Xinhua Zhang

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