Kangwook Lee - RankMe

159 papers A* 33A 1B 14Journal 92Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models. CoRR Chungpa Lee, Jy-yong Sohn, Kangwook Lee
2026	J	`jnl`	Meta-Harness: End-to-End Optimization of Model Harnesses. CoRR Yoonho Lee, Roshen Nair, Qizheng Zhang, Kangwook Lee, Omar Khattab, Chelsea Finn
2026	—	`conf`	TABED: Test-Time Adaptive Ensemble Drafting for Robust Speculative Decoding in LVLMs. EACL (Findings) Minjae Lee, Wonjun Kang, Byeongkeun Ahn, Christian Classen, Kevin Galim, Seunghyuk Oh, Minghao Yan, Hyung Il Koo, Kangwook Lee
2026	J	`jnl`	TABED: Test-Time Adaptive Ensemble Drafting for Robust Speculative Decoding in LVLMs. CoRR Minjae Lee, Wonjun Kang, Byeongkeun Ahn, Christian Classen, Kevin Galim, Seunghyuk Oh, Minghao Yan, Hyung Il Koo, Kangwook Lee
2026	J	`jnl`	TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents. CoRR Jongwon Jeong, Jungtaek Kim, Kangwook Lee
2026	J	`jnl`	Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback. CoRR Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee
2026	J	`jnl`	Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback. Trans. Mach. Learn. Res. Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee
2025	J	`jnl`	Buffer-based Gradient Projection for Continual Federated Learning. Trans. Mach. Learn. Res. Shenghong Dai, Jy-yong Sohn, Yicong Chen, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee
2025	J	`jnl`	Draft-based Approximate Inference for LLMs. CoRR Kevin Galim, Ethan Ewer, Wonjun Kang, Minjae Lee, Hyung Il Koo, Kangwook Lee
2025	J	`jnl`	Encoder-only Next Token Prediction. Trans. Mach. Learn. Res. Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee
2025	A*	`conf`	Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. ICML 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
2025	A*	`conf`	From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. ICLR Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos
2025	J	`jnl`	How to Correctly Report LLM-as-a-Judge Evaluations. CoRR Chungpa Lee, Thomas Zeng, Jongwon Jeong, Jy-yong Sohn, Kangwook Lee
2025	J	`jnl`	Improving CLIP Counting Accuracy via Parameter-Efficient Fine-Tuning. Trans. Mach. Learn. Res. Ruisu Zhang, Yicong Chen, Kangwook Lee
2025	J	`jnl`	In-Context Learning with Hypothesis-Class Guidance. CoRR Ziqian Lin, Shubham Kumar Bharti, Kangwook Lee
2025	J	`jnl`	Infected Smallville: How Disease Threat Shapes Sociality in LLM Agents. CoRR Soyeon Choi, Kangwook Lee, Oliver Sng, Joshua M. Ackerman
2025	J	`jnl`	LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization. CoRR Erica Zhang, Ryunosuke Goto, Naomi Sagan, Jurik Mutter, Nick Phillips, Ash A. Alizadeh, Kangwook Lee, Jose H. Blanchet, Mert Pilanci, Robert Tibshirani
2025	A*	`conf`	Looped Transformers for Length Generalization. ICLR Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee
2025	J	`jnl`	Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games. CoRR 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
2025	J	`jnl`	ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs. CoRR Wonjun Kang, Kevin Galim, Seunghyuk Oh, Minjae Lee, Yuchen Zeng, Shuibai Zhang, Coleman Hooper, Yuezhou Hu, Hyung Il Koo, Nam Ik Cho, Kangwook Lee
2025	A*	`conf`	Parameter-Efficient Fine-Tuning of State Space Models. ICML Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee
2025	A*	`conf`	Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. ICLR Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho
2025	J	`jnl`	ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning. CoRR 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
2025	A*	`conf`	Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges. ICML Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos
2025	J	`jnl`	Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges. CoRR Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos
2025	J	`jnl`	Task Vectors in In-Context Learning: Emergence, Formation, and Benefit. CoRR Liu Yang, Ziqian Lin, Kangwook Lee, Dimitris Papailiopoulos, Robert D. Nowak
2025	A*	`conf`	VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. ICML 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
2025	J	`jnl`	VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data. CoRR 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
2024	J	`jnl`	Buffer-based Gradient Projection for Continual Federated Learning. CoRR Shenghong Dai, Jy-yong Sohn, Yicong Chen, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee
2024	J	`jnl`	Can MLLMs Perform Text-to-Image In-Context Learning? CoRR Yuchen Zeng, Wonjun Kang, Yicong Chen, Hyung Il Koo, Kangwook Lee
2024	A*	`conf`	Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks. ICML Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos
2024	J	`jnl`	Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks. CoRR Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho, Samet Oymak, Kangwook Lee, Dimitris Papailiopoulos
2024	A*	`conf`	Dual Operating Modes of In-Context Learning. ICML Ziqian Lin, Kangwook Lee
2024	J	`jnl`	Dual Operating Modes of In-Context Learning. CoRR Ziqian Lin, Kangwook Lee
2024	J	`jnl`	ENTP: Encoder-only Next Token Prediction. CoRR Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee
2024	J	`jnl`	Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition. CoRR 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
2024	J	`jnl`	From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. CoRR Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos
2024	J	`jnl`	Hierarchical Deep Reinforcement Learning-Based Propofol Infusion Assistant Framework in Anesthesia. IEEE Trans. Neural Networks Learn. Syst. Won Joon Yun, Myungjae Shin, David Mohaisen, Kangwook Lee, Joongheon Kim
2024	A*	`conf`	Image Clustering Conditioned on Text Criteria. ICLR Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee
2024	A*	`conf`	Looped Transformers are Better at Learning Learning Algorithms. ICLR Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos
2024	J	`jnl`	Looped Transformers for Length Generalization. CoRR Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee
2024	A	`conf`	Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks. UAI Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee
2024	J	`jnl`	Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks. CoRR Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee
2024	J	`jnl`	Mini-Batch Optimization of Contrastive Loss. Trans. Mach. Learn. Res. Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee
2024	J	`jnl`	Multi-Bin Batching for Increasing LLM Inference Throughput. CoRR Ozgur Guldogan, Jackson Kunde, Kangwook Lee, Ramtin Pedarsani
2024	J	`jnl`	Parameter-Efficient Fine-Tuning of State Space Models. CoRR Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee
2024	J	`jnl`	Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding. Trans. Mach. Learn. Res. Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee
2024	J	`jnl`	Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. CoRR Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho
2024	A*	`conf`	Teaching Arithmetic to Small Transformers. ICLR Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos
2024	A*	`conf`	The Expressive Power of Low-Rank Adaptation. ICLR Yuchen Zeng, Kangwook Lee
2024	J	`jnl`	Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression. J. Mach. Learn. Res. Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak
2023	J	`jnl`	DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
2023	A*	`conf`	Equal Improvability: A New Fairness Notion Considering the Long-term Impact. ICLR Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
2023	B	`conf`	Federated Learning with Local Fairness Constraints. ISIT Yuchen Zeng, Hongxu Chen, Kangwook Lee
2023	J	`jnl`	Image Clustering Conditioned on Text Criteria. CoRR Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee
2023	A*	`conf`	Improving Fair Training under Correlation Shifts. ICML Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2023	J	`jnl`	Improving Fair Training under Correlation Shifts. CoRR Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2023	J	`jnl`	Looped Transformers are Better at Learning Learning Algorithms. CoRR Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos
2023	A*	`conf`	Looped Transformers as Programmable Computers. ICML Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos
2023	J	`jnl`	Looped Transformers as Programmable Computers. CoRR Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris S. Papailiopoulos
2023	J	`jnl`	Mini-Batch Optimization of Contrastive Loss. CoRR Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee
2023	—	`conf`	Online Federated Learning based Object Detection across Autonomous Vehicles in a Virtual World. CCNC Shenghong Dai, S. M. Iftekharul Alam, Ravikumar Balakrishnan, Kangwook Lee, Suman Banerjee, Nageen Himayat
2023	A*	`conf`	Optimizing DDPM Sampling with Shortcut Fine-Tuning. ICML Ying Fan, Kangwook Lee
2023	J	`jnl`	Optimizing DDPM Sampling with Shortcut Fine-Tuning. CoRR Ying Fan, Kangwook Lee
2023	J	`jnl`	Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding. CoRR Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris S. Papailiopoulos, Kangwook Lee
2023	—	`conf`	Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. ACL (Findings) Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee
2023	J	`jnl`	Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. CoRR Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee
2023	A*	`conf`	Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
2023	J	`jnl`	Teaching Arithmetic to Small Transformers. CoRR Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos
2023	J	`jnl`	The Expressive Power of Low-Rank Adaptation. CoRR Yuchen Zeng, Kangwook Lee
2023	J	`jnl`	Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization. CoRR Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak
2022	J	`jnl`	A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets. CoRR Liu Yang, Jifan Zhang, Joseph Shenouda, Dimitris S. Papailiopoulos, Kangwook Lee, Robert D. Nowak
2022	J	`jnl`	Addendum and Erratum to "The MDS Queue: Analysing the Latency Performance of Erasure Codes". IEEE Trans. Inf. Theory Kangwook Lee, Nihar B. Shah, Longbo Huang, Kannan Ramchandran
2022	B	`conf`	Breaking Fair Binary Classification with Optimal Flipping Attacks. ISIT Changhun Jo, Jy-yong Sohn, Kangwook Lee
2022	J	`jnl`	Breaking Fair Binary Classification with Optimal Flipping Attacks. CoRR Changhun Jo, Jy-yong Sohn, Kangwook Lee
2022	—	`conf`	Debiasing Pre-Trained Language Models via Efficient Fine-Tuning. LT-EDI Michael Gira, Ruisu Zhang, Kangwook Lee
2022	J	`jnl`	Equal Improvability: A New Fairness Notion Considering the Long-term Impact. CoRR Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
2022	A*	`conf`	GenLabel: Mixup Relabeling using Generative Models. ICML Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee
2022	J	`jnl`	GenLabel: Mixup Relabeling using Generative Models. CoRR Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee
2022	J	`jnl`	Improved Input Reprogramming for GAN Conditioning. CoRR Tuan Dinh, Daewon Seo, Zhixu Du, Liang Shang, Kangwook Lee
2022	J	`jnl`	LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks. CoRR Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee
2022	A*	`conf`	LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks. NeurIPS Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee
2022	J	`jnl`	Outlier-Robust Group Inference via Gradient Space Clustering. CoRR Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
2022	A*	`conf`	Permutation-Based SGD: Is Random Optimal? ICLR Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos
2022	A*	`conf`	Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos
2022	J	`jnl`	Rare Gems: Finding Lottery Tickets at Initialization. CoRR Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Kangwook Lee, Dimitris S. Papailiopoulos
2022	A*	`conf`	Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. NeurIPS Dohyun Kwon, Ying Fan, Kangwook Lee
2022	J	`jnl`	Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. CoRR Dohyun Kwon, Ying Fan, Kangwook Lee
2022	—	`conf`	Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. EMNLP (Findings) Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee
2022	J	`jnl`	Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. CoRR Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee
2021	—	`conf`	Adaptive Gradient Communication via Critical Learning Regime Identification. MLSys Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2021	A*	`conf`	Coded-InvNet for Resilient Prediction Serving Systems. ICML Tuan Dinh, Kangwook Lee
2021	J	`jnl`	Coded-InvNet for Resilient Prediction Serving Systems. CoRR Tuan Dinh, Kangwook Lee
2021	A*	`conf`	Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information. ICML Changhun Jo, Kangwook Lee
2021	A*	`conf`	FairBatch: Batch Selection for Model Fairness. ICLR Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2021	A*	`conf`	Gradient Inversion with Generative Image Prior. NeurIPS Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok
2021	J	`jnl`	Gradient Inversion with Generative Image Prior. CoRR Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok
2021	J	`jnl`	Improving Fairness via Federated Learning. CoRR Yuchen Zeng, Hongxu Chen, Kangwook Lee
2021	J	`jnl`	Permutation-Based SGD: Is Random Optimal? CoRR Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos
2021	J	`jnl`	Predicting vehicle collisions using data collected from video games. Mach. Vis. Appl. Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh
2021	A*	`conf`	Sample Selection for Fair and Robust Training. NeurIPS Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
2021	J	`jnl`	Sample Selection for Fair and Robust Training. CoRR Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2021	J	`jnl`	The Roaming Edge and its Applications. GetMobile Mob. Comput. Commun. Suman Banerjee, Remzi H. Arpaci-Dusseau, Shenghong Dai, Kassem Fawaz, Mohit Gupta, Kangwook Lee, Shivaram Venkataraman
2020	J	`jnl`	Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification. CoRR Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
2020	J	`jnl`	Applying the Deep Learning Method for Simulating Outcomes of Educational Interventions. SN Comput. Sci. Hyemin Han, Kangwook Lee, Firat Soylu
2020	A*	`conf`	Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. NeurIPS Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos
2020	J	`jnl`	Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. CoRR Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos
2020	J	`jnl`	Discrete-valued Preference Estimation with Graph Side Information. CoRR Changhun Jo, Kangwook Lee
2020	A*	`conf`	FR-Train: A Mutual Information-Based Approach to Fair and Robust Training. ICML Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
2020	J	`jnl`	FR-Train: A mutual information-based approach to fair and robust training. CoRR Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2020	J	`jnl`	FairBatch: Batch Selection for Model Fairness. CoRR Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
2020	—	`conf`	Reprogramming GANs via Input Noise Design. ECML/PKDD (2) Kangwook Lee, Changho Suh, Kannan Ramchandran
2019	J	`jnl`	Community Recovery in Hypergraphs. IEEE Trans. Inf. Theory Kwangjun Ahn, Kangwook Lee, Changho Suh
2019	A*	`conf`	Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator. AAAI Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh
2019	J	`jnl`	SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing Based on Sparse-Graph Codes. IEEE Trans. Signal Process. Kangwook Lee, Kabir Chandrasekher, Ramtin Pedarsani, Kannan Ramchandran
2019	B	`conf`	Synthesizing Differentially Private Datasets using Random Mixing. ISIT Kangwook Lee, Hoon Kim, Kyungmin Lee, Changho Suh, Kannan Ramchandran
2018	A*	`conf`	Binary Rating Estimation with Graph Side Information. NeurIPS Kwangjun Ahn, Kangwook Lee, Hyunseung Cha, Changho Suh
2018	B	`conf`	Hierarchical Coding for Distributed Computing. ISIT Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon
2018	J	`jnl`	Hierarchical Coding for Distributed Computing. CoRR Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon
2018	J	`jnl`	Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. CoRR Kwangjun Ahn, Kangwook Lee, Changho Suh
2018	J	`jnl`	Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. IEEE J. Sel. Top. Signal Process. Kwangjun Ahn, Kangwook Lee, Changho Suh
2018	—	`conf`	On the Joint Recovery of Community Structure and Community Features. Allerton Jisang Yoon, Kangwook Lee, Changho Suh
2018	—	`conf`	SGD on Random Mixtures: Private Machine Learning under Data Breach Threats. ICLR (Workshop) Kangwook Lee, Kyungmin Lee, Hoon Kim, Changho Suh, Kannan Ramchandran
2018	—	`conf`	Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings. ICLR (Poster) Kangwook Lee, Hoon Kim, Changho Suh
2018	J	`jnl`	Simulating outcomes of interventions using a multipurpose simulation program based on the evolutionary causal matrices and Markov chain. Knowl. Inf. Syst. Hyemin Han, Kangwook Lee, Firat Soylu
2018	J	`jnl`	Speeding Up Distributed Machine Learning Using Codes. IEEE Trans. Inf. Theory Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
2018	B	`conf`	Straggler-Proofing Massive-Scale Distributed Matrix Multiplication with D-Dimensional Product Codes. ISIT Tavor Baharav, Kangwook Lee, Orhan Ocal, Kannan Ramchandran
2017	—	`conf`	Asynchronous and noncoherent neighbor discovery for the IoT using sparse-graph codes. ICC Kabir Chandrasekher, Kangwook Lee, Peter Kairouz, Ramtin Pedarsani, Kannan Ramchandran
2017	B	`conf`	Coded computation for multicore setups. ISIT Kangwook Lee, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
2017	J	`jnl`	Community Recovery in Hypergraphs. CoRR Kwangjun Ahn, Kangwook Lee, Changho Suh
2017	B	`conf`	High-dimensional coded matrix multiplication. ISIT Kangwook Lee, Changho Suh, Kannan Ramchandran
2017	B	`conf`	Information-theoretic limits of subspace clustering. ISIT Kwangjun Ahn, Kangwook Lee, Changho Suh
2017	—	`conf`	Matrix sparsification for coded matrix multiplication. Allerton Geewon Suh, Kangwook Lee, Changho Suh
2017	J	`jnl`	On Scheduling Redundant Requests With Cancellation Overheads. IEEE/ACM Trans. Netw. Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2017	J	`jnl`	PhaseCode: Fast and Efficient Compressive Phase Retrieval Based on Sparse-Graph Codes. IEEE Trans. Inf. Theory Ramtin Pedarsani, Dong Yin, Kangwook Lee, Kannan Ramchandran
2017	J	`jnl`	Simulating outcomes of interventions using a multipurpose simulation program based on the Evolutionary Causal Matrices and Markov Chain. CoRR Hyemin Han, Kangwook Lee, Firat Soylu
2017	J	`jnl`	The MDS Queue: Analysing the Latency Performance of Erasure Codes. IEEE Trans. Inf. Theory Kangwook Lee, Nihar B. Shah, Longbo Huang, Kannan Ramchandran
2016	—	`conf`	Community recovery in hypergraphs. Allerton Kwangjun Ahn, Kangwook Lee, Changho Suh
2016	J	`jnl`	Fast and Robust Compressive Phase Retrieval with Sparse-Graph Codes. CoRR Dong Yin, Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2016	B	`conf`	SAFFRON: A fast, efficient, and robust framework for group testing based on sparse-graph codes. ISIT Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2016	B	`conf`	Speeding up distributed machine learning using codes. ISIT Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
2016	J	`jnl`	When Do Redundant Requests Reduce Latency? IEEE Trans. Commun. Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
2015	B	`conf`	Capacity-approaching PhaseCode for low-complexity compressive phase retrieval. ISIT Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran
2015	B	`conf`	Fast and robust compressive phase retrieval with sparse-graph codes. ISIT Dong Yin, Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2015	—	`conf`	On scheduling redundant requests with cancellation overheads. Allerton Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2015	J	`jnl`	SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes. CoRR Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
2015	—	`conf`	Sparse covariance estimation based on sparse-graph codes. Allerton Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran
2015	J	`jnl`	Speeding Up Distributed Machine Learning Using Codes. CoRR Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
2014	J	`jnl`	Capacity-Approaching PhaseCode for Low-Complexity Compressive Phase Retrieval. CoRR Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran
2014	J	`jnl`	PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph-Codes. CoRR Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran
2014	—	`conf`	PhaseCode: Fast and efficient compressive phase retrieval based on sparse-graph codes. Allerton Ramtin Pedarsani, Kangwook Lee, Kannan Ramchandran
2014	B	`conf`	The MDS queue: Analysing the latency performance of erasure codes. ISIT Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
2013	B	`conf`	A VoD System for Massively Scaled, Heterogeneous Environments: Design and Implementation. MASCOTS Kangwook Lee, Lisa Yan, Abhay Parekh, Kannan Ramchandran
2013	J	`jnl`	When Do Redundant Requests Reduce Latency ? CoRR Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
2013	—	`conf`	When do redundant requests reduce latency ? Allerton Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
2012	—	`conf`	An optimized distributed video-on-demand streaming system: Theory and design. Allerton Conference Kangwook Lee, Hao Zhang, Ziyu Shao, Minghua Chen, Abhay Parekh, Kannan Ramchandran
2012	J	`jnl`	The MDS Queue CoRR Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
2011	—	`conf`	Codes for a distributed caching based Video-on-Demand system. ACSCC Sameer Pawar, Salim Y. El Rouayheb, Hao Zhang, Kangwook Lee, Kannan Ramchandran
2011	A*	`conf`	Experimental evaluation of optimal CSMA. INFOCOM Bruno Nardelli, Jinsung Lee, Kangwook Lee, Yung Yi, Song Chong, Edward W. Knightly, Mung Chiang