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Dong-Jun Han

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+7 more ↓ πŸ—ΊοΈ Taxonomy Completionist (41) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (12) ⚑ Prolific Year Β· Productive πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (103)

Venues

ICLR (7) NeurIPS (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)

Research topics

Machine Learning (17) Artificial Intelligence (16) Learning Paradigms Β· Artificial Intelligence (12) Application Areas (10) Optimization & Theory (6) Deep Learning (5) Core AI (5) Learning Types Β· Machine Learning (5) Learning Types Β· Deep Learning (3) Computer Vision (2) Mathematics & Optimization (2) Reinforcement Learning (2) Learning Paradigms Β· Machine Learning (2) Methods (2) Analysis (1)

Keywords

federated learning (8) few-shot learning (3) adversarial robustness (2) domain shift (2) distributed learning (2) convergence analysis (2) distributed optimization (2) test-time adaptation (2) communication efficiency (2) domain generalization (2) out-of-distribution generalization (2) policy gradient (1) robust optimization (1) style transfer (1) entropy minimization (1) transfer learning (1) adversarial learning (1) active learning (1) attention mechanism (1) non-convex optimization (1)

Papers

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