Jaekyun Moon
16 papers · 2019–2026 · 4 venues · across top CS/AI venues
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πΊοΈ Taxonomy Completionist (33) π Conference Polyglot Β· Bronze π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Venues
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Research topics
Machine Learning
(14)
Artificial Intelligence
(12)
Application Areas
(10)
Learning Paradigms
(9)
Learning Types Β· Machine Learning
(5)
Optimization & Theory
(4)
Deep Learning
(3)
Core AI Β· Artificial Intelligence
(3)
Computer Vision
(2)
Mathematics & Optimization
(2)
Analysis
(1)
Architectures
(1)
Core AI Β· Computer Vision
(1)
Core Methods
(1)
Learning Types Β· Deep Learning
(1)
Keywords
federated learning
(5)
few-shot learning
(4)
communication efficiency
(3)
model aggregation
(2)
adversarial robustness
(2)
domain shift
(2)
out-of-distribution generalization
(2)
domain generalization
(2)
test-time adaptation
(2)
epistemic uncertainty
(1)
style transfer
(1)
embedding space
(1)
robust optimization
(1)
object detection
(1)
catastrophic forgetting
(1)
feature extraction
(1)
distributed learning
(1)
entropy minimization
(1)
adversarial learning
(1)
data augmentation
(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
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
Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation
ICLR 2023
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
NeurIPS 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
GenLabel: Mixup Relabeling using Generative Models
ICML 2022
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
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
ICML 2020
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
ICML 2019