Jae-Gil Lee
20 papers · 2019–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (6) π Cross-Pollinator (11)
π
Cross-Pollinator
(11)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(49)
π€
Dynamic Duo
(14)
π
Grand Slam
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(92)
π
Trend Setter
π
Century Club
(19)
π₯
Unstoppable
(5)
Conferences
AAAI (7)
NIPS (4)
ICLR (3)
ICML (3)
ACL (1)
CVPR (1)
EMNLP (1)
Top co-authors
Keywords
label noise
(3)
deep neural network
(2)
recommender system
(2)
class imbalance
(2)
data augmentation
(2)
active learning
(2)
time series
(2)
zero-shot learning
(1)
catastrophic forgetting
(1)
model compression
(1)
anomaly detection
(1)
feature extraction
(1)
change detection
(1)
noisy label learning
(1)
online learning
(1)
efficient training
(1)
representation learning
(1)
multimodal learning
(1)
multi-label classification
(1)
semi-supervised learning
(1)
Papers
QuDAR: Query-Wise Dual-Perspective Adaptive Retrieval
ACL 2026
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
AAAI 2025
MONAQ: Multi-Objective Neural Architecture Querying for Time-Series Analysis on Resource-Constrained Devices
EMNLP 2025
RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models
ICLR 2025
Active Learning for Continual Learning: Keeping the Past Alive in the Present
ICLR 2025
Exploiting Representation Curvature for Boundary Detection in Time Series
NIPS 2024
Active Prompt Learning in Vision Language Models
CVPR 2024
Adaptive Shortcut Debiasing for Online Continual Learning
AAAI 2024
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
ICML 2024
Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise
AAAI 2024
Context Consistency Regularization for Label Sparsity in Time Series
ICML 2023
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy
NIPS 2023
AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series
AAAI 2023
Meta-Learning for Online Update of Recommender Systems
AAAI 2022
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies
AAAI 2022
Coherence-based Label Propagation over Time Series for Accelerated Active Learning
ICLR 2022
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning
NIPS 2022
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data
NIPS 2021
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation
AAAI 2021
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
ICML 2019