NOMA in Distributed Antenna System for Max-Min Fairness and Max-Sum-Rate. - Dong-Jun Han; Minseok Choi; Jaekyun Moon (CoRR, 2017)

Combined Subband-Subcarrier Spectral Shaping in Multi-Carrier Modulation Under the Excess Frame Length Constraint. - Dong-Jun Han; Jaekyun Moon; Dongjae Kim; Sae-Young Chung; Yong H. Lee (IEEE J. Sel. Areas Commun., 2017)

Combined Window-Filter Waveform Design With Transmitter-Side Channel State Information. - Dong-Jun Han; Jaekyun Moon; Jy-yong Sohn; Sunyoung Jo; Jang Hun Kim (IEEE Trans. Veh. Technol., 2018)

Bi-Directional Cooperative NOMA Without Full CSIT. - Minseok Choi; Dong-Jun Han; Jaekyun Moon (IEEE Trans. Wirel. Commun., 2018)

Probabilistic Caching Policy for Categorized Contents and Consecutive User Demands. - Minseok Choi; Dongjae Kim; Dong-Jun Han; Joongheon Kim; Jaekyun Moon (ICC, 2019)

Scalable Network-Coded PBFT Consensus Algorithm. - Beongjun Choi; Jy-yong Sohn; Dong-Jun Han; Jaekyun Moon (ISIT, 2019)

Coded Distributed Computing over Packet Erasure Channels. - Dong-Jun Han; Jy-yong Sohn; Jaekyun Moon (ISIT, 2019)

Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks. - Jy-yong Sohn; Dong-Jun Han; Beongjun Choi; Jaekyun Moon (NeurIPS, 2020)

Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider's Perspective. - Minseok Choi; Andreas F. Molisch; Dong-Jun Han; Joongheon Kim; Jaekyun Moon (WCNC, 2020)

Communication-Computation Efficient Secure Aggregation for Federated Learning. - Beongjun Choi; Jy-yong Sohn; Dong-Jun Han; Jaekyun Moon (CoRR, 2020)

TiBroco: A Fast and Secure Distributed Learning Framework for Tiered Wireless Edge Networks. - Dong-Jun Han; Jy-yong Sohn; Jaekyun Moon (INFOCOM, 2021)

Sageflow: Robust Federated Learning against Both Stragglers and Adversaries. - Jungwuk Park; Dong-Jun Han; Minseok Choi; Jaekyun Moon (NeurIPS, 2021)

Few-Round Learning for Federated Learning. - Younghyun Park; Dong-Jun Han; Do-Yeon Kim 001; Jun Seo; Jaekyun Moon (NeurIPS, 2021)

FedMes: Speeding Up Federated Learning With Multiple Edge Servers. - Dong-Jun Han; Minseok Choi; Jungwuk Park; Jaekyun Moon (IEEE J. Sel. Areas Commun., 2021)

Probabilistic Caching and Dynamic Delivery Policies for Categorized Contents and Consecutive User Demands. - Minseok Choi; Andreas F. Molisch; Dong-Jun Han; Dongjae Kim; Joongheon Kim; Jaekyun Moon (IEEE Trans. Wirel. Commun., 2021)

Hierarchical Broadcast Coding: Expediting Distributed Learning at the Wireless Edge. - Dong-Jun Han; Jy-yong Sohn; Jaekyun Moon (IEEE Trans. Wirel. Commun., 2021)

Coded Wireless Distributed Computing With Packet Losses and Retransmissions. - Dong-Jun Han; Jy-yong Sohn; Jaekyun Moon (IEEE Trans. Wirel. Commun., 2021)

Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation. - Younghyun Park; Soyeong Kim; Wonjeong Choi; Dong-Jun Han; Jaekyun Moon (CVPR Workshops, 2022)

Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning. - Do-Yeon Kim 001; Dong-Jun Han; Jun Seo; Jaekyun Moon (ICLR, 2023)

Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation. - Younghyun Park; Wonjeong Choi; Soyeong Kim; Dong-Jun Han; Jaekyun Moon (ICLR, 2023)

Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization. - Jungwuk Park; Dong-Jun Han; Soyeong Kim; Jaekyun Moon (ICML, 2023)

SplitGP: Achieving Both Generalization and Personalization in Federated Learning. - Dong-Jun Han; Do-Yeon Kim 001; Minseok Choi; Christopher G. Brinton; Jaekyun Moon (INFOCOM, 2023)

NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks. - Seokil Ham; Jungwuk Park; Dong-Jun Han; Jaekyun Moon (NeurIPS, 2023)

StableFDG: Style and Attention Based Learning for Federated Domain Generalization. - Jungwuk Park; Dong-Jun Han; Jinho Kim; Shiqiang Wang 001; Christopher G. Brinton; Jaekyun Moon (NeurIPS, 2023)

Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration. - Wonjeong Choi; Jungwuk Park; Dong-Jun Han; Younghyun Park; Jaekyun Moon (AAAI, 2024)

Submodel Partitioning in Hierarchical Federated Learning: Algorithm Design and Convergence Analysis. - Wenzhi Fang; Dong-Jun Han; Christopher G. Brinton (ICC, 2024)

Cooperative Federated Learning over Hybrid Terrestrial and Non-Terrestrial Networks. - Dong-Jun Han; Seyyedali Hosseinalipour; David J. Love; Mung Chiang; Christopher G. Brinton (ICC, 2024)

FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication. - Liangqi Yuan; Dong-Jun Han; Vishnu Pandi Chellapandi; Stanislaw H. Zak; Christopher G. Brinton (ICC, 2024)

Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning. - Do-Yeon Kim 001; Dong-Jun Han; Jun Seo; Jaekyun Moon (ICML, 2024)

Hierarchical Federated Learning with Multi-Timescale Gradient Correction. - Wenzhi Fang; Dong-Jun Han; Evan Chen; Shiqiang Wang 001; Christopher G. Brinton (NeurIPS, 2024)

FICDF: A Federated Incremental Learning Framework for IoT Device Fingerprinting. - Shengli Ding; Dong-Jun Han; Christopher G. Brinton; Keerthi Dasala (WiOpt, 2024)

Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation. - Yun-Wei Chu; Dong-Jun Han; Christopher G. Brinton (WWW (Companion Volume), 2024)

Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection. - Liangqi Yuan; Dong-Jun Han; Su Wang 007; Devesh Upadhyay; Christopher G. Brinton (CoRR, 2024)

Rethinking the Starting Point: Enhancing Performance and Fairness of Federated Learning via Collaborative Pre-Training. - Yun-Wei Chu; Dong-Jun Han; Seyyedali Hosseinalipour; Christopher G. Brinton (CoRR, 2024)

Decentralized Sporadic Federated Learning: A Unified Methodology with Generalized Convergence Guarantees. - Shahryar Zehtabi; Dong-Jun Han; Rohit Parasnis; Seyyedali Hosseinalipour; Christopher G. Brinton (CoRR, 2024)

SePPO: Semi-Policy Preference Optimization for Diffusion Alignment. - Daoan Zhang; Guangchen Lan; Dong-Jun Han; Wenlin Yao; Xiaoman Pan; Hongming Zhang 009; Mingxiao Li 004; Pengcheng Chen; Dong Yu 001; Christopher Brinton 001; Jiebo Luo 001 (CoRR, 2024)

Federated Learning with Dynamic Client Arrival and Departure: Convergence and Rapid Adaptation via Initial Model Construction. - Zhan-Lun Chang; Dong-Jun Han; Rohit Parasnis; Seyyedali Hosseinalipour; Christopher G. Brinton (CoRR, 2024)

Using Diffusion Models as Generative Replay in Continual Federated Learning - What will Happen? - Yongsheng Mei; Liangqi Yuan; Dong-Jun Han; Kevin S. Chan; Christopher G. Brinton; Tian Lan 001 (CoRR, 2024)

Cooperative Federated Learning Over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading. - Dong-Jun Han; Seyyedali Hosseinalipour; David J. Love; Mung Chiang; Christopher G. Brinton (IEEE J. Sel. Areas Commun., 2024)

Federated Split Learning With Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks. - Dong-Jun Han; Do-Yeon Kim 001; Minseok Choi; David Nickel; Jaekyun Moon; Mung Chiang; Christopher G. Brinton (IEEE Trans. Mob. Comput., 2024)

Improving Low-Latency Predictions in Multi-Exit Neural Networks via Block-Dependent Losses. - Dong-Jun Han; Jungwuk Park; Seokil Ham; Namjin Lee; Jaekyun Moon (IEEE Trans. Neural Networks Learn. Syst., 2024)

Orchestrating Federated Learning in Space-Air- Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover. - Dong-Jun Han; Wenzhi Fang; Seyyedali Hosseinalipour; Mung Chiang; Christopher G. Brinton (IEEE J. Sel. Areas Commun., 2024)

Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks. - Yun-Wei Chu; Dong-Jun Han; Seyyedali Hosseinalipour; Christopher G. Brinton (AAAI, 2025)

Adaptive Energy Alignment for Accelerating Test-Time Adaptation. - Wonjeong Choi; Do-Yeon Kim 001; Jungwuk Park; Jungmoon Lee; Younghyun Park; Dong-Jun Han; Jaekyun Moon (ICLR, 2025)

Unlocking the Potential of Model Calibration in Federated Learning. - Yun-Wei Chu; Dong-Jun Han; Seyyedali Hosseinalipour; Christopher Brinton 001 (ICLR, 2025)

Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. - Guangchen Lan; Dong-Jun Han; Abolfazl Hashemi; Vaneet Aggarwal; Christopher Brinton 001 (ICLR, 2025)

PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models. - Kyeongkook Seo; Dong-Jun Han; Jaejun Yoo (ICLR, 2025)

Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees. - Shahryar Zehtabi; Dong-Jun Han; Rohit Parasnis; Seyyedali Hosseinalipour; Christopher G. Brinton (ICLR, 2025)

Federated Sketching LoRA: On-Device Collaborative Fine-Tuning of Large Language Models. - Wenzhi Fang; Dong-Jun Han; Liangqi Yuan; Seyyedali Hosseinalipour; Christopher G. Brinton (CoRR, 2025)

Differentially-Private Multi-Tier Federated Learning: A Formal Analysis and Evaluation. - Evan Chen; Frank Po-Chen Lin; Dong-Jun Han; Christopher G. Brinton (CoRR, 2025)

Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings. - Liangqi Yuan; Dong-Jun Han; Shiqiang Wang 001; Christopher G. Brinton (CoRR, 2025)

Decentralized Federated Domain Generalization with Style Sharing: A Formal Modeling and Convergence Analysis. - Shahryar Zehtabi; Dong-Jun Han; Seyyedali Hosseinalipour; Christopher G. Brinton (CoRR, 2025)

MaPPO: Maximum a Posteriori Preference Optimization with Prior Knowledge. - Guangchen Lan; Sipeng Zhang; Tianle Wang 009; Yuwei Zhang; Daoan Zhang; Xinpeng Wei; Xiaoman Pan; Hongming Zhang 009; Dong-Jun Han; Christopher G. Brinton (CoRR, 2025)