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2020 – today
- 2025
[j18]Taeeon Park
, Sangwon Jung, Sanghyuk Chun, Taesup Moon:
FairDRO: Group fairness regularization via classwise robust optimization. Neural Networks 182: 106891 (2025)- 2024
- [j17]Sunghwan Joo, Taesup Moon:
Debiased Learning via Composed Conceptual Sensitivity Regularization. IEEE Access 12: 170295-170308 (2024) - [c43]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 - [c42]Jaeseok Byun, Dohoon Kim, Taesup Moon:
MAFA: Managing False Negatives for Vision-Language Pre-Training. CVPR 2024: 27304-27314 - [c41]Donggyu Lee, Sangwon Jung, Taesup Moon:
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline. ICLR 2024 - [c40]Sungmin Cha, Kyunghyun Cho, Taesup Moon:
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning. ICML 2024 - [c39]Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon:
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. ICML 2024 - [c38]Sungmin Cha, Naeun Ko, Heewoong Choi, Youngjoon Yoo, Taesup Moon:
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations. WACV 2024: 3777-3787 - [i44]Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon:
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning. CoRR abs/2403.05066 (2024) - [i43]Jihwan Kwak, Sungmin Cha, Taesup Moon:
Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation. CoRR abs/2405.09858 (2024) - [i42]Jaeseok Byun, Seokhyeon Jeong, Wonjae Kim, Sanghyuk Chun, Taesup Moon:
Reducing Task Discrepancy of Text Encoders for Zero-Shot Composed Image Retrieval. CoRR abs/2406.09188 (2024) - [i41]Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon:
Listwise Reward Estimation for Offline Preference-based Reinforcement Learning. CoRR abs/2408.04190 (2024) - 2023
- [j16]Joonhyun Jeong, Sungmin Cha, Jongwon Choi, Sangdoo Yun, Taesup Moon, Youngjoon Yoo:
Observations on K-Image Expansion of Image-Mixing Augmentation. IEEE Access 11: 16631-16643 (2023) - [c37]Donggyu Lee, Sangwon Jung, Taesup Moon:
Issues for Continual Learning in the Presence of Dataset Bias. AAAI Bridge Program 2023: 92-99 - [c36]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. AAAI 2023: 8168-8176 - [c35]Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon:
Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning. CVPR 2023: 20127-20136 - [c34]Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon:
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. ICLR 2023 - [c33]Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon:
SwiFT: Swin 4D fMRI Transformer. NeurIPS 2023 - [i40]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) - [i39]Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon:
Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization. CoRR abs/2303.00442 (2023) - [i38]Donggyu Lee, Sangwon Jung, Taesup Moon:
Continual Learning in the Presence of Spurious Correlation. CoRR abs/2303.11863 (2023) - [i37]Sungmin Cha, Taesup Moon:
Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning. CoRR abs/2306.05101 (2023) - [i36]Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, Taesup Moon:
SwiFT: Swin 4D fMRI Transformer. CoRR abs/2307.05916 (2023) - [i35]Juhyeon Park, Seokhyeon Jeong, Taesup Moon:
TLDR: Text Based Last-layer Retraining for Debiasing Image Classifiers. CoRR abs/2311.18291 (2023) - [i34]Jaeseok Byun, Dohoon Kim, Taesup Moon:
Converting and Smoothing False Negatives for Vision-Language Pre-training. CoRR abs/2312.06112 (2023) - 2022
- [j15]Taeeon Park, Jihwan Kwak, Hongjoon Ahn, Jinwoong Lee, Jaehyuk Lim, Sangho Yu, Changhwan Shin, Taesup Moon:
GAN-Based Framework for Unified Estimation of Process-Induced Random Variation in FinFET. IEEE Access 10: 130001-130023 (2022) - [j14]Donggyu Lee, Hyeongmin Park, Taesup Moon, Youngwook Kim:
Continual Learning of Micro-Doppler Signature-Based Human Activity Classification. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [c32]Sangwon Jung, Sanghyuk Chun, Taesup Moon:
Learning Fair Classifiers with Partially Annotated Group Labels. CVPR 2022: 10338-10347 - [c31]Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon:
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. ECCV (19) 2022: 395-412 - [c30]Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf:
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. NeurIPS 2022 - [e1]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable AI - International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers. Lecture Notes in Computer Science 13200, Springer 2022, ISBN 978-3-031-04082-5 [contents] - [i33]Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon:
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning. CoRR abs/2201.12559 (2022) - [i32]Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon:
Is Continual Learning Truly Learning Representations Continually? CoRR abs/2206.08101 (2022) - [i31]Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon:
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR abs/2206.11081 (2022) - [i30]Jaeseok Byun, Taebaek Hwang, Jianlong Fu, Taesup Moon:
GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training. CoRR abs/2208.04060 (2022) - [i29]Sunghwan Joo, Seokhyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon:
Towards More Robust Interpretation via Local Gradient Alignment. CoRR abs/2211.15900 (2022) - 2021
- [j13]Yong Sung Kil, Jun Min Song, Sang-Hyo Kim, Taesup Moon, Seok-Ho Chang:
Deep Learning Aided Blind Synchronization Word Estimation. IEEE Access 9: 30321-30334 (2021) - [c29]Jaeseok Byun, Sungmin Cha, Taesup Moon:
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CVPR 2021: 5768-5777 - [c28]Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon:
Fair Feature Distillation for Visual Recognition. CVPR 2021: 12115-12124 - [c27]Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, Taesup Moon:
SS-IL: Separated Softmax for Incremental Learning. ICCV 2021: 824-833 - [c26]Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flávio P. Calmon, Taesup Moon:
CPR: Classifier-Projection Regularization for Continual Learning. ICLR 2021 - [c25]Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon:
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images. ICLR 2021 - [c24]Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon:
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. NeurIPS 2021: 10919-10930 - [i28]Jaeseok Byun, Sungmin Cha, Taesup Moon:
FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise. CoRR abs/2105.10967 (2021) - [i27]Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon:
Fair Feature Distillation for Visual Recognition. CoRR abs/2106.04411 (2021) - [i26]Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon:
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning. CoRR abs/2106.11562 (2021) - [i25]Sungmin Cha, Naeun Ko, Youngjoon Yoo, Taesup Moon:
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack. CoRR abs/2106.11644 (2021) - [i24]Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi:
Observations on K-image Expansion of Image-Mixing Augmentation for Classification. CoRR abs/2110.04248 (2021) - [i23]Sungmin Cha, Seonwoo Min, Sungroh Yoon, Taesup Moon:
Supervised Neural Discrete Universal Denoiser for Adaptive Denoising. CoRR abs/2111.12350 (2021) - [i22]Sangwon Jung, Sanghyuk Chun, Taesup Moon:
Learning Fair Classifiers with Partially Annotated Group Labels. CoRR abs/2111.14581 (2021) - 2020
- [j12]Jaeseok Byun, Taesup Moon:
Learning Blind Pixelwise Affine Image Denoiser With Single Noisy Images. IEEE Signal Process. Lett. 27: 1105-1109 (2020) - [c23]Taeeon Park, Taesup Moon:
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. AISTATS 2020: 331-340 - [c22]Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, Wojciech Samek:
xxAI - Beyond Explainable Artificial Intelligence. xxAI@ICML 2020: 3-10 - [c21]Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon:
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization. NeurIPS 2020 - [c20]Hongjoon Ahn, Taesup Moon:
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. UAI 2020: 91-100 - [i21]Taeeon Park, Taesup Moon:
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel. CoRR abs/2003.02623 (2020) - [i20]Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon:
Adaptive Group Sparse Regularization for Continual Learning. CoRR abs/2003.13726 (2020) - [i19]Hongjoon Ahn, Taesup Moon:
A Simple Class Decision Balancing for Incremental Learning. CoRR abs/2003.13947 (2020) - [i18]Sungmin Cha, Hsiang Hsu, Flávio P. Calmon, Taesup Moon:
CPR: Classifier-Projection Regularization for Continual Learning. CoRR abs/2006.07326 (2020)
2010 – 2019
- 2019
- [j11]Toan Duc Bui, Jitae Shin, Taesup Moon:
Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation. Biomed. Signal Process. Control. 54 (2019) - [c19]Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee:
Subtask Gated Networks for Non-Intrusive Load Monitoring. AAAI 2019: 1150-1157 - [c18]Sunghwan Joo, Sungmin Cha, Taesup Moon:
DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. AAAI 2019: 4031-4038 - [c17]Sungmin Cha, Taesup Moon:
Fully Convolutional Pixel Adaptive Image Denoiser. ICCV 2019: 4159-4168 - [c16]Juyeon Heo, Sunghwan Joo, Taesup Moon:
Fooling Neural Network Interpretations via Adversarial Model Manipulation. NeurIPS 2019: 2921-2932 - [c15]Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon:
Uncertainty-based Continual Learning with Adaptive Regularization. NeurIPS 2019: 4394-4404 - [c14]Yongbee Park, Taesup Moon:
Working Vacation Scheduling of MX/M/1/N System using Neural Network. RiTA 2019: 20-25 - [i17]Juyeon Heo, Sunghwan Joo, Taesup Moon:
Fooling Neural Network Interpretations via Adversarial Model Manipulation. CoRR abs/1902.02041 (2019) - [i16]Sunghwan Joo, Sungmin Cha, Taesup Moon:
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling. CoRR abs/1902.02530 (2019) - [i15]Hongjoon Ahn, Taesup Moon:
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty. CoRR abs/1902.08921 (2019) - [i14]Sungmin Cha, Taeeon Park, Taesup Moon:
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images. CoRR abs/1905.10488 (2019) - [i13]Hongjoon Ahn, Donggyu Lee, Sungmin Cha, Taesup Moon:
Uncertainty-based Continual Learning with Adaptive Regularization. CoRR abs/1905.11614 (2019) - 2018
- [c13]Sungmin Cha, Taesup Moon:
Neural Adaptive Image Denoiser. ICASSP 2018: 2981-2985 - [c12]Sungmin Cha, Taesup Moon:
UDLR Convolutional Network for Adaptive Image Denoiser. RiTA 2018: 55-61 - [i12]Sungmin Cha, Taesup Moon:
Fully Convolutional Pixel Adaptive Image Denoiser. CoRR abs/1807.07569 (2018) - [i11]Changho Shin, Sunghwan Joo, Jaeryun Yim, Hyoseop Lee, Taesup Moon, Wonjong Rhee:
Subtask Gated Networks for Non-Intrusive Load Monitoring. CoRR abs/1811.06692 (2018) - 2017
- [i10]Toan Duc Bui, Jitae Shin, Taesup Moon:
3D Densely Convolutional Networks for Volumetric Segmentation. CoRR abs/1709.03199 (2017) - [i9]Taesup Moon:
Uniform Concentration of the Loss Estimator for Neural DUDE. CoRR abs/1709.03657 (2017) - [i8]Sungmin Cha, Taesup Moon:
Neural Affine Grayscale Image Denoising. CoRR abs/1709.05672 (2017) - 2016
- [j10]Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon:
Regularization and Kernelization of the Maximin Correlation Approach. IEEE Access 4: 1385-1392 (2016) - [j9]Youngwook Kim, Taesup Moon:
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks. IEEE Geosci. Remote. Sens. Lett. 13(1): 8-12 (2016) - [j8]Jinhee Park, Rios Jesus Javier, Taesup Moon, Youngwook Kim:
Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks. Sensors 16(12): 1990 (2016) - [c11]Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon:
Neural Universal Discrete Denoiser. NIPS 2016: 4772-4780 - [i7]Taesup Moon, Seonwoo Min:
Neural Universal Discrete Denoiser. CoRR abs/1605.07779 (2016) - 2015
- [j7]Taesup Moon, Yueqing Wang, Yang Liu, Bin Yu:
Evaluation of a MISR-Based High-Resolution Aerosol Retrieval Method Using AERONET DRAGON Campaign Data. IEEE Trans. Geosci. Remote. Sens. 53(8): 4328-4339 (2015) - [c10]Taesup Moon, Heeyoul Choi, Hoshik Lee, Inchul Song:
RNNDROP: A novel dropout for RNNS in ASR. ASRU 2015: 65-70 - [i6]Taehoon Lee, Taesup Moon, Seung Jean Kim, Sungroh Yoon:
Regularization and Kernelization of the Maximin Correlation Approach. CoRR abs/1502.06105 (2015) - [i5]Byunghan Lee, Taesup Moon, Sungroh Yoon, Tsachy Weissman:
DUDE-Seq: Fast Universal Denoising of Nucleotide Sequences. CoRR abs/1511.04836 (2015) - 2014
- [j6]Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang:
Exploiting User Preference for Online Learning in Web Content Optimization Systems. ACM Trans. Intell. Syst. Technol. 5(2): 33:1-33:23 (2014) - 2012
- [j5]Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang:
An Online Learning Framework for Refining Recency Search Results with User Click Feedback. ACM Trans. Inf. Syst. 30(4): 20:1-20:28 (2012) - [j4]Taesup Moon:
Universal Switching FIR Filtering. IEEE Trans. Signal Process. 60(3): 1460-1464 (2012) - [c9]Lihong Li, Wei Chu, John Langford, Taesup Moon, Xuanhui Wang:
Bandits with Generalized Linear Models. ICML On-line Trading of Exploration and Exploitation 2012: 19-36 - 2011
- [c8]Taesup Moon, Tsachy Weissman, Jae-Young Kim:
Discrete denoising of heterogeneous two-dimensional data. ISIT 2011: 1041-1045 - [c7]Yuanhua Lv, Taesup Moon, Pranam Kolari, Zhaohui Zheng, Xuanhui Wang, Yi Chang:
Learning to model relatedness for news recommendation. WWW 2011: 57-66 - [i4]Taesup Moon, Wei Chu, Lihong Li, Zhaohui Zheng, Yi Chang:
Refining Recency Search Results with User Click Feedback. CoRR abs/1103.3735 (2011) - 2010
- [c6]Taesup Moon, Georges Dupret, Shihao Ji, Ciya Liao, Zhaohui Zheng:
User behavior driven ranking without editorial judgments. CIKM 2010: 1473-1476 - [c5]Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohui Zheng, Yi Chang:
Online learning for recency search ranking using real-time user feedback. CIKM 2010: 1501-1504 - [c4]Taesup Moon, Alexander J. Smola, Yi Chang, Zhaohui Zheng:
IntervalRank: isotonic regression with listwise and pairwise constraints. WSDM 2010: 151-160 - [i3]Taesup Moon, Tsachy Weissman, Jae-Young Kim:
Discrete denoising of heterogenous two-dimensional data. CoRR abs/1007.1799 (2010)
2000 – 2009
- 2009
- [j3]Taesup Moon, Tsachy Weissman:
Discrete denoising with shifts. IEEE Trans. Inf. Theory 55(11): 5284-5301 (2009) - [j2]Taesup Moon, Tsachy Weissman:
Universal FIR MMSE Filtering. IEEE Trans. Signal Process. 57(3): 1068-1083 (2009) - 2008
- [j1]Taesup Moon, Tsachy Weissman:
Universal Filtering Via Hidden Markov Modeling. IEEE Trans. Inf. Theory 54(2): 692-708 (2008) - 2007
- [c3]Taesup Moon, Tsachy Weissman:
Competitive On-line Linear FIR MMSE Filtering. ISIT 2007: 1126-1130 - [i2]Taesup Moon, Tsachy Weissman:
Discrete Denoising with Shifts. CoRR abs/0708.2566 (2007) - 2006
- [c2]Yejin Kim, Hyeon Bae, Kyungmin Poo, Jongrack Kim, Taesup Moon, Sungshin Kim, Changwon Kim:
Soft Sensor Using PNN Model and Rule Base for Wastewater Treatment Plant. ISNN (2) 2006: 1261-1269 - [i1]Taesup Moon, Tsachy Weissman:
Universal Filtering via Hidden Markov Modeling. CoRR abs/cs/0605077 (2006) - 2005
- [c1]Taesup Moon, Tsachy Weissman:
Discrete universal filtering via hidden Markov modelling. ISIT 2005: 1285-1289
Coauthor Index
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