← Authors

Zhi-Hua Zhou

148 papers · 2010–2026 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (38) 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (15) 🌍 Conference Polyglot (10) 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (8) 🏠 Conference Loyalist (43) πŸ† Keyword Champion πŸ”¬ Deep Specialist (13) 🀝 Dynamic Duo (36) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (181) ⚑ Prolific Year (12) πŸ’Ž Century Club (146) πŸ”₯ Unstoppable (16)

Conferences

NIPS (43) IJCAI (31) ICML (29) AAAI (14) JMLR (10) AISTATS (8) ACML (7) COLT (3) ICLR (2) UAI (1)

Top co-authors

Peng Zhao (36) Lijun Zhang (20) Yuan Jiang (18) Wei Gao (13) Yang Yu (12) Tian-Zuo Wang (12) Rong Jin (10) Yu-Jie Zhang (10) Yu-feng Li (8) Yu-Hu Yan (7)

Research topics

Privacy (1)

Keywords

online learning (24) dynamic regret (19) online convex optimization (11) model reuse (8) semi-supervised learning (8) non-stationary environment (7) regret bound (7) stochastic optimization (6) abductive learning (6) convex optimization (6) transfer learning (6) active learning (6) multi-instance learning (5) adaptive regret (5) gradient variation (5) distribution shift (5) reinforcement learning (4) ensemble learning (4) learning theory (4) representation learning (4)

Papers

CoRE-Learning with Look-Ahead and Immediate Resource Allocation AAAI 2026
Tabular Learnwares Can Be Repurposed for Seemingly Irrelevant New Tasks AAAI 2026
On the Diversity of Adversarial Ensemble Learning ICML 2025
Gradient-Based Nonlinear Rehearsal Learning with Multivariate Alterations AAAI 2025
Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection AAAI 2025
Avoiding Undesired Future with Sequential Decisions IJCAI 2025
Identifying and Reusing Learnwares Across Different Label Spaces IJCAI 2025
Enabling Optimal Decisions in Rehearsal Learning under CARE Condition ICML 2025
Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection (Extended Abstract) IJCAI 2025
One-Pass Feature Evolvable Learning with Theoretical Guarantees ICML 2025
Efficient Methods for Non-stationary Online Learning JMLR 2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update ICML 2025
Polynomial-Delay MAG Listing with Novel Locally Complete Orientation Rules ICML 2025
TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree ICML 2025
Learning Only When It Matters: Cost-Aware Long-Tailed Classification AAAI 2024
On the Intrinsic Structures of Spiking Neural Networks JMLR 2024
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization JMLR 2024
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation ICML 2024
Learning with Adaptive Resource Allocation ICML 2024
An Efficient Maximal Ancestral Graph Listing Algorithm ICML 2024
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts ICML 2024
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations NIPS 2024
Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation NIPS 2024
On the Ability of Developers' Training Data Preservation of Learnware NIPS 2024
Gradient-Variation Online Learning under Generalized Smoothness NIPS 2024
Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs NIPS 2024
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation NIPS 2024
Avoiding Undesired Future with Minimal Cost in Non-Stationary Environments NIPS 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning ICLR 2024
Safe Abductive Learning in the Presence of Inaccurate Rules AAAI 2024
Towards Making Learnware Specification and Market Evolvable AAAI 2024
Dynamic Regret of Adversarial MDPs with Unknown Transition and Linear Function Approximation AAAI 2024
Estimating Possible Causal Effects with Latent Variables via Adjustment ICML 2023
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning ICLR 2023
Handling Learnwares Developed from Heterogeneous Feature Spaces without Auxiliary Data IJCAI 2023
Enabling Abductive Learning to Exploit Knowledge Graph IJCAI 2023
Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent NIPS 2023
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach NIPS 2023
On the Gini-impurity Preservation For Privacy Random Forests NIPS 2023
Stochastic Approximation Approaches to Group Distributionally Robust Optimization NIPS 2023
Dynamic Regret of Adversarial Linear Mixture MDPs NIPS 2023
Rehearsal Learning for Avoiding Undesired Future NIPS 2023
Enabling Knowledge Refinement upon New Concepts in Abductive Learning AAAI 2023
Fast Rates in Time-Varying Strongly Monotone Games ICML 2023
Online Non-stochastic Control with Partial Feedback JMLR 2023
Non-stationary Online Learning with Memory and Non-stochastic Control JMLR 2023
On the Consistency Rate of Decision Tree Learning Algorithms AISTATS 2023
Revisiting Weighted Strategy for Non-stationary Parametric Bandits AISTATS 2023
Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions AISTATS 2023
Identifying Useful Learnwares for Heterogeneous Label Spaces ICML 2023
Depth is More Powerful than Width with Prediction Concatenation in Deep Forest NIPS 2022
Efficient Methods for Non-stationary Online Learning NIPS 2022
Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge NIPS 2022
No-Regret Learning in Time-Varying Zero-Sum Games ICML 2022
Dynamic Regret of Online Markov Decision Processes ICML 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits COLT 2022
Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning NIPS 2022
Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks NIPS 2022
Non-stationary Online Learning with Memory and Non-stochastic Control AISTATS 2022
Adapting to Online Label Shift with Provable Guarantees NIPS 2022
Theoretically Provable Spiking Neural Networks NIPS 2022
Fast Provably Robust Decision Trees and Boosting ICML 2022
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions NIPS 2021
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable NIPS 2021
Bandit Convex Optimization in Non-stationary Environments JMLR 2021
Bifurcation Spiking Neural Network JMLR 2021
Budgeted Heterogeneous Treatment Effect Estimation ICML 2021
Storage Fit Learning with Feature Evolvable Streams AAAI 2021
Towards Enabling Learnware to Handle Unseen Jobs AAAI 2021
Exploratory Machine Learning with Unknown Unknowns AAAI 2021
Towards Convergence Rate Analysis of Random Forests for Classification NIPS 2020
An Unbiased Risk Estimator for Learning with Augmented Classes NIPS 2020
Dynamic Regret of Convex and Smooth Functions NIPS 2020
Control Flow Graph Embedding Based on Multi-Instance Decomposition for Bug Localization AAAI 2020
Differentially Private Learning with Small Public Data AAAI 2020
Boosting-Based Reliable Model Reuse ACML 2020
A Simple Approach for Non-stationary Linear Bandits AISTATS 2020
Bandit Convex Optimization in Non-stationary Environments AISTATS 2020
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data ICML 2020
Cost-effectively Identifying Causal Effects When Only Response Variable is Observable ICML 2020
Learning with Feature and Distribution Evolvable Streams ICML 2020
A Simple Online Algorithm for Competing with Dynamic Comparators UAI 2020
A Refined Margin Distribution Analysis for Forest Representation Learning NIPS 2019
Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin ICML 2019
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019
Adaptive Regret of Convex and Smooth Functions ICML 2019
Reinforcement Learning Experience Reuse with Policy Residual Representation IJCAI 2019
Partial Label Learning with Unlabeled Data IJCAI 2019
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder NIPS 2019
Bridging Machine Learning and Logical Reasoning by Abductive Learning NIPS 2019
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate COLT 2019
$\ell_1$-regression with Heavy-tailed Distributions NIPS 2018
Tri-net for Semi-Supervised Deep Learning IJCAI 2018
Experienced Optimization with Reusable Directional Model for Hyper-Parameter Search IJCAI 2018
Learning Environmental Calibration Actions for Policy Self-Evolution IJCAI 2018
Semi-Supervised Optimal Margin Distribution Machines IJCAI 2018
Preference Based Adaptation for Learning Objectives NIPS 2018
Multi-Layered Gradient Boosting Decision Trees NIPS 2018
Unorganized Malicious Attacks Detection NIPS 2018
Adaptive Online Learning in Dynamic Environments NIPS 2018
Dynamic Regret of Strongly Adaptive Methods ICML 2018
Rectify Heterogeneous Models with Semantic Mapping ICML 2018
Deep Forest: Towards An Alternative to Deep Neural Networks IJCAI 2017
Subset Selection under Noise NIPS 2017
Improved Dynamic Regret for Non-degenerate Functions NIPS 2017
Learning with Feature Evolvable Streams NIPS 2017
Storage Fit Learning with Unlabeled Data IJCAI 2017
Cost-Effective Active Learning from Diverse Labelers IJCAI 2017
Optimizing Ratio of Monotone Set Functions IJCAI 2017
Obtaining High-Quality Label by Distinguishing between Easy and Hard Items in Crowdsourcing IJCAI 2017
Deep Descriptor Transforming for Image Co-Localization IJCAI 2017
Incomplete Label Distribution Learning IJCAI 2017
Multi-Instance Learning with Key Instance Shift IJCAI 2017
Multi-Class Optimal Margin Distribution Machine ICML 2017
A Unified View of Multi-Label Performance Measures ICML 2017
What Makes Objects Similar: A Unified Multi-Metric Learning Approach NIPS 2016
Learnability of Non-I.I.D. ACML 2016
Parallel Pareto Optimization for Subset Selection IJCAI 2016
Cost-Saving Effect of Crowdsourcing Learning IJCAI 2016
Online Stochastic Linear Optimization under One-bit Feedback ICML 2016
Learning Unified Features from Natural and Programming Languages for Locating Buggy Source Code IJCAI 2016
Graph Quality Judgement: A Large Margin Expedition IJCAI 2016
On Constrained Boolean Pareto Optimization IJCAI 2015
CUR Algorithm for Partially Observed Matrices ICML 2015
On the Consistency of AUC Pairwise Optimization IJCAI 2015
Multi-Label Active Learning: Query Type Matters IJCAI 2015
Active Learning from Crowds with Unsure Option IJCAI 2015
Subset Selection by Pareto Optimization NIPS 2015
A Simple Homotopy Algorithm for Compressive Sensing AISTATS 2015
One-Pass Multi-View Learning ACML 2015
Statistical Unfolded Logic Learning ACML 2015
Top Rank Optimization in Linear Time NIPS 2014
Learning with Augmented Multi-Instance View ACML 2014
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning NIPS 2013
Convex and Scalable Weakly Labeled SVMs JMLR 2013
Multi-Instance Multi-Label Learning with Weak Label IJCAI 2013
On the Approximation Ability of Evolutionary Optimization with Application to Minimum Set Cover: Extended Abstract IJCAI 2013
Uniform Convergence, Stability and Learnability for Ranking Problems IJCAI 2013
Co-Training with Insufficient Views ACML 2013
One-Pass AUC Optimization ICML 2013
Multi-Modal Image Annotation with Multi-Instance Multi-Label LDA IJCAI 2013
NystrΓΆm Method vs Random Fourier Features: A Theoretical and Empirical Comparison NIPS 2012
Key Instance Detection in Multi-Instance Learning ACML 2012
A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin JMLR 2011
On the Consistency of Multi-Label Learning COLT 2011
Multi-View Active Learning in the Non-Realizable Case NIPS 2010
Active Learning by Querying Informative and Representative Examples NIPS 2010