Sheng-jun Huang
51 papers · 2010–2026 · 9 venues · across top CS/AI venues
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Research topics
Machine Learning
(40)
Learning Types Β· Machine Learning
(31)
Core Methods
(15)
Artificial Intelligence
(10)
Deep Learning
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Optimization & Theory
(10)
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Computer Vision
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Natural Language Processing
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Reinforcement Learning
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active learning
(16)
query strategy
(5)
multi-label classification
(5)
query selection
(3)
neural network optimization
(3)
distribution shift
(3)
annotation cost
(3)
image restoration
(3)
representation learning
(3)
semi-supervised learning
(3)
multi-label learning
(3)
label complexity
(2)
class imbalance
(2)
feature representation
(2)
label noise
(2)
uncertainty sampling
(2)
test-time adaptation
(2)
adversarial training
(2)
uncertainty quantification
(2)
federated learning
(2)
Papers
Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis
CVPR 2026
Federated Active Learning Under Extreme Non-IID and Global Class Imbalance
CVPR 2026
MultiMedBench: A Scenario-Aware Benchmark for Evaluating Knowledge Editing in Medical VQA
AAAI 2026
Reflect Then Learn: Active Prompting for Information Extraction Guided by Introspective Confusion
AAAI 2026
Revisiting Unknowns: Towards Effective and Efficient Open-Set Active Learning
CVPR 2026
DM-POSA: Enhancing Open-World Test-Time Adaptation with Dual-Mode Matching and Prompt-Based Open Set Adaptation
IJCAI 2025
Efficient Heterogeneity-Aware Federated Active Data Selection
ICML 2025
FedDLAD: A Federated Learning Dual-Layer Anomaly Detection Framework for Enhancing Resilience Against Backdoor Attacks
IJCAI 2025
Graph-guided Cross-composition Feature Disentanglement for Compositional Zero-shot Learning
ACL 2025
Improving Generalization of Deep Neural Networks by Optimum Shifting
AAAI 2025
Inconsistency-Based Federated Active Learning
IJCAI 2025
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
ICML 2025
MLC-NC: Long-Tailed Multi-Label Image Classification Through the Lens of Neural Collapse
AAAI 2025
Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach
CVPR 2025
StructSR: Refuse Spurious Details in Real-World Image Super-Resolution
AAAI 2025
Bidirectional Uncertainty-Based Active Learning for Open-Set Annotation
ECCV 2024
Causality-enhanced Discreted Physics-informed Neural Networks for Predicting Evolutionary Equations
IJCAI 2024
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
ICML 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
AAAI 2024
Dual-Decoupling Learning and Metric-Adaptive Thresholding for Semi-Supervised Multi-Label Learning
ECCV 2024
NanoAdapt: Mitigating Negative Transfer in Test Time Adaptation with Extremely Small Batch Sizes
IJCAI 2024
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
ICLR 2024
Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
NeurIPS 2024
Unlocking the Power of Open Set: A New Perspective for Open-Set Noisy Label Learning
AAAI 2024
ALL-E: Aesthetics-guided Low-light Image Enhancement
IJCAI 2023
Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
NeurIPS 2023
Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks
AAAI 2023
Improving Lens Flare Removal with General-Purpose Pipeline and Multiple Light Sources Recovery
ICCV 2023
Multi-Label Knowledge Distillation
ICCV 2023
Active Learning for Multiple Target Models
NeurIPS 2022
Active Learning for Open-Set Annotation
CVPR 2022
Can Adversarial Training Be Manipulated By Non-Robust Features?
NeurIPS 2022
Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels
NeurIPS 2022
Asynchronous Active Learning with Distributed Label Querying
IJCAI 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
NeurIPS 2021
Dual Active Learning for Both Model and Data Selection
IJCAI 2021
Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries
AAAI 2021
Multi-Label Learning with Pairwise Relevance Ordering
NeurIPS 2021
Active Learning with Query Generation for Cost-Effective Text Classification
AAAI 2020
Cost-effectively Identifying Causal Effects When Only Response Variable is Observable
ICML 2020
Partial Multi-Label Learning with Noisy Label Identification
AAAI 2020
Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning
AAAI 2020
Active Sampling for Open-Set Classification without Initial Annotation
AAAI 2019
Multi-View Active Learning for Video Recommendation
IJCAI 2019
Self-Paced Active Learning: Query the Right Thing at the Right Time
AAAI 2019
Cost-Effective Active Learning for Hierarchical Multi-Label Classification
IJCAI 2018
Cost-Effective Active Learning from Diverse Labelers
IJCAI 2017
Multi-instance multi-label active learning
IJCAI 2017
Transfer Learning with Active Queries from Source Domain
IJCAI 2016
Multi-Label Active Learning: Query Type Matters
IJCAI 2015
Active Learning by Querying Informative and Representative Examples
NeurIPS 2010