Dong-Jun Han

19 papers · 2020–2026 · 5 conferences · across top CS/AI conferences

Achievements

+9 more ↓

🌍 Conference Polyglot (5) 🏃 Academic Marathon (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐝 Cross-Pollinator (5)

🌈 Renaissance Researcher (6) 🗺️ Taxonomy Completionist (34) 🌉 Interdisciplinary Bridge 👑 Triple Crown 🤝 Dynamic Duo (11) 🏆 Grand Slam ⚡ Prolific Year (5) 🗃️ Keyword Collector (68) 💎 Century Club (18)

Conferences

ICLR (7) NIPS (6) AAAI (3) ICML (2) EMNLP (1)

Top co-authors

Jaekyun Moon (12) Jungwuk Park (7) Christopher Brinton (5) Do-Yeon Kim (4) Younghyun Park (4) Wonjeong Choi (3) Jun Seo (3) Seyyedali Hosseinalipour (3) Shiqiang Wang (2) Soyeong Kim (2)

Keywords

federated learning (5) domain generalization (2) out-of-distribution generalization (2) distributed optimization (2) communication efficiency (2) few-shot learning (2) adversarial robustness (2) non-convex optimization (1) attention mechanism (1) adversarial learning (1) model robustness (1) knowledge distillation (1) distributed learning (1) test-time adaptation (1) early exit (1) style transfer (1) model aggregation (1) adversarial training (1) transfer learning (1) robust optimization (1)

Papers

ProLoG: Hybrid Prompt and LoRA Based Adaptation of Vision-Language Models for OOD Generalization AAAI 2026 Unlocking the Potential of Model Calibration in Federated Learning ICLR 2025 PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models ICLR 2025 Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees ICLR 2025 Adaptive Energy Alignment for Accelerating Test-Time Adaptation ICLR 2025 Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks AAAI 2025 LLMAP: LLM-Assisted Multi-Objective Route Planning with User Preferences EMNLP 2025 Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis ICLR 2025 Hierarchical Federated Learning with Multi-Timescale Gradient Correction NIPS 2024 Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration AAAI 2024 Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning ICML 2024 Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation ICLR 2023 NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks NIPS 2023 StableFDG: Style and Attention Based Learning for Federated Domain Generalization NIPS 2023 Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning ICLR 2023 Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization ICML 2023 Sageflow: Robust Federated Learning against Both Stragglers and Adversaries NIPS 2021 Few-Round Learning for Federated Learning NIPS 2021 Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks NIPS 2020