Han, Dong-Jun

20 publications

ICLR 2026 Identifying Robust Neural Pathways: Few-Shot Adversarial Mask Tuning for Vision-Language Models Wonjeong Choi, Sejong Ryu, Jungmoon Lee, Dong-Jun Han, Jaekyun Moon

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

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

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

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

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

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

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

AAAI 2024 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

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

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

ICLRW 2023 Distribution Aware Active Learning via Gaussian Mixtures Younghyun Park, Dong-Jun Han, Jungwuk Park, Wonjeong Choi, Humaira Kousar, Jaekyun Moon

NeurIPS 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, Christopher Brinton, Jaekyun Moon

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

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

CVPRW 2022 Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation Younghyun Park, Soyeong Kim, Wonjeong Choi, Dong-Jun Han, Jaekyun Moon

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

NeurIPS 2021 Sageflow: Robust Federated Learning Against Both Stragglers and Adversaries Jungwuk Park, Dong-Jun Han, Minseok Choi, Jaekyun Moon

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