Jaekyun Moon

16 papers · 2019–2026 · 4 conferences · across top CS/AI conferences

Achievements

+11 more ↓

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (4) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (6)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) 🤝 Dynamic Duo (11) 👑 Triple Crown 🏆 Grand Slam 🔥 Unstoppable (7) 💎 Century Club (15) 📈 Trend Setter ⚡ Prolific Year (6) 🗃️ Keyword Collector (56)

Conferences

NIPS (6) ICML (5) ICLR (3) AAAI (2)

Top co-authors

Dong-Jun Han (12) Jungwuk Park (7) Do-Yeon Kim (5) Younghyun Park (5) Jun Seo (5) Wonjeong Choi (3) Sung Whan Yoon (2) Jy-yong Sohn (2) Soyeong Kim (2) Shiqiang Wang (1)

Keywords

federated learning (4) communication efficiency (3) few-shot learning (3) model aggregation (2) domain generalization (2) out-of-distribution generalization (2) adversarial robustness (2) data augmentation (1) attention mechanism (1) adversarial learning (1) model robustness (1) knowledge distillation (1) distributed optimization (1) distributed learning (1) style transfer (1) adversarial training (1) embedding space (1) incremental learning (1) test-time adaptation (1) feature extraction (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 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 Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning ICLR 2023 NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks NIPS 2023 EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning NIPS 2023 StableFDG: Style and Attention Based Learning for Federated Domain Generalization NIPS 2023 Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization ICML 2023 GenLabel: Mixup Relabeling using Generative Models ICML 2022 Sageflow: Robust Federated Learning against Both Stragglers and Adversaries NIPS 2021 Few-Round Learning for Federated Learning NIPS 2021 XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning ICML 2020 Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks NIPS 2020 TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning ICML 2019