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ORCIDKangwook Lee 0001
Kang Wook Lee 0001
Person information
- affiliation: University of Wisconsin Madison, WI, USA
- affiliation (2016 - 2019): Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- affiliation (PhD 2016): University of California Berkeley, CA, USA
Other persons with the same name
- Kang Wook Lee 0002 (aka: Kangwook Lee 0002) — Tohoku University, Sendai, Japan
- Kang-Wook Lee 0003 (aka: Kangwook Lee 0003) — Thomas J. Watson Research Center, IBM Research Division, Yorktown Heights, NY
- Kangwook Lee 0004 — Samsung Research
- Kangwook Lee 0005 — Amkor Technology Korea, Inc, Incheon, South Korea
- Kangwook Lee 0006 — Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Kangwook Lee 0007 — Georgia Institute of Technology, School of Chemical Engineering, Atlanta, GA, USA
- Kangwook Lee 0008 — Synopsys Korea, Yongin-Si, South Korea
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2020 – today
- 2026
[c67]Minjae Lee, Wonjun Kang, Byeongkeun Ahn, Christian Classen, Kevin Galim, Seunghyuk Oh, Minghao Yan, Hyung Il Koo, Kangwook Lee:
TABED: Test-Time Adaptive Ensemble Drafting for Robust Speculative Decoding in LVLMs. EACL (Findings) 2026: 3948-3974- [i71]Minjae Lee, Wonjun Kang, Byeongkeun Ahn, Christian Classen, Kevin Galim, Seunghyuk Oh, Minghao Yan, Hyung Il Koo, Kangwook Lee:
TABED: Test-Time Adaptive Ensemble Drafting for Robust Speculative Decoding in LVLMs. CoRR abs/2601.20357 (2026) - [i70]Jongwon Jeong, Jungtaek Kim, Kangwook Lee:
TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents. CoRR abs/2602.19633 (2026) - [i69]Chungpa Lee, Jy-yong Sohn, Kangwook Lee:
Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models. CoRR abs/2602.23197 (2026) - [i68]Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-Yong Sohn, Hyung Il Koo, Kangwook Lee:
Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback. CoRR abs/2603.24780 (2026) - [i67]Yoonho Lee, Roshen Nair, Qizheng Zhang, Kangwook Lee, Omar Khattab, Chelsea Finn:
Meta-Harness: End-to-End Optimization of Model Harnesses. CoRR abs/2603.28052 (2026) - 2025
- [j20]Shenghong Dai, Jy-yong Sohn, Yicong Chen, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee:
Buffer-based Gradient Projection for Continual Federated Learning. Trans. Mach. Learn. Res. 2025 (2025) - [j19]Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee:
Encoder-only Next Token Prediction. Trans. Mach. Learn. Res. 2025 (2025) - [j18]Ruisu Zhang, Yicong Chen, Kangwook Lee:
Improving CLIP Counting Accuracy via Parameter-Efficient Fine-Tuning. Trans. Mach. Learn. Res. 2025 (2025) - [c66]Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee:
Looped Transformers for Length Generalization. ICLR 2025 - [c65]Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho:
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. ICLR 2025 - [c64]Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos:
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. ICLR 2025 - [c63]Thomas Zeng, Shuibai Zhang, Shutong Wu, Christian Classen, Daewon Chae, Ethan Ewer, Minjae Lee, Heeju Kim, Wonjun Kang, Jackson Kunde, Ying Fan, Jungtaek Kim, Hyung Il Koo, Kannan Ramchandran, Dimitris Papailiopoulos, Kangwook Lee:
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. ICML 2025 - [c62]Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee:
Parameter-Efficient Fine-Tuning of State Space Models. ICML 2025 - [c61]Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos:
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges. ICML 2025 - [c60]Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos:
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. ICML 2025 - [i66]Liu Yang, Ziqian Lin, Kangwook Lee, Dimitris Papailiopoulos, Robert D. Nowak:
Task Vectors in In-Context Learning: Emergence, Formation, and Benefit. CoRR abs/2501.09240 (2025) - [i65]Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos:
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges. CoRR abs/2502.01612 (2025) - [i64]Thomas Zeng, Shuibai Zhang, Shutong Wu, Christian Classen, Daewon Chae, Ethan Ewer, Minjae Lee, Heeju Kim, Wonjun Kang, Jackson Kunde, Ying Fan, Jungtaek Kim, Hyung Il Koo, Kannan Ramchandran, Dimitris Papailiopoulos, Kangwook Lee:
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. CoRR abs/2502.06737 (2025) - [i63]Erica Zhang, Ryunosuke Goto, Naomi Sagan, Jurik Mutter, Nick Phillips, Ash A. Alizadeh, Kangwook Lee, Jose H. Blanchet, Mert Pilanci, Robert Tibshirani:
LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization. CoRR abs/2502.10648 (2025) - [i62]Ziqian Lin, Shubham Kumar Bharti, Kangwook Lee:
In-Context Learning with Hypothesis-Class Guidance. CoRR abs/2502.19787 (2025) - [i61]Dongmin Park, Minkyu Kim, Beongjun Choi, Junhyuck Kim, Keon Lee, Jonghyun Lee, Inkyu Park, Byeong-Uk Lee, Jaeyoung Hwang, Jaewoo Ahn, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Biswas, Yoshi Suhara, Kangwook Lee, Jaewoong Cho:
Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games. CoRR abs/2506.03610 (2025) - [i60]Kevin Galim, Ethan Ewer, Wonjun Kang, Minjae Lee, Hyung Il Koo, Kangwook Lee:
Draft-based Approximate Inference for LLMs. CoRR abs/2506.08373 (2025) - [i59]Soyeon Choi, Kangwook Lee, Oliver Sng, Joshua M. Ackerman:
Infected Smallville: How Disease Threat Shapes Sociality in LLM Agents. CoRR abs/2506.13783 (2025) - [i58]Wonjun Kang, Kevin Galim, Seunghyuk Oh, Minjae Lee, Yuchen Zeng, Shuibai Zhang, Coleman Hooper, Yuezhou Hu, Hyung Il Koo, Nam Ik Cho, Kangwook Lee:
ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs. CoRR abs/2510.04767 (2025) - [i57]Chungpa Lee, Thomas Zeng, Jongwon Jeong, Jy-yong Sohn, Kangwook Lee:
How to Correctly Report LLM-as-a-Judge Evaluations. CoRR abs/2511.21140 (2025) - [i56]Yuchen Zeng, Shuibai Zhang, Wonjun Kang, Shutong Wu, Lynnix Zou, Ying Fan, Heeju Kim, Ziqian Lin, Jungtaek Kim, Hyung Il Koo, Dimitris Papailiopoulos, Kangwook Lee:
ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning. CoRR abs/2512.00831 (2025) - 2024
- [j17]Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak:
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression. J. Mach. Learn. Res. 25: 231:1-231:40 (2024) - [j16]Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee:
Mini-Batch Optimization of Contrastive Loss. Trans. Mach. Learn. Res. 2024 (2024) - [j15]Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee:
Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding. Trans. Mach. Learn. Res. 2024 (2024) - [j14]Won Joon Yun
, Myungjae Shin, David Mohaisen, Kangwook Lee, Joongheon Kim:
Hierarchical Deep Reinforcement Learning-Based Propofol Infusion Assistant Framework in Anesthesia. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2510-2521 (2024) - [c59]Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee:
Image Clustering Conditioned on Text Criteria. ICLR 2024 - [c58]Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos:
Teaching Arithmetic to Small Transformers. ICLR 2024 - [c57]Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos:
Looped Transformers are Better at Learning Learning Algorithms. ICLR 2024 - [c56]Yuchen Zeng, Kangwook Lee:
The Expressive Power of Low-Rank Adaptation. ICLR 2024 - [c55]Ziqian Lin, Kangwook Lee:
Dual Operating Modes of In-Context Learning. ICML 2024: 30135-30188 - [c54]Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos:
Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks. ICML 2024: 39793-39812 - [c53]Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee:
Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks. UAI 2024: 3264-3278 - [i55]Yuchen Zeng, Wonjun Kang, Yicong Chen, Hyung Il Koo, Kangwook Lee:
Can MLLMs Perform Text-to-Image In-Context Learning? CoRR abs/2402.01293 (2024) - [i54]Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos:
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks. CoRR abs/2402.04248 (2024) - [i53]Ziqian Lin, Kangwook Lee:
Dual Operating Modes of In-Context Learning. CoRR abs/2402.18819 (2024) - [i52]Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos:
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. CoRR abs/2406.19292 (2024) - [i51]Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee:
Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks. CoRR abs/2408.00359 (2024) - [i50]Shenghong Dai, Jy-yong Sohn, Yicong Chen, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee:
Buffer-based Gradient Projection for Continual Federated Learning. CoRR abs/2409.01585 (2024) - [i49]Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee:
Looped Transformers for Length Generalization. CoRR abs/2409.15647 (2024) - [i48]Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee:
ENTP: Encoder-only Next Token Prediction. CoRR abs/2410.01600 (2024) - [i47]Zheyang Xiong, Ziyang Cai, John Cooper, Albert Ge, Vasilis Papageorgiou, Zack Sifakis, Angeliki Giannou, Ziqian Lin, Liu Yang, Saurabh Agarwal, Grigorios G. Chrysos, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos:
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. CoRR abs/2410.05603 (2024) - [i46]Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee:
Parameter-Efficient Fine-Tuning of State Space Models. CoRR abs/2410.09016 (2024) - [i45]Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho:
Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. CoRR abs/2410.22376 (2024) - [i44]Ozgur Guldogan, Jackson Kunde, Kangwook Lee, Ramtin Pedarsani:
Multi-Bin Batching for Increasing LLM Inference Throughput. CoRR abs/2412.04504 (2024) - 2023
- [c52]Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee:
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. ACL (Findings) 2023: 4536-4554 - [c51]Shenghong Dai, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Kangwook Lee, Suman Banerjee, Nageen Himayat:
Online Federated Learning based Object Detection across Autonomous Vehicles in a Virtual World. CCNC 2023: 919-920 - [c50]Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee:
Equal Improvability: A New Fairness Notion Considering the Long-term Impact. ICLR 2023 - [c49]Ying Fan, Kangwook Lee:
Optimizing DDPM Sampling with Shortcut Fine-Tuning. ICML 2023: 9623-9639 - [c48]Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos:
Looped Transformers as Programmable Computers. ICML 2023: 11398-11442 - [c47]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
Improving Fair Training under Correlation Shifts. ICML 2023: 29179-29209 - [c46]Yuchen Zeng, Hongxu Chen, Kangwook Lee:
Federated Learning with Local Fairness Constraints. ISIT 2023: 1937-1942 - [c45]Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee:
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS 2023 - [i43]Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris S. Papailiopoulos:
Looped Transformers as Programmable Computers. CoRR abs/2301.13196 (2023) - [i42]Ying Fan, Kangwook Lee:
Optimizing DDPM Sampling with Shortcut Fine-Tuning. CoRR abs/2301.13362 (2023) - [i41]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
Improving Fair Training under Correlation Shifts. CoRR abs/2302.02323 (2023) - [i40]Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee:
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. CoRR abs/2305.04533 (2023) - [i39]Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee:
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR abs/2305.16381 (2023) - [i38]Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak:
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization. CoRR abs/2305.16534 (2023) - [i37]Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos:
Teaching Arithmetic to Small Transformers. CoRR abs/2307.03381 (2023) - [i36]Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee:
Mini-Batch Optimization of Contrastive Loss. CoRR abs/2307.05906 (2023) - [i35]Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris S. Papailiopoulos, Kangwook Lee:
Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding. CoRR abs/2307.05908 (2023) - [i34]Yuchen Zeng, Kangwook Lee:
The Expressive Power of Low-Rank Adaptation. CoRR abs/2310.17513 (2023) - [i33]Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee:
Image Clustering Conditioned on Text Criteria. CoRR abs/2310.18297 (2023) - [i32]Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos:
Looped Transformers are Better at Learning Learning Algorithms. CoRR abs/2311.12424 (2023) - 2022
- [j13]Kangwook Lee, Nihar B. Shah, Longbo Huang, Kannan Ramchandran:
Addendum and Erratum to "The MDS Queue: Analysing the Latency Performance of Erasure Codes". IEEE Trans. Inf. Theory 68(9): 5850-5851 (2022) - [c44]Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee:
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. EMNLP (Findings) 2022: 154-168 - [c43]Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos:
Permutation-Based SGD: Is Random Optimal? ICLR 2022 - [c42]Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee:
GenLabel: Mixup Relabeling using Generative Models. ICML 2022: 20278-20313 - [c41]Changhun Jo, Jy-yong Sohn, Kangwook Lee:
Breaking Fair Binary Classification with Optimal Flipping Attacks. ISIT 2022: 1453-1458 - [c40]Michael Gira, Ruisu Zhang, Kangwook Lee:
Debiasing Pre-Trained Language Models via Efficient Fine-Tuning. LT-EDI 2022: 59-69 - [c39]Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee:
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks. NeurIPS 2022 - [c38]Dohyun Kwon, Ying Fan, Kangwook Lee:
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. NeurIPS 2022 - [c37]Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos:
Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS 2022 - [i31]Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee:
GenLabel: Mixup Relabeling using Generative Models. CoRR abs/2201.02354 (2022) - [i30]Tuan Dinh, Daewon Seo, Zhixu Du, Liang Shang, Kangwook Lee:
Improved Input Reprogramming for GAN Conditioning. CoRR abs/2201.02692 (2022) - [i29]Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Kangwook Lee, Dimitris S. Papailiopoulos:
Rare Gems: Finding Lottery Tickets at Initialization. CoRR abs/2202.12002 (2022) - [i28]Changhun Jo, Jy-yong Sohn, Kangwook Lee:
Breaking Fair Binary Classification with Optimal Flipping Attacks. CoRR abs/2204.05472 (2022) - [i27]Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee:
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. CoRR abs/2205.11616 (2022) - [i26]Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee:
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks. CoRR abs/2206.06565 (2022) - [i25]Liu Yang, Jifan Zhang, Joseph Shenouda, Dimitris S. Papailiopoulos, Kangwook Lee, Robert D. Nowak:
A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets. CoRR abs/2210.03069 (2022) - [i24]Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee:
Equal Improvability: A New Fairness Notion Considering the Long-term Impact. CoRR abs/2210.06732 (2022) - [i23]Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin:
Outlier-Robust Group Inference via Gradient Space Clustering. CoRR abs/2210.06759 (2022) - [i22]Dohyun Kwon, Ying Fan, Kangwook Lee:
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. CoRR abs/2212.06359 (2022) - 2021
- [j12]Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh:
Predicting vehicle collisions using data collected from video games. Mach. Vis. Appl. 32(4): 93 (2021) - [j11]Suman Banerjee, Remzi H. Arpaci-Dusseau, Shenghong Dai, Kassem Fawaz, Mohit Gupta, Kangwook Lee, Shivaram Venkataraman:
The Roaming Edge and its Applications. GetMobile Mob. Comput. Commun. 25(4): 5-11 (2021) - [c36]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
FairBatch: Batch Selection for Model Fairness. ICLR 2021 - [c35]Tuan Dinh, Kangwook Lee:
Coded-InvNet for Resilient Prediction Serving Systems. ICML 2021: 2749-2759 - [c34]Changhun Jo, Kangwook Lee:
Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information. ICML 2021: 5107-5117 - [c33]Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos:
Adaptive Gradient Communication via Critical Learning Regime Identification. MLSys 2021 - [c32]Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh:
Sample Selection for Fair and Robust Training. NeurIPS 2021: 815-827 - [c31]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. NeurIPS 2021: 29898-29908 - [i21]Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos:
Permutation-Based SGD: Is Random Optimal? CoRR abs/2102.09718 (2021) - [i20]Tuan Dinh, Kangwook Lee:
Coded-InvNet for Resilient Prediction Serving Systems. CoRR abs/2106.06445 (2021) - [i19]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
Sample Selection for Fair and Robust Training. CoRR abs/2110.14222 (2021) - [i18]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. CoRR abs/2110.14962 (2021) - [i17]Yuchen Zeng, Hongxu Chen, Kangwook Lee:
Improving Fairness via Federated Learning. CoRR abs/2110.15545 (2021) - 2020
- [j10]Hyemin Han, Kangwook Lee, Firat Soylu:
Applying the Deep Learning Method for Simulating Outcomes of Educational Interventions. SN Comput. Sci. 1(2): 70 (2020) - [c30]Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh:
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training. ICML 2020: 8147-8157 - [c29]Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos:
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. NeurIPS 2020 - [c28]Kangwook Lee, Changho Suh, Kannan Ramchandran:
Reprogramming GANs via Input Noise Design. ECML/PKDD (2) 2020: 256-271 - [i16]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
FR-Train: A mutual information-based approach to fair and robust training. CoRR abs/2002.10234 (2020) - [i15]Changhun Jo, Kangwook Lee:
Discrete-valued Preference Estimation with Graph Side Information. CoRR abs/2003.07040 (2020) - [i14]Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos:
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. CoRR abs/2007.05084 (2020) - [i13]Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos:
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification. CoRR abs/2010.16248 (2020) - [i12]Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh:
FairBatch: Batch Selection for Model Fairness. CoRR abs/2012.01696 (2020)
2010 – 2019
- 2019
- [j9]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Community Recovery in Hypergraphs. IEEE Trans. Inf. Theory 65(10): 6561-6579 (2019) - [j8]Kangwook Lee, Kabir Chandrasekher, Ramtin Pedarsani, Kannan Ramchandran:
SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing Based on Sparse-Graph Codes. IEEE Trans. Signal Process. 67(17): 4649-4664 (2019) - [c27]Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh:
Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator. AAAI 2019: 978-985 - [c26]Kangwook Lee, Hoon Kim, Kyungmin Lee, Changho Suh, Kannan Ramchandran:
Synthesizing Differentially Private Datasets using Random Mixing. ISIT 2019: 542-546 - 2018
- [j7]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. IEEE J. Sel. Top. Signal Process. 12(5): 959-974 (2018) - [j6]Hyemin Han, Kangwook Lee, Firat Soylu:
Simulating outcomes of interventions using a multipurpose simulation program based on the evolutionary causal matrices and Markov chain. Knowl. Inf. Syst. 57(3): 685-707 (2018) - [j5]Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran:
Speeding Up Distributed Machine Learning Using Codes. IEEE Trans. Inf. Theory 64(3): 1514-1529 (2018) - [c25]Jisang Yoon, Kangwook Lee, Changho Suh:
On the Joint Recovery of Community Structure and Community Features. Allerton 2018: 686-694 - [c24]Kangwook Lee, Hoon Kim, Changho Suh:
Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings. ICLR (Poster) 2018 - [c23]Kangwook Lee, Kyungmin Lee, Hoon Kim, Changho Suh, Kannan Ramchandran:
SGD on Random Mixtures: Private Machine Learning under Data Breach Threats. ICLR (Workshop) 2018 - [c22]Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon:
Hierarchical Coding for Distributed Computing. ISIT 2018: 1630-1634 - [c21]Tavor Baharav, Kangwook Lee, Orhan Ocal, Kannan Ramchandran:
Straggler-Proofing Massive-Scale Distributed Matrix Multiplication with D-Dimensional Product Codes. ISIT 2018: 1993-1997 - [c20]Kwangjun Ahn, Kangwook Lee, Hyunseung Cha, Changho Suh:
Binary Rating Estimation with Graph Side Information. NeurIPS 2018: 4277-4288 - [i11]Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon:
Hierarchical Coding for Distributed Computing. CoRR abs/1801.04686 (2018) - [i10]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. CoRR abs/1805.08956 (2018) - 2017
- [j4]Kangwook Lee, Nihar B. Shah, Longbo Huang, Kannan Ramchandran:
The MDS Queue: Analysing the Latency Performance of Erasure Codes. IEEE Trans. Inf. Theory 63(5): 2822-2842 (2017) - [j3]Ramtin Pedarsani, Dong Yin, Kangwook Lee, Kannan Ramchandran:
PhaseCode: Fast and Efficient Compressive Phase Retrieval Based on Sparse-Graph Codes. IEEE Trans. Inf. Theory 63(6): 3663-3691 (2017) - [j2]Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
On Scheduling Redundant Requests With Cancellation Overheads. IEEE/ACM Trans. Netw. 25(2): 1279-1290 (2017) - [c19]Geewon Suh, Kangwook Lee, Changho Suh:
Matrix sparsification for coded matrix multiplication. Allerton 2017: 1271-1278 - [c18]Kabir Chandrasekher, Kangwook Lee, Peter Kairouz, Ramtin Pedarsani, Kannan Ramchandran:
Asynchronous and noncoherent neighbor discovery for the IoT using sparse-graph codes. ICC 2017: 1-6 - [c17]Kangwook Lee, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran:
Coded computation for multicore setups. ISIT 2017: 2413-2417 - [c16]Kangwook Lee, Changho Suh, Kannan Ramchandran:
High-dimensional coded matrix multiplication. ISIT 2017: 2418-2422 - [c15]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Information-theoretic limits of subspace clustering. ISIT 2017: 2473-2477 - [i9]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Community Recovery in Hypergraphs. CoRR abs/1709.03670 (2017) - [i8]Hyemin Han, Kangwook Lee, Firat Soylu:
Simulating outcomes of interventions using a multipurpose simulation program based on the Evolutionary Causal Matrices and Markov Chain. CoRR abs/1711.09490 (2017) - 2016
- [b1]Kang Wook Lee:
Speeding up distributed storage and computing systems using codes. University of California, Berkeley, USA, 2016 - [j1]Nihar B. Shah, Kangwook Lee, Kannan Ramchandran:
When Do Redundant Requests Reduce Latency? IEEE Trans. Commun. 64(2): 715-722 (2016) - [c14]Kwangjun Ahn, Kangwook Lee, Changho Suh:
Community recovery in hypergraphs. Allerton 2016: 657-663 - [c13]Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran:
Speeding up distributed machine learning using codes. ISIT 2016: 1143-1147 - [c12]Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
SAFFRON: A fast, efficient, and robust framework for group testing based on sparse-graph codes. ISIT 2016: 2873-2877 - [i7]Dong Yin, Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
Fast and Robust Compressive Phase Retrieval with Sparse-Graph Codes. CoRR abs/1606.00531 (2016) - 2015
- [c11]Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
On scheduling redundant requests with cancellation overheads. Allerton 2015: 99-106 - [c10]Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran:
Sparse covariance estimation based on sparse-graph codes. Allerton 2015: 612-619 - [c9]Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran:
Capacity-approaching PhaseCode for low-complexity compressive phase retrieval. ISIT 2015: 989-993 - [c8]Dong Yin, Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
Fast and robust compressive phase retrieval with sparse-graph codes. ISIT 2015: 2583-2587 - [i6]Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran:
SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes. CoRR abs/1508.04485 (2015) - [i5]Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran:
Speeding Up Distributed Machine Learning Using Codes. CoRR abs/1512.02673 (2015) - 2014
- [c7]Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran:
PhaseCode: Fast and efficient compressive phase retrieval based on sparse-graph codes. Allerton 2014: 842-849 - [c6]Nihar B. Shah, Kangwook Lee, Kannan Ramchandran:
The MDS queue: Analysing the latency performance of erasure codes. ISIT 2014: 861-865 - [i4]Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran:
PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph-Codes. CoRR abs/1408.0034 (2014) - [i3]Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran:
Capacity-Approaching PhaseCode for Low-Complexity Compressive Phase Retrieval. CoRR abs/1412.5694 (2014) - 2013
- [c5]Nihar B. Shah, Kangwook Lee, Kannan Ramchandran:
When do redundant requests reduce latency ? Allerton 2013: 731-738 - [c4]Kangwook Lee, Lisa Yan, Abhay Parekh, Kannan Ramchandran:
A VoD System for Massively Scaled, Heterogeneous Environments: Design and Implementation. MASCOTS 2013: 1-10 - [i2]Nihar B. Shah, Kangwook Lee, Kannan Ramchandran:
When Do Redundant Requests Reduce Latency ? CoRR abs/1311.2851 (2013) - 2012
- [c3]Kangwook Lee, Hao Zhang, Ziyu Shao, Minghua Chen, Abhay Parekh, Kannan Ramchandran:
An optimized distributed video-on-demand streaming system: Theory and design. Allerton Conference 2012: 1347-1354 - [i1]Nihar B. Shah, Kangwook Lee, Kannan Ramchandran:
The MDS Queue. CoRR abs/1211.5405 (2012) - 2011
- [c2]Sameer Pawar, Salim Y. El Rouayheb, Hao Zhang, Kangwook Lee, Kannan Ramchandran:
Codes for a distributed caching based Video-on-Demand system. ACSCC 2011: 1783-1787 - [c1]Bruno Nardelli, Jinsung Lee, Kangwook Lee, Yung Yi, Song Chong, Edward W. Knightly, Mung Chiang:
Experimental evaluation of optimal CSMA. INFOCOM 2011: 1188-1196
Coauthor Index
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