default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLu Yin 0006
Person information
- affiliation: University of Surrey, School of Computer Science and Electronic Engineering, UK
- affiliation: Eindhoven University of Technology, Eindhoven, The Netherlands
Other persons with the same name
- Lu Yin — disambiguation page
- Lu Yin 0001
![[0000-0002-4978-8439]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-4978-8439")
— Beijing University of Posts and Telecommunications, School of Electronic Engineering, Beijing, China - Lu Yin 0002 — Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, China
- Lu Yin 0003 — University of California San Diego, La Jolla, CA, USA
- Lu Yin 0004 — Harbin Institute of Technology (Shenzhen), Guangdong, China
- Lu Yin 0005 — Nanjing University of Science and Technology, Nanjing, China
Other persons with a similar name
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2025
[i33]Adarsh Kappiyath, Abhra Chaudhuri, Ajay Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin:
Sebra: Debiasing Through Self-Guided Bias Ranking. CoRR abs/2501.18277 (2025)- 2024
- [c21]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Tianlong Chen, Shiwei Liu, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. EMNLP 2024: 16943-16956 - [c20]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. EMNLP 2024: 18089-18099 - [c19]Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma:
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization. ICLR 2024 - [c18]Lu Yin, Ajay Kumar Jaiswal, Shiwei Liu, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs. ICML 2024 - [c17]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML 2024 - [c16]Jie Ji, Gen Li, Lu Yin, Minghai Qin, Geng Yuan, Linke Guo, Shiwei Liu, Xiaolong Ma:
Advancing Dynamic Sparse Training by Exploring Optimization Opportunities. ICML 2024 - [c15]Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy:
A Structural-Clustering Based Active Learning for Graph Neural Networks. IDA (1) 2024: 28-40 - [c14]Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu:
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. NeurIPS 2024 - [i32]Ajay Jaiswal, Bodun Hu, Lu Yin, Yeonju Ro, Shiwei Liu, Tianlong Chen, Aditya Akella:
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping. CoRR abs/2404.03865 (2024) - [i31]Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei Liu:
OwLore: Outlier-weighed Layerwise Sampled Low-Rank Projection for Memory-Efficient LLM Fine-tuning. CoRR abs/2405.18380 (2024) - [i30]Adriana Fernandez-Lopez, Honglie Chen, Pingchuan Ma, Lu Yin, Qiao Xiao, Stavros Petridis, Shiwei Liu, Maja Pantic:
MSRS: Training Multimodal Speech Recognition Models from Scratch with Sparse Mask Optimization. CoRR abs/2406.17614 (2024) - [i29]Qiao Xiao, Pingchuan Ma, Adriana Fernandez-Lopez, Boqian Wu, Lu Yin, Stavros Petridis, Mykola Pechenizkiy, Maja Pantic, Decebal Constantin Mocanu, Shiwei Liu:
Dynamic Data Pruning for Automatic Speech Recognition. CoRR abs/2406.18373 (2024) - [i28]Zhenyu Zhang, Ajay Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. CoRR abs/2407.08296 (2024) - [i27]Ajay Jaiswal, Lu Yin, Zhenyu Zhang, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. CoRR abs/2407.11239 (2024) - [i26]Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy:
Robust Active Learning (RoAL): Countering Dynamic Adversaries in Active Learning with Elastic Weight Consolidation. CoRR abs/2408.07364 (2024) - [i25]Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Are Sparse Neural Networks Better Hard Sample Learners? CoRR abs/2409.09196 (2024) - [i24]Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Kumar Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu:
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. CoRR abs/2410.07461 (2024) - [i23]Adriana Fernandez-Lopez, Shiwei Liu, Lu Yin, Stavros Petridis, Maja Pantic:
Full-Rank No More: Low-Rank Weight Training for Modern Speech Recognition Models. CoRR abs/2410.07771 (2024) - [i22]Yuxiang Guo, Lu Yin, Bo Jiang, Jiaqi Zhang:
TODO: Enhancing LLM Alignment with Ternary Preferences. CoRR abs/2411.02442 (2024) - [i21]Xinglei Wang, Tao Cheng, Stephen Law, Zichao Zeng, Lu Yin, Junyuan Liu:
Multimodal Contrastive Learning of Urban Space Representations from POI Data. CoRR abs/2411.06229 (2024) - [i20]Jiaxi Li, Lu Yin, Xilu Wang:
OWLed: Outlier-weighed Layerwise Pruning for Efficient Autonomous Driving Framework. CoRR abs/2411.07711 (2024) - [i19]Mingyu Cao, Gen Li, Jie Ji, Jiaqi Zhang, Xiaolong Ma, Shiwei Liu, Lu Yin:
Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning. CoRR abs/2412.00069 (2024) - [i18]Tim van Engeland, Lu Yin, Vlado Menkovski:
Aspect-Based Few-Shot Learning. CoRR abs/2412.16202 (2024) - 2023
- [j1]Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu:
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c13]Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy:
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI 2023: 10945-10953 - [c12]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? ICML 2023: 14023-14038 - [c11]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS 2023 - [c10]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) 2023: 113-130 - [c9]Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy:
REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training. ECML/PKDD (2) 2023: 313-329 - [i17]Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu:
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. CoRR abs/2303.07200 (2023) - [i16]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR abs/2305.19412 (2023) - [i15]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR abs/2305.19454 (2023) - [i14]Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy:
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR abs/2306.14275 (2023) - [i13]Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. CoRR abs/2310.02277 (2023) - [i12]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR abs/2310.05175 (2023) - [i11]Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy:
REST: Enhancing Group Robustness in DNNs through Reweighted Sparse Training. CoRR abs/2312.03044 (2023) - [i10]Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy:
A Structural-Clustering Based Active Learning for Graph Neural Networks. CoRR abs/2312.04307 (2023) - [i9]Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu:
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. CoRR abs/2312.04727 (2023) - 2022
- [c8]Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy:
Semantic-Based Few-Shot Classification by Psychometric Learning. IDA 2022: 392-403 - [c7]Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu:
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG 2022: 8 - [c6]Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy:
Superposing many tickets into one: A performance booster for sparse neural network training. UAI 2022: 2267-2277 - [i8]Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu:
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR abs/2205.15322 (2022) - [i7]Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy:
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR abs/2208.10842 (2022) - [i6]Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu:
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR abs/2211.15335 (2022) - 2021
- [c5]Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy:
Hierarchical Semantic Segmentation using Psychometric Learning. ACML 2021: 798-813 - [c4]Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. ICML 2021: 6989-7000 - [c3]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS 2021: 9908-9922 - [i5]Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR abs/2102.02887 (2021) - [i4]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu:
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR abs/2106.10404 (2021) - [i3]Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy:
Hierarchical Semantic Segmentation using Psychometric Learning. CoRR abs/2107.03212 (2021) - [i2]Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy:
Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. CoRR abs/2112.09201 (2021) - 2020
- [c2]Lu Yin:
Beyond Labels: Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. IJCAI 2020: 5214-5215 - [c1]Lu Yin, Vlado Menkovski, Mykola Pechenizkiy:
Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. ECML/PKDD (2) 2020: 154-169 - [i1]Lu Yin, Vlado Menkovski, Mykola Pechenizkiy:
Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. CoRR abs/2004.06353 (2020)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-03-04 02:01 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
