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ORCIDDong-Jun Han
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2020 – today
- 2024
[j9]Dong-Jun Han
, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning Over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading. IEEE J. Sel. Areas Commun. 42(5): 1080-1096 (2024)- [j8]Dong-Jun Han, Do-Yeon Kim, Minseok Choi, David Nickel, Jaekyun Moon, Mung Chiang, Christopher G. Brinton:
Federated Split Learning With Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks. IEEE Trans. Mob. Comput. 23(6): 7048-7065 (2024) - [c21]Wonjeong Choi, Jungwuk Park, Dong-Jun Han, Younghyun Park, Jaekyun Moon:
Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration. AAAI 2024: 11588-11596 - [c20]Wenzhi Fang, Dong-Jun Han, Christopher G. Brinton:
Submodel Partitioning in Hierarchical Federated Learning: Algorithm Design and Convergence Analysis. ICC 2024: 268-273 - [c19]Liangqi Yuan, Dong-Jun Han, Vishnu Pandi Chellapandi, Stanislaw H. Zak, Christopher G. Brinton:
FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication. ICC 2024: 287-292 - [c18]Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning over Hybrid Terrestrial and Non-Terrestrial Networks. ICC 2024: 2992-2997 - [c17]Do-Yeon Kim, Dong-Jun Han, Jun Seo, Jaekyun Moon:
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning. ICML 2024 - [c16]Yun-Wei Chu, Dong-Jun Han, Christopher G. Brinton:
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation. WWW (Companion Volume) 2024: 1548-1557 - [i22]Yun-Wei Chu, Dong-Jun Han, Christopher G. Brinton:
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation. CoRR abs/2401.07456 (2024) - [i21]Liangqi Yuan, Dong-Jun Han, Su Wang, Devesh Upadhyay, Christopher G. Brinton:
Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection. CoRR abs/2401.16685 (2024) - [i20]Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher G. Brinton:
Rethinking the Starting Point: Enhancing Performance and Fairness of Federated Learning via Collaborative Pre-Training. CoRR abs/2402.02225 (2024) - [i19]Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis, Seyyedali Hosseinalipour, Christopher G. Brinton:
Decentralized Sporadic Federated Learning: A Unified Methodology with Generalized Convergence Guarantees. CoRR abs/2402.03448 (2024) - [i18]Wonjeong Choi, Jungwuk Park, Dong-Jun Han, Younghyun Park, Jaekyun Moon:
Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration. CoRR abs/2402.15019 (2024) - [i17]Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher G. Brinton:
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. CoRR abs/2404.08003 (2024) - [i16]Dong-Jun Han, Wenzhi Fang, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Orchestrating Federated Learning in Space-Air-Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover. CoRR abs/2408.09522 (2024) - [i15]Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher Brinton:
Unlocking the Potential of Model Calibration in Federated Learning. CoRR abs/2409.04901 (2024) - [i14]Wenzhi Fang, Dong-Jun Han, Evan Chen, Shiqiang Wang, Christopher G. Brinton:
Hierarchical Federated Learning with Multi-Timescale Gradient Correction. CoRR abs/2409.18448 (2024) - 2023
- [c15]Do-Yeon Kim, Dong-Jun Han, Jun Seo, Jaekyun Moon:
Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning. ICLR 2023 - [c14]Younghyun Park, Wonjeong Choi, Soyeong Kim, Dong-Jun Han, Jaekyun Moon:
Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation. ICLR 2023 - [c13]Jungwuk Park, Dong-Jun Han, Soyeong Kim, Jaekyun Moon:
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization. ICML 2023: 27114-27131 - [c12]Dong-Jun Han, Do-Yeon Kim, Minseok Choi, Christopher G. Brinton, Jaekyun Moon:
SplitGP: Achieving Both Generalization and Personalization in Federated Learning. INFOCOM 2023: 1-10 - [c11]Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon:
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks. NeurIPS 2023 - [c10]Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon:
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. NeurIPS 2023 - [i13]Jungwuk Park, Dong-Jun Han, Soyeong Kim, Jaekyun Moon:
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization. CoRR abs/2306.04911 (2023) - [i12]Liangqi Yuan, Dong-Jun Han, Vishnu Pandi Chellapandi, Stanislaw H. Zak, Christopher G. Brinton:
FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication. CoRR abs/2310.07048 (2023) - [i11]Wenzhi Fang, Dong-Jun Han, Christopher G. Brinton:
Submodel Partitioning in Hierarchical Federated Learning: Algorithm Design and Convergence Analysis. CoRR abs/2310.17890 (2023) - [i10]Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon:
StableFDG: Style and Attention Based Learning for Federated Domain Generalization. CoRR abs/2311.00227 (2023) - [i9]Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon:
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks. CoRR abs/2311.00428 (2023) - [i8]Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading. CoRR abs/2312.15361 (2023) - 2022
- [c9]Younghyun Park, Soyeong Kim, Wonjeong Choi, Dong-Jun Han, Jaekyun Moon:
Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation. CVPR Workshops 2022: 2711-2715 - [i7]Dong-Jun Han, Do-Yeon Kim, Minseok Choi, Christopher G. Brinton, Jaekyun Moon:
SplitGP: Achieving Both Generalization and Personalization in Federated Learning. CoRR abs/2212.08343 (2022) - 2021
- [j7]Dong-Jun Han, Minseok Choi, Jungwuk Park, Jaekyun Moon:
FedMes: Speeding Up Federated Learning With Multiple Edge Servers. IEEE J. Sel. Areas Commun. 39(12): 3870-3885 (2021) - [j6]Dong-Jun Han, Jy-yong Sohn, Jaekyun Moon:
Hierarchical Broadcast Coding: Expediting Distributed Learning at the Wireless Edge. IEEE Trans. Wirel. Commun. 20(4): 2266-2281 (2021) - [j5]Minseok Choi, Andreas F. Molisch, Dong-Jun Han, Dongjae Kim, Joongheon Kim, Jaekyun Moon:
Probabilistic Caching and Dynamic Delivery Policies for Categorized Contents and Consecutive User Demands. IEEE Trans. Wirel. Commun. 20(4): 2685-2699 (2021) - [j4]Dong-Jun Han, Jy-yong Sohn, Jaekyun Moon:
Coded Wireless Distributed Computing With Packet Losses and Retransmissions. IEEE Trans. Wirel. Commun. 20(12): 8204-8217 (2021) - [c8]Dong-Jun Han, Jy-yong Sohn, Jaekyun Moon:
TiBroco: A Fast and Secure Distributed Learning Framework for Tiered Wireless Edge Networks. INFOCOM 2021: 1-10 - [c7]Jungwuk Park, Dong-Jun Han, Minseok Choi, Jaekyun Moon:
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries. NeurIPS 2021: 840-851 - [c6]Younghyun Park, Dong-Jun Han, Do-Yeon Kim, Jun Seo, Jaekyun Moon:
Few-Round Learning for Federated Learning. NeurIPS 2021: 28612-28622 - 2020
- [c5]Jy-yong Sohn, Dong-Jun Han, Beongjun Choi, Jaekyun Moon:
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks. NeurIPS 2020 - [c4]Minseok Choi, Andreas F. Molisch, Dong-Jun Han, Joongheon Kim, Jaekyun Moon:
Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider's Perspective. WCNC 2020: 1-6 - [i6]Minseok Choi, Andreas F. Molisch, Dong-Jun Han, Joongheon Kim, Jaekyun Moon:
Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider's Perspective. CoRR abs/2002.06254 (2020) - [i5]Beongjun Choi, Jy-yong Sohn, Dong-Jun Han, Jaekyun Moon:
Communication-Computation Efficient Secure Aggregation for Federated Learning. CoRR abs/2012.05433 (2020)
2010 – 2019
- 2019
- [c3]Minseok Choi, Dongjae Kim, Dong-Jun Han, Joongheon Kim, Jaekyun Moon:
Probabilistic Caching Policy for Categorized Contents and Consecutive User Demands. ICC 2019: 1-6 - [c2]Dong-Jun Han, Jy-yong Sohn, Jaekyun Moon:
Coded Distributed Computing over Packet Erasure Channels. ISIT 2019: 717-721 - [c1]Beongjun Choi, Jy-yong Sohn, Dong-Jun Han, Jaekyun Moon:
Scalable Network-Coded PBFT Consensus Algorithm. ISIT 2019: 857-861 - [i4]Dong-Jun Han, Jy-yong Sohn, Jaekyun Moon:
Coded Distributed Computing over Packet Erasure Channels. CoRR abs/1901.03610 (2019) - [i3]Jy-yong Sohn, Dong-Jun Han, Beongjun Choi, Jaekyun Moon:
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks. CoRR abs/1910.06093 (2019) - 2018
- [j3]Dong-Jun Han, Jaekyun Moon, Jy-yong Sohn, Sunyoung Jo, Jang Hun Kim:
Combined Window-Filter Waveform Design With Transmitter-Side Channel State Information. IEEE Trans. Veh. Technol. 67(9): 8959-8963 (2018) - [j2]Minseok Choi, Dong-Jun Han, Jaekyun Moon:
Bi-Directional Cooperative NOMA Without Full CSIT. IEEE Trans. Wirel. Commun. 17(11): 7515-7527 (2018) - [i2]Minseok Choi, Dong-Jun Han, Jaekyun Moon:
Bi-Directional Cooperative NOMA without Full CSIT. CoRR abs/1807.07707 (2018) - 2017
- [j1]Dong-Jun Han, Jaekyun Moon, Dongjae Kim, Sae-Young Chung, Yong H. Lee:
Combined Subband-Subcarrier Spectral Shaping in Multi-Carrier Modulation Under the Excess Frame Length Constraint. IEEE J. Sel. Areas Commun. 35(6): 1339-1352 (2017) - [i1]Dong-Jun Han, Minseok Choi, Jaekyun Moon:
NOMA in Distributed Antenna System for Max-Min Fairness and Max-Sum-Rate. CoRR abs/1706.05314 (2017)
Coauthor Index
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