Guangquan Zhang

18 papers · 2017–2026 · 6 conferences · across top CS/AI conferences

Achievements

+7 more ↓

🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (5) 🏃 Academic Marathon (8) 🗺️ Taxonomy Completionist (30)

🌍 Conference Polyglot (5) 🏃 Academic Marathon (8) 🌈 Renaissance Researcher (6) 🤝 Dynamic Duo (12) ❓ The Questioner 💎 Century Club (13) 🗃️ Keyword Collector (66)

Conferences

AAAI (7) ICML (4) IJCAI (3) ICCV (2) ACL (1) ICLR (1)

Top co-authors

Jie Lu (17) Zhen Fang (7) Anjin Liu (5) Feng Liu (4) Pengqian Lu (3) En Yu (3) Bo Peng (2) Bo Yuan (2) Junyu Xuan (2) Kezhi Lu (1)

Keywords

concept drift (5) drift detection (3) continual learning (2) representation learning (2) gaussian mixture model (2) data stream (2) ensemble learning (1) online learning (1) deep reinforcement learning (1) policy learning (1) unsupervised domain adaptation (1) partial label learning (1) covariate shift (1) hypothesis testing (1) image clustering (1) knowledge distillation (1) maximum mean discrepancy (1) distribution shift (1) skill discovery (1) covariate shift adaptation (1)

Papers

Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning AAAI 2026 PARS: Partial-Label-Learning-inspired Recommender Systems AAAI 2026 Discovering Mixture Skills for Unsupervised Reinforcement Learning AAAI 2026 TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG ACL 2026 Autonomous Concept Drift Threshold Determination AAAI 2026 On the Provable Importance of Gradients for Autonomous Language-Assisted Image Clustering ICCV 2025 Early Concept Drift Detection via Prediction Uncertainty AAAI 2025 Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer ICLR 2025 Adaptive Stabilization Based on Machine Learning for Column Generation ICML 2024 Online Boosting Adaptive Learning under Concept Drift for Multistream Classification AAAI 2024 Knowledge Distillation with Auxiliary Variable ICML 2024 A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points IJCAI 2024 Meta OOD Learning For Continuously Adaptive OOD Detection ICCV 2023 How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? AAAI 2021 Learning Bounds for Open-Set Learning ICML 2021 Learning Deep Kernels for Non-Parametric Two-Sample Tests ICML 2020 Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation IJCAI 2020 Regional Concept Drift Detection and Density Synchronized Drift Adaptation IJCAI 2017