Logeswaran, Dong-Ki Kim, Dongsub Shim, Honglak Lee:
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues. CoRR abs/2312.04668 (2023) - 2022
- [c144]Yijie Guo, Qiucheng Wu, Honglak Lee:
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks. AAAI 2022: 6792-6800 - [c143]Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee:
Learning Parameterized Task Structure for Generalization to Unseen Entities. AAAI 2022: 7534-7541 - [c142]Yuan Li, Biaoyan Fang, Jiayuan He, Hiyori Yoshikawa, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Zubair Afzal, Zenan Zhai, Kojiro Machi, Masaharu Yoshioka, Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae, Darshini Mahendran, Christina Tang, Bridget T. McInnes, Timothy Baldwin, Karin Verspoor:
Extended Overview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents. CLEF (Working Notes) 2022: 758-781 - [c141]Youngrok Jang, Hosung Song, Junho Lee, Gyeonghun Kim, Yireun Kim, Stanley Jungkyu Choi, Honglak Lee, Kyunghoon Bae:
Context aware Named Entity Recognition and Relation Extraction with Domain-specific language model. CLEF (Working Notes) 2022: 782-796 - [c140]Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae:
L-Verse: Bidirectional Generation Between Image and Text. CVPR 2022: 16505-16515 - [c139]Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim:
Lipschitz-constrained Unsupervised Skill Discovery. ICLR 2022 - [c138]Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. ICLR 2022 - [c137]Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim, Sehui Han, Moontae Lee, Honglak Lee, Yousung Jung:
Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules. ICML 2022: 16952-16968 - [c136]Sihaeng Lee, Eojindl Yi, Janghyeon Lee, Jinsu Yoo, Honglak Lee, Seung Hwan Kim:
Fully Convolutional Transformer with Local-Global Attention. IROS 2022: 552-559 - [c135]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. NAACL-HLT 2022: 5493-5506 - [c134]Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology. NeurIPS 2022 - [c133]Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong:
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. NeurIPS 2022 - [c132]Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee:
CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition. NeurIPS 2022 - [c131]Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee:
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. NeurIPS 2022 - [c130]Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. NeurIPS 2022 - [c129]Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim:
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. NeurIPS 2022 - [c128]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee:
Fast inference and transfer of compositional task structures for few-shot task generalization. UAI 2022: 1857-1865 - [i111]Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Environment Generation for Zero-Shot Compositional Reinforcement Learning. CoRR abs/2201.08896 (2022) - [i110]Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim:
Lipschitz-constrained Unsupervised Skill Discovery. CoRR abs/2202.00914 (2022) - [i109]Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim:
Rich CNN-Transformer Feature Aggregation Networks for Super-Resolution. CoRR abs/2203.07682 (2022) - [i108]Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. CoRR abs/2203.10050 (2022) - [i107]Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee:
Learning Parameterized Task Structure for Generalization to Unseen Entities. CoRR abs/2203.15034 (2022) - [i106]Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Simple and Effective Synthesis of Indoor 3D Scenes. CoRR abs/2204.02960 (2022) - [i105]Yunseok Jang, Ruben Villegas, Jimei Yang, Duygu Ceylan, Xin Sun, Honglak Lee:
RiCS: A 2D Self-Occlusion Map for Harmonizing Volumetric Objects. CoRR abs/2205.06975 (2022) - [i104]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee:
Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization. CoRR abs/2205.12648 (2022) - [i103]Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang:
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA. CoRR abs/2205.12650 (2022) - [i102]Lajanugen Logeswaran, Yao Fu, Moontae Lee, Honglak Lee:
Few-shot Subgoal Planning with Language Models. CoRR abs/2205.14288 (2022) - [i101]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i100]Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology. CoRR abs/2206.08439 (2022) - [i99]Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. CoRR abs/2207.02505 (2022) - [i98]Yijie Guo, Qiucheng Wu, Honglak Lee:
Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks. CoRR abs/2207.09071 (2022) - [i97]Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee:
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters. CoRR abs/2209.02939 (2022) - [i96]Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim:
UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. CoRR abs/2209.13430 (2022) - [i95]Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong:
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. CoRR abs/2210.15541 (2022) - [i94]Jongseong Jang, Daeun Kyung, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae, Edward Choi:
Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders. CoRR abs/2212.07050 (2022) - [i93]Tiange Luo, Honglak Lee, Justin Johnson:
Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program. CoRR abs/2212.12952 (2022) - 2021
- [c127]Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang:
Improved Consistency Regularization for GANs. AAAI 2021: 11033-11041 - [c126]Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Cross-Modal Contrastive Learning for Text-to-Image Generation. CVPR 2021: 833-842 - [c125]Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Pathdreamer: A World Model for Indoor Navigation. ICCV 2021: 14718-14728 - [c124]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. ICLR 2021 - [c123]Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed H. Chi, Honglak Lee, Minmin Chen:
Batch Reinforcement Learning Through Continuation Method. ICLR 2021 - [c122]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. ICLR 2021 - [c121]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. ICLR 2021 - [c120]Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu:
Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. ICML 2021: 1953-1963 - [c119]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. ICML 2021: 9443-9454 - [c118]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. ICML 2021: 9780-9790 - [c117]Yunke Wang, Chang Xu, Bo Du, Honglak Lee:
Learning to Weight Imperfect Demonstrations. ICML 2021: 10961-10970 - [c116]Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh:
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment. IJCAI 2021: 2219-2226 - [c115]Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Weilong Yang, Honglak Lee, Irfan Essa:
Text as Neural Operator: Image Manipulation by Text Instruction. ACM Multimedia 2021: 1893-1902 - [c114]Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Environment Generation for Zero-Shot Compositional Reinforcement Learning. NeurIPS 2021: 4157-4169 - [c113]Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin:
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. NeurIPS 2021: 17710-17722 - [c112]Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee:
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. NeurIPS 2021: 26963-26975 - [c111]Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi:
Why Do Better Loss Functions Lead to Less Transferable Features? NeurIPS 2021: 28648-28662 - [c110]Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Text-to-Image Generation Grounded by Fine-Grained User Attention. WACV 2021: 237-246 - [i92]John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust:
Evolving Reinforcement Learning Algorithms. CoRR abs/2101.03958 (2021) - [i91]Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Cross-Modal Contrastive Learning for Text-to-Image Generation. CoRR abs/2101.04702 (2021) - [i90]Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee:
State Entropy Maximization with Random Encoders for Efficient Exploration. CoRR abs/2102.09430 (2021) - [i89]Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust:
Adversarial Environment Generation for Learning to Navigate the Web. CoRR abs/2103.01991 (2021) - [i88]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. CoRR abs/2104.06697 (2021) - [i87]Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson:
Pathdreamer: A World Model for Indoor Navigation. CoRR abs/2105.08756 (2021) - [i86]Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu:
Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning. CoRR abs/2106.01404 (2021) - [i85]Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee:
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. CoRR abs/2107.06405 (2021) - [i84]Cheng Jiang, Abhishek Bhattacharya, Joseph Linzey, Rushikesh S. Joshi, Sung Jik Cha, Sudharsan Srinivasan, Daniel Alber, Akhil Kondepudi, Esteban Urias, Balaji Pandian, Wajd Al-Holou, Steve Sullivan, B. Gregory Thompson, Jason Heth, Chris Freudiger, Siri S. Khalsa, Donato Pacione, John G. Golfinos, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon:
Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology. CoRR abs/2108.03555 (2021) - [i83]Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin:
Improving Transferability of Representations via Augmentation-Aware Self-Supervision. CoRR abs/2111.09613 (2021) - [i82]Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee:
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning. CoRR abs/2111.09858 (2021) - [i81]Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae:
L-Verse: Bidirectional Generation Between Image and Text. CoRR abs/2111.11133 (2021) - 2020
- [c109]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? AAAI 2020: 5454-5461 - [c108]Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash:
Efficient Adversarial Training With Transferable Adversarial Examples. CVPR 2020: 1178-1187 - [c107]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
Distilling Effective Supervision From Severe Label Noise. CVPR 2020: 9291-9300 - [c106]Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li:
SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing. ECCV (14) 2020: 19-37 - [c105]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. ECCV (26) 2020: 157-174 - [c104]Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee:
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning. ICLR 2020 - [c103]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. ICLR 2020 - [c102]Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee:
Consistency Regularization for Generative Adversarial Networks. ICLR 2020 - [c101]Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin:
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. ICML 2020: 5757-5766 - [c100]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. IJCAI 2020: 2824-2830 - [c99]Krzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
Ode to an ODE. NeurIPS 2020 - [c98]Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee:
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards. NeurIPS 2020 - [c97]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. NeurIPS 2020 - [c96]Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang:
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. NeurIPS 2020 - [c95]Shubham Dash, Giridharan Kumaravelu, Vijayakrishna Naganoor, Suraj Kiran Raman, Aditya Ramesh, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. WACV 2020: 2314-2322 - [i80]Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee:
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies. CoRR abs/2001.00248 (2020) - [i79]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. CoRR abs/2001.04296 (2020) - [i78]Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang:
Improved Consistency Regularization for GANs. CoRR abs/2002.04724 (2020) - [i77]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. CoRR abs/2002.05522 (2020) - [i76]Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques E. Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani:
Time Dependence in Non-Autonomous Neural ODEs. CoRR abs/2005.01906 (2020) - [i75]Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin:
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning. CoRR abs/2005.06800 (2020) - [i74]Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee:
CompressNet: Generative Compression at Extremely Low Bitrates. CoRR abs/2006.08003 (2020) - [i73]Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani:
An Ode to an ODE. CoRR abs/2006.11421 (2020) - [i72]Haizhong Zheng, Ziqi Zhang, Honglak Lee, Atul Prakash:
Understanding and Diagnosing Vulnerability under Adversarial Attacks. CoRR abs/2007.08716 (2020) - [i71]Kuang-Huei Lee, Ian Fischer, Anthony Z. Liu, Yijie Guo, Honglak Lee, John F. Canny, Sergio Guadarrama:
Predictive Information Accelerates Learning in RL. CoRR abs/2007.12401 (2020) - [i70]Tianhao Zhang, Hung-Yu Tseng, Lu Jiang, Honglak Lee, Irfan Essa, Weilong Yang:
Text as Neural Operator: Image Manipulation by Text Instruction. CoRR abs/2008.04556 (2020) - [i69]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Strategy for Regularizing Contrastive Representation Learning. CoRR abs/2010.08887 (2020) - [i68]Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang:
Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning. CoRR abs/2010.12142 (2020) - [i67]Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh:
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments. CoRR abs/2010.15195 (2020) - [i66]Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi:
What's in a Loss Function for Image Classification? CoRR abs/2010.16402 (2020) - [i65]Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang:
Text-to-Image Generation Grounded by Fine-Grained User Attention. CoRR abs/2011.03775 (2020) - [i64]Lajanugen Logeswaran, Ann Lee, Myle Ott, Honglak Lee, Marc'Aurelio Ranzato, Arthur Szlam:
Few-shot Sequence Learning with Transformers. CoRR abs/2012.09543 (2020)
2010 – 2019
- 2019
- [c94]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. ACL (1) 2019: 3449-3460 - [c93]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Incremental Learning with Unlabeled Data in the Wild. CVPR Workshops 2019: 29-32 - [c92]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild. ICCV 2019: 312-321 - [c91]Yunseok Jang, Tianchen Zhao, Seunghoon Hong, Honglak Lee:
Adversarial Defense via Learning to Generate Diverse Attacks. ICCV 2019: 2740-2749 - [c90]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. ICLR (Poster) 2019 - [c89]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. ICLR (Poster) 2019 - [c88]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. ICLR (Poster) 2019 - [c87]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. ICML 2019: 2555-2565 - [c86]Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton:
Similarity of Neural Network Representations Revisited. ICML 2019: 3519-3529 - [c85]Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin:
Robust Inference via Generative Classifiers for Handling Noisy Labels. ICML 2019: 3763-3772 - [c84]Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee:
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. NeurIPS 2019: 81-91 - [c83]Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee:
Unsupervised learning of object structure and dynamics from videos. NeurIPS 2019: 92-102 - [p1]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation. Explainable AI 2019: 77-95 - [i63]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. CoRR abs/1901.09024 (2019) - [i62]Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin:
Robust Inference via Generative Classifiers for Handling Noisy Labels. CoRR abs/1901.11300 (2019) - [i61]Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee:
Incremental Learning with Unlabeled Data in the Wild. CoRR abs/1903.12648 (2019) - [i60]Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton:
Similarity of Neural Network Representations Revisited. CoRR abs/1905.00414 (2019) - [i59]Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, Honglak Lee:
Zero-Shot Entity Linking by Reading Entity Descriptions. CoRR abs/1906.07348 (2019) - [i58]Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin Murphy, Honglak Lee:
Unsupervised Learning of Object Structure and Dynamics from Videos. CoRR abs/1906.07889 (2019) - [i57]Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li:
SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing. CoRR abs/1906.07927 (2019) - [i56]Xinchen Yan, Mohi Khansari, Jasmine Hsu, Yuanzheng Gong, Yunfei Bai, Sören Pirk, Honglak Lee:
Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks. CoRR abs/1906.08989 (2019) - [i55]Yijie Guo, Jongwook Choi, Marcin Moczulski, Samy Bengio, Mohammad Norouzi, Honglak Lee:
Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy. CoRR abs/1907.10247 (2019) - [i54]Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine:
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR abs/1909.10618 (2019) - [i53]Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister:
IEG: Robust Neural Network Training to Tackle Severe Label Noise. CoRR abs/1910.00701 (2019) - [i52]Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee:
A Simple Randomization Technique for Generalization in Deep Reinforcement Learning. CoRR abs/1910.05396 (2019) - [i51]Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee:
Consistency Regularization for Generative Adversarial Networks. CoRR abs/1910.12027 (2019) - [i50]Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee:
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks. CoRR abs/1911.01655 (2019) - [i49]Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh:
How Should an Agent Practice? CoRR abs/1912.07045 (2019) - [i48]Haizhong Zheng, Ziqi Zhang, Juncheng Gu, Honglak Lee, Atul Prakash:
Efficient Adversarial Training with Transferable Adversarial Examples. CoRR abs/1912.11969 (2019) - 2018
- [c82]Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev:
Sentence Ordering and Coherence Modeling using Recurrent Neural Networks. AAAI 2018: 5285-5292 - [c81]Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev:
Addressee and Response Selection in Multi-Party Conversations With Speaker Interaction RNNs. AAAI 2018: 5690-5697 - [c80]Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee:
Hierarchical Novelty Detection for Visual Object Recognition. CVPR 2018: 1034-1042 - [c79]Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee:
Unsupervised Discovery of Object Landmarks as Structural Representations. CVPR 2018: 2694-2703 - [c78]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CVPR 2018: 7986-7994 - [c77]Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee:
Neural Kinematic Networks for Unsupervised Motion Retargetting. CVPR 2018: 8639-8648 - [c76]Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee:
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. ECCV (5) 2018: 276-293 - [c75]Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin:
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. ICLR (Poster) 2018 - [c74]Lajanugen Logeswaran, Honglak Lee:
An efficient framework for learning sentence representations. ICLR (Poster) 2018 - [c73]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. ICML 2018: 3875-3884 - [c72]Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee:
Hierarchical Long-term Video Prediction without Supervision. ICML 2018: 6033-6041 - [c71]Xinchen Yan, Jasmine Hsu, Mohammad Khansari, Yunfei Bai, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee:
Learning 6-DOF Grasping Interaction via Deep Geometry-Aware 3D Representations. ICRA 2018: 1-9 - [c70]Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. NeurIPS 2018: 2713-2723 - [c69]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Data-Efficient Hierarchical Reinforcement Learning. NeurIPS 2018: 3307-3317 - [c68]Lajanugen Logeswaran, Honglak Lee, Samy Bengio:
Content preserving text generation with attribute controls. NeurIPS 2018: 5108-5118 - [c67]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. NeurIPS 2018: 7156-7166 - [c66]Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin:
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. NeurIPS 2018: 7167-7177 - [c65]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. NeurIPS 2018: 8234-8244 - [i47]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CoRR abs/1801.05091 (2018) - [i46]Lajanugen Logeswaran, Honglak Lee:
An efficient framework for learning sentence representations. CoRR abs/1803.02893 (2018) - [i45]Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee:
Hierarchical Novelty Detection for Visual Object Recognition. CoRR abs/1804.00722 (2018) - [i44]Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee:
Unsupervised Discovery of Object Landmarks as Structural Representations. CoRR abs/1804.04412 (2018) - [i43]Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee:
Neural Kinematic Networks for Unsupervised Motion Retargetting. CoRR abs/1804.05653 (2018) - [i42]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Data-Efficient Hierarchical Reinforcement Learning. CoRR abs/1805.08296 (2018) - [i41]Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee:
Hierarchical Long-term Video Prediction without Supervision. CoRR abs/1806.04768 (2018) - [i40]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. CoRR abs/1806.05635 (2018) - [i39]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. CoRR abs/1807.01675 (2018) - [i38]Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin:
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks. CoRR abs/1807.03888 (2018) - [i37]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. CoRR abs/1807.07665 (2018) - [i36]Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee:
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. CoRR abs/1808.04545 (2018) - [i35]Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. CoRR abs/1808.07535 (2018) - [i34]Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine:
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. CoRR abs/1810.01257 (2018) - [i33]Lajanugen Logeswaran, Honglak Lee, Samy Bengio:
Content preserving text generation with attribute controls. CoRR abs/1811.01135 (2018) - [i32]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. CoRR abs/1811.01483 (2018) - [i31]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. CoRR abs/1811.04551 (2018) - [i30]Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee:
Generative Adversarial Self-Imitation Learning. CoRR abs/1812.00950 (2018) - 2017
- [c64]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. BMVC 2017 - [c63]Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee:
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries. CVPR 2017: 1090-1099 - [c62]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos. CVPR 2017: 2224-2232 - [c61]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. ICLR (Poster) 2017 - [c60]Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. ICML 2017: 2661-2670 - [c59]Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee:
Learning to Generate Long-term Future via Hierarchical Prediction. ICML 2017: 3560-3569 - [c58]Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee:
Towards Understanding the Invertibility of Convolutional Neural Networks. IJCAI 2017: 1703-1710 - [c57]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. NIPS 2017: 6118-6128 - [i29]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation using Web-Crawled Videos. CoRR abs/1701.00352 (2017) - [i28]Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee:
Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries. CoRR abs/1704.03944 (2017) - [i27]Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee:
Learning to Generate Long-term Future via Hierarchical Prediction. CoRR abs/1704.05831 (2017) - [i26]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. CoRR abs/1705.06830 (2017) - [i25]Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee:
Towards Understanding the Invertibility of Convolutional Neural Networks. CoRR abs/1705.08664 (2017) - [i24]Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. CoRR abs/1706.05064 (2017) - [i23]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. CoRR abs/1706.08033 (2017) - [i22]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. CoRR abs/1707.03497 (2017) - [i21]Xinchen Yan, Mohi Khansari, Yunfei Bai, Jasmine Hsu, Arkanath Pathak, Abhinav Gupta, James Davidson, Honglak Lee:
Learning Grasping Interaction with Geometry-aware 3D Representations. CoRR abs/1708.07303 (2017) - [i20]Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev:
Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs. CoRR abs/1709.04005 (2017) - [i19]Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin:
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples. CoRR abs/1711.09325 (2017) - 2016
- [c56]Scott E. Reed, Zeynep Akata, Honglak Lee, Bernt Schiele:
Learning Deep Representations of Fine-Grained Visual Descriptions. CVPR 2016: 49-58 - [c55]Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang:
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network. CVPR 2016: 193-202 - [c54]Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CVPR 2016: 3204-3212 - [c53]Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee:
Attribute2Image: Conditional Image Generation from Visual Attributes. ECCV (4) 2016: 776-791 - [c52]Yuting Zhang, Kibok Lee, Honglak Lee:
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification. ICML 2016: 612-621 - [c51]Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee:
Generative Adversarial Text to Image Synthesis. ICML 2016: 1060-1069 - [c50]Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee:
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. ICML 2016: 2217-2225 - [c49]Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. ICML 2016: 2790-2799 - [c48]Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee:
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. IJCAI 2016: 1519-1525 - [c47]Rui Zhang, Honglak Lee, Dragomir R. Radev:
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents. HLT-NAACL 2016: 1512-1521 - [c46]Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee:
Learning What and Where to Draw. NIPS 2016: 217-225 - [c45]Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee:
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision. NIPS 2016: 1696-1704 - [c44]Wenling Shang, Kihyuk Sohn, Honglak Lee, Anna C. Gilbert:
Discriminative Training of Structured Dictionaries via Block Orthogonal Matching Pursuit. SDM 2016: 243-251 - [i18]Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee:
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis. CoRR abs/1601.00706 (2016) - [i17]Jimei Yang, Brian L. Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang:
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network. CoRR abs/1603.04530 (2016) - [i16]Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee:
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. CoRR abs/1603.05201 (2016) - [i15]Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee:
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. CoRR abs/1604.07095 (2016) - [i14]Scott E. Reed, Zeynep Akata, Bernt Schiele, Honglak Lee:
Learning Deep Representations of Fine-grained Visual Descriptions. CoRR abs/1605.05395 (2016) - [i13]Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee:
Generative Adversarial Text to Image Synthesis. CoRR abs/1605.05396 (2016) - [i12]Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. CoRR abs/1605.09128 (2016) - [i11]Yuting Zhang, Kibok Lee, Honglak Lee:
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification. CoRR abs/1606.06582 (2016) - [i10]Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee:
Learning What and Where to Draw. CoRR abs/1610.02454 (2016) - [i9]Weiran Wang, Honglak Lee, Karen Livescu:
Deep Variational Canonical Correlation Analysis. CoRR abs/1610.03454 (2016) - [i8]Rui Zhang, Honglak Lee, Dragomir R. Radev:
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents. CoRR abs/1611.02361 (2016) - [i7]Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev:
Sentence Ordering using Recurrent Neural Networks. CoRR abs/1611.02654 (2016) - [i6]Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee:
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision. CoRR abs/1612.00814 (2016) - 2015
- [j4]Ian Lenz, Honglak Lee, Ashutosh Saxena:
Deep learning for detecting robotic grasps. Int. J. Robotics Res. 34(4-5): 705-724 (2015) - [j3]Yoshua Bengio, Honglak Lee:
Editorial introduction to the Neural Networks special issue on Deep Learning of Representations. Neural Networks 64: 1-3 (2015) - [c43]Yuting Zhang, Kihyuk Sohn, Ruben Villegas, Gang Pan, Honglak Lee:
Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction. CVPR 2015: 249-258 - [c42]Zeynep Akata, Scott E. Reed, Daniel Walter, Honglak Lee, Bernt Schiele:
Evaluation of output embeddings for fine-grained image classification. CVPR 2015: 2927-2936 - [c41]Changhan Wang, Xinchen Yan, Max Smith, Kanika Kochhar, Marcie Rubin, Stephen M. Warren, James S. Wrobel, Honglak Lee:
A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks. EMBC 2015: 2415-2418 - [c40]Jimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee:
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis. NIPS 2015: 1099-1107 - [c39]Scott E. Reed, Yi Zhang, Yuting Zhang, Honglak Lee:
Deep Visual Analogy-Making. NIPS 2015: 1252-1260 - [c38]Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh:
Action-Conditional Video Prediction using Deep Networks in Atari Games. NIPS 2015: 2863-2871 - [c37]Kihyuk Sohn, Honglak Lee, Xinchen Yan:
Learning Structured Output Representation using Deep Conditional Generative Models. NIPS 2015: 3483-3491 - [c36]Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich:
Training Deep Neural Networks on Noisy Labels with Bootstrapping. ICLR (Workshop) 2015 - [i5]Yuting Zhang, Kihyuk Sohn, Ruben Villegas, Gang Pan, Honglak Lee:
Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction. CoRR abs/1504.03293 (2015) - [i4]Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh:
Action-Conditional Video Prediction using Deep Networks in Atari Games. CoRR abs/1507.08750 (2015) - [i3]Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee:
Attribute2Image: Conditional Image Generation from Visual Attributes. CoRR abs/1512.00570 (2015) - [i2]Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CoRR abs/1512.07928 (2015) - 2014
- [c35]Scott E. Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee:
Learning to Disentangle Factors of Variation with Manifold Interaction. ICML 2014: 1431-1439 - [c34]Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee:
Structured Recurrent Temporal Restricted Boltzmann Machines. ICML 2014: 1647-1655 - [c33]Kihyuk Sohn, Wenling Shang, Honglak Lee:
Improved Multimodal Deep Learning with Variation of Information. NIPS 2014: 2141-2149 - [c32]Xiaoxiao Guo, Satinder Singh, Honglak Lee, Richard L. Lewis, Xiaoshi Wang:
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning. NIPS 2014: 3338-3346 - [i1]Zeynep Akata, Honglak Lee, Bernt Schiele:
Zero-Shot Learning with Structured Embeddings. CoRR abs/1409.8403 (2014) - 2013
- [j2]Samy Bengio, Li Deng, Hugo Larochelle, Honglak Lee, Ruslan Salakhutdinov:
Guest Editors' Introduction: Special Section on Learning Deep Architectures. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1795-1797 (2013) - [c31]Roni Mittelman, Honglak Lee, Benjamin Kuipers, Silvio Savarese:
Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines. CVPR 2013: 476-483 - [c30]Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik G. Learned-Miller:
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling. CVPR 2013: 2019-2026 - [c29]Yelin Kim, Honglak Lee, Emily Mower Provost:
Deep learning for robust feature generation in audiovisual emotion recognition. ICASSP 2013: 3687-3691 - [c28]Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee:
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines. ICML (2) 2013: 217-225 - [c27]Forest Agostinelli, Michael R. Anderson, Honglak Lee:
Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising. NIPS 2013: 1493-1501 - [c26]Ian Lenz, Honglak Lee, Ashutosh Saxena:
Deep Learning for Detecting Robotic Grasps. Robotics: Science and Systems 2013 - [c25]Ian Lenz, Honglak Lee, Ashutosh Saxena:
Deep Learning for Detecting Robotic Grasps. ICLR (Workshop) 2013 - 2012
- [c24]Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese:
An efficient branch-and-bound algorithm for optimal human pose estimation. CVPR 2012: 1616-1623 - [c23]Gary B. Huang, Honglak Lee, Erik G. Learned-Miller:
Learning hierarchical representations for face verification with convolutional deep belief networks. CVPR 2012: 2518-2525 - [c22]Kihyuk Sohn, Honglak Lee:
Learning Invariant Representations with Local Transformations. ICML 2012 - [c21]Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller:
Learning to Align from Scratch. NIPS 2012: 773-781 - [c20]Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese:
Efficient and Exact MAP-MRF Inference using Branch and Bound. AISTATS 2012: 1134-1142 - [c19]Caoxie Zhang, Honglak Lee, Kang G. Shin:
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers. AISTATS 2012: 1398-1406 - [c18]Guanyu Zhou, Kihyuk Sohn, Honglak Lee:
Online Incremental Feature Learning with Denoising Autoencoders. AISTATS 2012: 1453-1461 - 2011
- [j1]Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng:
Unsupervised learning of hierarchical representations with convolutional deep belief networks. Commun. ACM 54(10): 95-103 (2011) - [c17]Kihyuk Sohn, Dae Yon Jung, Honglak Lee, Alfred O. Hero III:
Efficient learning of sparse, distributed, convolutional feature representations for object recognition. ICCV 2011: 2643-2650 - [c16]Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Y. Ng:
Multimodal Deep Learning. ICML 2011: 689-696 - [c15]Juhan Nam, Jiquan Ngiam, Honglak Lee, Malcolm Slaney:
A Classification-Based Polyphonic Piano Transcription Approach Using Learned Feature Representations. ISMIR 2011: 175-180 - [c14]Adam Coates, Andrew Y. Ng, Honglak Lee:
An Analysis of Single-Layer Networks in Unsupervised Feature Learning. AISTATS 2011: 215-223 - 2010
- [b1]Honglak Lee:
Unsupervised feature learning via sparse hierarchical representations. Stanford University, USA, 2010 - [c13]Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Kuang Chiu, Junling Hu, Honglak Lee:
An integrated machine learning approach to stroke prediction. KDD 2010: 183-192
2000 – 2009
- 2009
- [c12]Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng:
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. ICML 2009: 609-616 - [c11]Honglak Lee, Rajat Raina, Alex Teichman, Andrew Y. Ng:
Exponential Family Sparse Coding with Application to Self-taught Learning. IJCAI 2009: 1113-1119 - [c10]Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng:
Measuring Invariances in Deep Networks. NIPS 2009: 646-654 - [c9]Honglak Lee, Peter T. Pham, Yan Largman, Andrew Y. Ng:
Unsupervised feature learning for audio classification using convolutional deep belief networks. NIPS 2009: 1096-1104 - 2007
- [c8]Rajat Raina, Alexis J. Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng:
Self-taught learning: transfer learning from unlabeled data. ICML 2007: 759-766 - [c7]Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng:
Sparse deep belief net model for visual area V2. NIPS 2007: 873-880 - 2006
- [c6]Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng:
Efficient L1 Regularized Logistic Regression. AAAI 2006: 401-408 - [c5]Erick Delage, Honglak Lee, Andrew Y. Ng:
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image. CVPR (2) 2006: 2418-2428 - [c4]Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, Andrew Y. Ng:
Quadruped Robot Obstacle Negotiation via Reinforcement Learning. ICRA 2006: 3003-3010 - [c3]Honglak Lee, Alexis J. Battle, Rajat Raina, Andrew Y. Ng:
Efficient sparse coding algorithms. NIPS 2006: 801-808 - 2005
- [c2]Honglak Lee, Andrew Y. Ng:
Spam Deobfuscation using a Hidden Markov Model. CEAS 2005 - [c1]Erick Delage, Honglak Lee, Andrew Y. Ng:
Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes. ISRR 2005: 305-321
Coauthor Index
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