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Kangwook 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
- Kangwook Lee
- 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
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2020 – today
- 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
Hierarchical Deep Reinforcement Learning-Based Propofol Infusion Assistant Framework in Anesthesia. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2510-2521 (2024) - [c58]Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee:
Image Clustering Conditioned on Text Criteria. ICLR 2024 - [c57]Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos:
Teaching Arithmetic to Small Transformers. ICLR 2024 - [c56]Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos:
Looped Transformers are Better at Learning Learning Algorithms. ICLR 2024 - [c55]Yuchen Zeng, Kangwook Lee:
The Expressive Power of Low-Rank Adaptation. ICLR 2024 - [c54]Ziqian Lin, Kangwook Lee:
Dual Operating Modes of In-Context Learning. ICML 2024 - [c53]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 - [i53]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) - [i52]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) - [i51]Ziqian Lin, Kangwook Lee:
Dual Operating Modes of In-Context Learning. CoRR abs/2402.18819 (2024) - [i50]Zheyang Xiong, Vasilis Papageorgiou
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. CoRR abs/2406.19292 (2024) - [i49]Jy-yong Sohn, Dohyun Kwon, Seoyeon An, Kangwook Lee:
Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks. CoRR abs/2408.00359 (2024) - [i48]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) - [i47]Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee:
Looped Transformers for Length Generalization. CoRR abs/2409.15647 (2024) - [i46]Ethan Ewer, Daewon Chae, Thomas Zeng, Jinkyu Kim, Kangwook Lee:
ENTP: Encoder-only Next Token Prediction. CoRR abs/2410.01600 (2024) - [i45]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) - [i44]Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee:
Parameter-Efficient Fine-Tuning of State Space Models. CoRR abs/2410.09016 (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
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
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
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
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
Community Recovery in Hypergraphs. IEEE Trans. Inf. Theory 65(10): 6561-6579 (2019) - [j8]Kangwook Lee
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
Synthesizing Differentially Private Datasets using Random Mixing. ISIT 2019: 542-546 - 2018
- [j7]Kwangjun Ahn
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model. IEEE J. Sel. Top. Signal Process. 12(5): 959-974 (2018) - [j6]Hyemin Han
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
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
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
The MDS Queue: Analysing the Latency Performance of Erasure Codes. IEEE Trans. Inf. Theory 63(5): 2822-2842 (2017) - [j3]Ramtin Pedarsani
PhaseCode: Fast and Efficient Compressive Phase Retrieval Based on Sparse-Graph Codes. IEEE Trans. Inf. Theory 63(6): 3663-3691 (2017) - [j2]Kangwook Lee
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
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
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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last updated on 2024-12-01 00:16 CET by the dblp team
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