Kangwook Lee

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 106

Top Venues

Publications

Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos
Teaching Arithmetic to Small Transformers. ICLR (2024)
Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee
Image Clustering Conditioned on Text Criteria. ICLR (2024)
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)
Yuchen Zeng, Kangwook Lee
The Expressive Power of Low-Rank Adaptation. ICLR (2024)
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) (2024)
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 (2024)
Yuchen Zeng, Wonjun Kang, Yicong Chen, Hyung Il Koo, Kangwook Lee
Can MLLMs Perform Text-to-Image In-Context Learning? CoRR (2024)
Ziqian Lin, Kangwook Lee
Dual Operating Modes of In-Context Learning. CoRR (2024)
Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos
Looped Transformers are Better at Learning Learning Algorithms. ICLR (2024)
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)
Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris S. Papailiopoulos, Kangwook Lee
Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding. CoRR (2023)
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 (2023)
Ying Fan, Kangwook Lee
Optimizing DDPM Sampling with Shortcut Fine-Tuning. CoRR (2023)
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)
Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee
Image Clustering Conditioned on Text Criteria. CoRR (2023)
Yuchen Zeng, Hongxu Chen, Kangwook Lee
Federated Learning with Local Fairness Constraints. ISIT (2023)
Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization. CoRR (2023)
Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris S. Papailiopoulos
Looped Transformers as Programmable Computers. CoRR (2023)
Ying Fan, Kangwook Lee
Optimizing DDPM Sampling with Shortcut Fine-Tuning. ICML (2023)
Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. ACL (Findings) (2023)
Yuchen Zeng, Kangwook Lee
The Expressive Power of Low-Rank Adaptation. CoRR (2023)
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 (2023)
Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos
Looped Transformers are Better at Learning Learning Algorithms. CoRR (2023)
Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
Equal Improvability: A New Fairness Notion Considering the Long-term Impact. ICLR (2023)
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)
Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos
Teaching Arithmetic to Small Transformers. CoRR (2023)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
Improving Fair Training under Correlation Shifts. CoRR (2023)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
Improving Fair Training under Correlation Shifts. ICML (2023)
Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos
Looped Transformers as Programmable Computers. ICML (2023)
Changhun Jo, Jy-yong Sohn, Kangwook Lee
Breaking Fair Binary Classification with Optimal Flipping Attacks. ISIT (2022)
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 (2022)
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) (2022)
Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
Outlier-Robust Group Inference via Gradient Space Clustering. CoRR (2022)
Dohyun Kwon, Ying Fan, Kangwook Lee
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. CoRR (2022)
Tuan Dinh, Daewon Seo, Zhixu Du, Liang Shang, Kangwook Lee
Improved Input Reprogramming for GAN Conditioning. CoRR (2022)
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)
Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos
Permutation-Based SGD: Is Random Optimal? ICLR (2022)
Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
Equal Improvability: A New Fairness Notion Considering the Long-term Impact. CoRR (2022)
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)
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 (2022)
Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee
GenLabel: Mixup Relabeling using Generative Models. CoRR (2022)
Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon, Dimitris S. Papailiopoulos, Kangwook Lee
GenLabel: Mixup Relabeling using Generative Models. ICML (2022)
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 (2022)
Changhun Jo, Jy-yong Sohn, Kangwook Lee
Breaking Fair Binary Classification with Optimal Flipping Attacks. CoRR (2022)
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 (2022)
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)
Michael Gira, Ruisu Zhang, Kangwook Lee
Debiasing Pre-Trained Language Models via Efficient Fine-Tuning. LT-EDI (2022)
Dohyun Kwon, Ying Fan, Kangwook Lee
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. NeurIPS (2022)
Yuchen Zeng, Hongxu Chen, Kangwook Lee
Improving Fairness via Federated Learning. CoRR (2021)
Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
Adaptive Gradient Communication via Critical Learning Regime Identification. MLSys (2021)
Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok
Gradient Inversion with Generative Image Prior. CoRR (2021)
Tuan Dinh, Kangwook Lee
Coded-InvNet for Resilient Prediction Serving Systems. ICML (2021)
Tuan Dinh, Kangwook Lee
Coded-InvNet for Resilient Prediction Serving Systems. CoRR (2021)
Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos
Permutation-Based SGD: Is Random Optimal? CoRR (2021)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
FairBatch: Batch Selection for Model Fairness. ICLR (2021)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
Sample Selection for Fair and Robust Training. CoRR (2021)
Changhun Jo, Kangwook Lee
Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information. ICML (2021)
Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok
Gradient Inversion with Generative Image Prior. NeurIPS (2021)
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) (2021)
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Sample Selection for Fair and Robust Training. NeurIPS (2021)
Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh
Predicting vehicle collisions using data collected from video games. Mach. Vis. Appl. 32 (4) (2021)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
FairBatch: Batch Selection for Model Fairness. CoRR (2020)
Changhun Jo, Kangwook Lee
Discrete-valued Preference Estimation with Graph Side Information. CoRR (2020)
Hyemin Han, Kangwook Lee, Firat Soylu
Applying the Deep Learning Method for Simulating Outcomes of Educational Interventions. SN Comput. Sci. 1 (2) (2020)
Yuji Roh, Kangwook Lee, Steven Euijong Whang, Changho Suh
FR-Train: A mutual information-based approach to fair and robust training. CoRR (2020)
Kangwook Lee, Changho Suh, Kannan Ramchandran
Reprogramming GANs via Input Noise Design. ECML/PKDD (2) (2020)
Saurabh Agarwal, Hongyi Wang, Kangwook Lee, Shivaram Venkataraman, Dimitris S. Papailiopoulos
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification. CoRR (2020)
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)
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training. ICML (2020)
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 (2020)
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) (2019)
Hoon Kim, Kangwook Lee, Gyeongjo Hwang, Changho Suh
Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator. AAAI (2019)
Kangwook Lee, Hoon Kim, Kyungmin Lee, Changho Suh, Kannan Ramchandran
Synthesizing Differentially Private Datasets using Random Mixing. ISIT (2019)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Community Recovery in Hypergraphs. IEEE Trans. Inf. Theory 65 (10) (2019)
Kangwook Lee, Hoon Kim, Changho Suh
Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings. ICLR (Poster) (2018)
Tavor Baharav, Kangwook Lee, Orhan Ocal, Kannan Ramchandran
Straggler-Proofing Massive-Scale Distributed Matrix Multiplication with D-Dimensional Product Codes. ISIT (2018)
Kangwook Lee, Kyungmin Lee, Hoon Kim, Changho Suh, Kannan Ramchandran
SGD on Random Mixtures: Private Machine Learning under Data Breach Threats. ICLR (Workshop) (2018)
Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon
Hierarchical Coding for Distributed Computing. ISIT (2018)
Hyegyeong Park, Kangwook Lee, Jy-yong Sohn, Changho Suh, Jaekyun Moon
Hierarchical Coding for Distributed Computing. CoRR (2018)
Jisang Yoon, Kangwook Lee, Changho Suh
On the Joint Recovery of Community Structure and Community Features. Allerton (2018)
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) (2018)
Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
Speeding Up Distributed Machine Learning Using Codes. IEEE Trans. Inf. Theory 64 (3) (2018)
Kwangjun Ahn, Kangwook Lee, Hyunseung Cha, Changho Suh
Binary Rating Estimation with Graph Side Information. NeurIPS (2018)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. CoRR (2018)
Geewon Suh, Kangwook Lee, Changho Suh
Matrix sparsification for coded matrix multiplication. Allerton (2017)
Kabir Chandrasekher, Kangwook Lee, Peter Kairouz, Ramtin Pedarsani, Kannan Ramchandran
Asynchronous and noncoherent neighbor discovery for the IoT using sparse-graph codes. ICC (2017)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Information-theoretic limits of subspace clustering. ISIT (2017)
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) (2017)
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 (2017)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Community Recovery in Hypergraphs. CoRR (2017)
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) (2017)
Kangwook Lee, Changho Suh, Kannan Ramchandran
High-dimensional coded matrix multiplication. ISIT (2017)
Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
On Scheduling Redundant Requests With Cancellation Overheads. IEEE/ACM Trans. Netw. 25 (2) (2017)
Kangwook Lee, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
Coded computation for multicore setups. ISIT (2017)
Nihar B. Shah, Kangwook Lee, Kannan Ramchandran
When Do Redundant Requests Reduce Latency? IEEE Trans. Commun. 64 (2) (2016)
Kangwook Lee, Maximilian Lam, Ramtin Pedarsani, Dimitris S. Papailiopoulos, Kannan Ramchandran
Speeding up distributed machine learning using codes. ISIT (2016)
Kwangjun Ahn, Kangwook Lee, Changho Suh
Community recovery in hypergraphs. Allerton (2016)
Dong Yin, Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
Fast and Robust Compressive Phase Retrieval with Sparse-Graph Codes. CoRR (2016)
Kangwook Lee, Ramtin Pedarsani, Kannan Ramchandran
SAFFRON: A fast, efficient, and robust framework for group testing based on sparse-graph codes. ISIT (2016)

Kangwook Lee.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Kangwook Lee