Preprints

  • [P01] Discrete-valued Preference Estimation with Graph Side Information
    C. Jo, and K. Lee
    Preprint
    Arxiv

Journal Papers

  • [J01] SAFFRON: Sparse-Graph Code Framework for Group Testing
    K. Lee, K. Chandrasekher, R. Pedarsani, and K. Ramchandran
    IEEE Transactions on Signal Processing 2019

  • [J02] Community Recovery in Hypergraphs
    K. Ahn*, K. Lee*, and C. Suh
    IEEE Transactions on Information Theory 2019

  • [J03] Hypergraph Spectral Clustering in the Weighted Stochastic Block Model
    K. Ahn, K. Lee, and C. Suh
    IEEE Journal of Selected Topics in Signal Processing, October 2018

  • [J04] Speeding Up Distributed Machine Learning Using Codes
    K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran
    IEEE Transactions on Information Theory, January 2018
    The Joint Communications Society/Information Theory Society Paper Award, 2020

  • [J05] PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph-Codes
    R. Pedarsani, D. Yin, K. Lee, and K. Ramchandran
    IEEE Transactions on Information Theory, June 2017

  • [J06] The MDS Queue: Analysing the Latency Performance of Erasure Codes
    K. Lee, N. Shah, L. Huang, and K. Ramchandran
    IEEE Transactions on Information Theory, May 2017

  • [J07] On Scheduling Redundant Requests With Cancellation Overheads
    K. Lee, R. Pedarsani, and K. Ramchandran
    IEEE/ACM Transactions on Networking, April 2017

  • [J08] When Do Redundant Requests Reduce Latency?
    N. Shah, K. Lee, and K. Ramchandran
    IEEE Transactions on Communications, February 2016

Peer-reviewed Conference/Workshop Proceedings

  • [C01] Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
    H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J. Sohn, K. Lee, and D. Papailiopoulos
    NeurIPS 2020 2020

  • [C02] GAN-mixup: Augmenting Across Data Manifolds for Improved Robustness
    J. Sohn, K. Lee, J. Moon, and D. Papailiopoulos
    ICML Workshop on Uncertainty & Robustness in Deep Learning 2020

  • [C03] Reprogramming GANs via Input Noise Design
    K. Lee, C. Suh, and K. Ramchandran
    ECML PKDD 2020

  • [C04] FR-Train: A mutual information-based approach to fair and robust training
    Y. Roh, K. Lee, S. Whang, and C. Suh
    ICML 2020

  • [C05] Improving Model Robustness via Automatically Incorporating Self-supervision Tasks
    D. Kim, K. Lee, and C. Suh
    NeurIPS Workshop on Meta-Learning (MetaLearn 2019) 2019

  • [C06] Synthesizing Differentially Private Datasets using Random Mixing
    K. Lee, H. Kim, K. Lee, C. Suh, and K. Ramchandran
    IEEE ISIT 2019

  • [C07] Crash to Not Crash: Learn to Identify Dangerous Vehicles using a Simulator
    H. Kim*, K. Lee*, G. Hwang, and C. Suh
    AAAI 2019 (oral presentation) Project website

  • [C08] Binary Rating Estimation with Graph Side Information
    K. Ahn, K. Lee, H. Cha, and C. Suh
    NeurIPS 2018

  • [C09] On the Joint Recovery of Community Structure and Community Features
    J. Yoon, K. Lee, and C. Suh
    Allerton Conference on Communication, Control and Computing 2018

  • [C10] Hierarchical Coding for Distributed Computing
    H. Park, K. Lee, J. Sohn, C. Suh, and J. Moon
    IEEE ISIT 2018

  • [C11] Straggler-proofing massive-scale distributed matrix multiplication with d-dimensional product codes
    T. Baharav, K. Lee, O. Ocal, and K. Ramchandran
    IEEE ISIT 2018

  • [C12] Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings
    K. Lee*, H. Kim*, and C. Suh
    ICLR 2018

  • [C13] SGD on Random Mixtures: Private Machine Learning under Data-breach Threats
    K. Lee, K. Lee, H. Kim, C. Suh, and K. Ramchandran
    ICLR Workshop, SysML 2018

  • [C14] UberShuffle: Communication-efficient Data Shuffling for SGD via Coding Theory
    J. Chung, K. Lee, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran
    SysML 2018, NIPS Workshop on Machine Learning Systems 2017

  • [C15] Matrix Sparsification for Coded Matrix Multiplication
    G. Suh, K. Lee, and C. Suh
    Allerton Conference on Communication, Control and Computing 2017

  • [C16] Crash to not crash: Playing video games to predict vehicle collisions
    K. Lee, H. Kim, and C. Suh
    ICML Workshop on Machine Learning for Autonomous Vehicles 2017

  • [C17] Large-scale and Interpretable Collaborative Filtering for Educational Data
    K. Lee, J. Chung, and C. Suh
    KDD Workshop on Advancing Education with Data 2017

  • [C18] High-Dimensional Coded Matrix Multiplication
    K. Lee, C. Suh, and K. Ramchandran
    IEEE ISIT 2017

  • [C19] Coded Computation for Multicore Setups
    K. Lee, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran
    IEEE ISIT 2017

  • [C20] Information-theoretic Limits of Subspace Clustering
    K. Ahn, K. Lee, and C. Suh
    IEEE ISIT 2017

  • [C21] Asynchronous and Noncoherent Neighbor Discovery for the IoT Using Sparse-Graph Codes
    K. Chandrasekher, K. Lee, P. Kairouz, R. Pedarsani, and K. Ramchandran
    IEEE ICC 2017

  • [C22] Machine Learning Approaches for Learning Analytics: Collaborative Filtering or Regression With Experts?
    K. Lee, J. Chung, Y. Cha, and C. Suh
    NIPS Workshop on Machine Learning for Education 2016

  • [C23] Community Recovery in Hypergraphs
    K. Ahn, K. Lee, and C. Suh
    Allerton Conference on Communication, Control and Computing 2016

  • [C24] Speeding Up Distributed Machine Learning Using Codes
    K. Lee, M. Lam, R. Pedarsani, and K. Ramchandran
    NIPS Workshop on Machine Learning Systems 2015, IEEE ISIT 2016

  • [C25] SAFFRON: Sparse-Graph Code Framework for Group Testing
    K. Lee, R. Pedarsani, and K. Ramchandran
    IEEE ISIT 2016

  • [C26] On Scheduling Redundant Requests with Cancellation Overheads
    K. Lee, R. Pedarsani, and K. Ramchandran
    Allerton Conference on Communication, Control and Computing 2015

  • [C27] Sparse Covariance Estimation Based on Sparse-Graph Codes
    R. Pedarsani, K. Lee, and K. Ramchandran
    Allerton Conference on Communication, Control and Computing 2015

  • [C28] Fast and Robust Compressive Phase Retrieval with Sparse- Graph Codes
    D. Yin, K. Lee, and K. Ramchandran
    IEEE ISIT 2015

  • [C29] Capacity-Approaching PhaseCode for Low-Complexity Compressive Phase Retrieval
    R. Pedarsani, K. Lee, and K. Ramchandran
    IEEE ISIT 2015

  • [C30] PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph-Codes
    R. Pedarsani, K. Lee, and K. Ramchandran
    Allerton Conference on Communication, Control and Computing 2014

  • [C31] The MDS Queue: Analysing the Latency Performance of Codes
    N. Shah, K. Lee, and K. Ramchandran
    IEEE ISIT 2014

  • [C32] When Do Redundant Requests Reduce Latency?
    N. Shah, K. Lee, and K. Ramchandran
    Allerton Conference on Communication, Control and Computing 2013

  • [C33] A VoD System for Massively Scaled, Heterogeneous Environments: Design and Implementation
    K. Lee, L. Yan, A. Parekh, and K. Ramchandran
    IEEE MASCOTS 2013 (Best Paper Award finalist)

  • [C34] An Optimized Distributed Video-on-Demand Streaming System: Theory and Design
    K. Lee, H. Zhang, Z. Shao, M. Chen, A. Parekh, and K. Ramchandran
    Allerton Conference on Communication, Control and Computing 2012

  • [C35] Codes for a Distributed Caching based Video-On-Demand System
    S. Pawar, S. Rouayheb, H. Zhang, K. Lee, and K. Ramchandran
    Asilomar Conference on Signals, Systems, and Computers 2011

  • [C36] Experiment evaluation of optimal CSMA
    B. Nardelli, J. Lee, K. Lee, Y. Yi, S. Chong, E. Knightly, and M. Chiang
    IEEE INFOCOM 2011