← Authors

Xinhua Zhang

40 papers · 2006–2026 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (19) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (7) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (23) 🌍 Conference Polyglot (7) πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (20) πŸ”¬ Deep Specialist (17) πŸ† Keyword Champion πŸ’Ž Century Club (39) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (86) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (14)

Conferences

NIPS (20) AISTATS (6) ICML (6) AAAI (2) COLT (2) JMLR (2) UAI (2)

Top co-authors

Yaoliang Yu (9) Dale Schuurmans (7) Zhan Shi (6) Zishun Yu (6) Brian Ziebart (5) Yingyi Ma (4) Vignesh Ganapathiraman (4) Yao-Liang Yu (3) S.v.n. Vishwanathan (3) Mohammad Ali Bashiri (3)

Keywords

convex optimization (11) kernel methods (6) distributionally robust optimization (4) graphical model (4) conditional gradient (4) semi-supervised learning (3) graph matching (3) structured prediction (3) representation learning (3) support vector machine (3) linear convergence (2) sparse optimization (2) adversarial learning (2) trace norm (2) cutting plane method (2) reproducing kernel hilbert space (2) bregman divergence (2) semi-definite programming (2) adversarial robustness (2) online learning (2)

Papers

Language Model Distillation: A Temporal Difference Imitation Learning Perspective AAAI 2026
Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning AAAI 2025
Fairness Risks for Group-Conditionally Missing Demographics AISTATS 2025
Offline Reward Perturbation Boosts Distributional Shift in Online RL UAI 2024
Actor-Critic Alignment for Offline-to-Online Reinforcement Learning ICML 2023
Poisoning Generative Replay in Continual Learning to Promote Forgetting ICML 2023
Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound UAI 2022
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks AISTATS 2022
Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats NIPS 2022
Warping Layer: Representation Learning for Label Structures in Weakly Supervised Learning AISTATS 2022
Moment Distributionally Robust Tree Structured Prediction NIPS 2022
Distributionally Robust Imitation Learning NIPS 2021
Generalised Lipschitz Regularisation Equals Distributional Robustness ICML 2021
Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation NIPS 2021
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks NIPS 2020
Proximal Mapping for Deep Regularization NIPS 2020
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space ICML 2020
Learning Invariant Representations with Kernel Warping AISTATS 2019
Distributionally Robust Graphical Models NIPS 2018
Efficient and Consistent Adversarial Bipartite Matching ICML 2018
Inductive Two-Layer Modeling with Parametric Bregman Transfer ICML 2018
Generalized Conditional Gradient for Sparse Estimation JMLR 2017
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search NIPS 2017
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NIPS 2017
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Convex Two-Layer Modeling with Latent Structure NIPS 2016
Exp-Concavity of Proper Composite Losses COLT 2015
Robust Bayesian Max-Margin Clustering NIPS 2014
Convex Deep Learning via Normalized Kernels NIPS 2014
Convex Two-Layer Modeling NIPS 2013
Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space NIPS 2013
Polar Operators for Structured Sparse Estimation NIPS 2013
Open Problem: Lower bounds for Boosting with Hadamard Matrices COLT 2013
Accelerated Training for Matrix-norm Regularization: A Boosting Approach NIPS 2012
Smoothing Multivariate Performance Measures JMLR 2012
Convex Multi-view Subspace Learning NIPS 2012
Lower Bounds on Rate of Convergence of Cutting Plane Methods NIPS 2010
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures AISTATS 2010
Kernel Measures of Independence for non-iid Data NIPS 2008
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NIPS 2006