About & Contact
We are looking for integrated MS/PhD candidates in areas of machine learning (with emphasis on distributed learning, low-data learning and low-complexity learning) and distributed storage. Interested candidates may contact Prof. Jaekyun Moon via email (jmoon@kaist.edu).
Research Areas: distributed/decentralized machine learning, learning on low data, and hardware-friendly learning algorithms, all using various theoretical tools and insights from the fields of communications, signal processing, statistics and information theory.
News
2022.04 | Two papers accepted to CVPR Workshop:
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2022.04 | D.-J. Han received the Best Ph.D. Dissertation Award from KAIST EE |
2021.10 | Y. Park's paper entitled "CAFENet: Class-Agnostic Few-Shot Edge Detection Network" accepted to BMVC 2021 |
2021.09 | Two papers accepted to NeurIPS 2021:
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2021.08 | D.-J. Han's paper entitled "FedMes: Speeding Up Federated Learning with Multiple Edge Servers" accepted for publication in IEEE Journal on Selected Areas in Communications |
2021.07 | Two papers accepted to ICML Workshop:
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2021.06 | D.-J. Han's paper entitled "Coded Wireless Distributed Computing with Packet Losses and Retransmissions" accepted for publication in IEEE Transactions on Wireless Communications |
2020.12 | D.-J. Han's paper entitled "TiBroco: A Fast and Secure Distributed Learning Framework for Tiered Wireless Edge Networks" accepted to IEEE INFOCOM 2021 |
2020.12 | M. Choi's paper entitled "Probabilistic Caching and Dynamic Delivery Policies for Categorized Contents and Consecutive User Demands" accepted for publication in IEEE Transactions on Wireless Communications |
2020.11 | D.-J. Han's paper entitled "Hierarchical Broadcast Coding: Expediting Distributed Learning at the Wireless Edge" accepted for publication in IEEE Transactions on Wireless Communications |
2020.10 | S. Park's paper entitled "Characterization of Inter-Cell Interference in 3D NAND Flash Memory" accepted for publication in IEEE Transactions Circuits and Systems I: Regular Papers |
2020.09 | J. Sohn's paper entitled "Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks" accepted to Neural Information Processing Systems (NeurIPS) 2020 |
2020.07 | J. Sohn's paper entitled "GAN-mixup: Augmenting Across Data Manifolds for Improved Robustness" accepted to ICML Workshop on Uncertainty & Robustness in Deep Learning |
2020.06 | S. W. Yoon and D.-Y. Kim's paper entitled "XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning" accepted to International Conference on Machine Learning (ICML) 2020 |
2020.03 | Dr. Sung Whan Yoon, a Ph.D. alumnus of our group joined UNIST as an Assistant Professor |
2020.03 | Dr. Minseok Choi, a Ph.D. alumnus of our group joined Jeju National University as an Assistant Professor |
2020.03 | So Yeong Kim and Jinho Kim joined our lab. Welcome! |
2019.07 | M. Choi's paper entitled “Dynamic Power Allocation and User Scheduling for Power-Efficient and Delay-Constrained Multiple Access Networks” accepted for publication in IEEE Transactions on Wireless Communications |
2019.06 | B. Choi's paper entitled "Secure Clustered Distributed Storage Against Eavesdropping" accepted for publication in IEEE Transactions on Information Theory |
2019.04 | S. W. Yoon and J. Seo's paper entitled "TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning" accepted to the 36th International Conference on Machine Learning (ICML) 2019 |
2019.04 | Four papers accepted in IEEE International Symposium on Information Theory (ISIT) 2019
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