Xinhua Zhang

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

Achievements

+12 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (23) 🌍 Conference Polyglot (7)

🗺️ Taxonomy Completionist (23) 🌍 Conference Polyglot (7) 🌉 Interdisciplinary Bridge 🏠 Conference Loyalist (20) 🔬 Deep Specialist (17) 🏆 Keyword Champion 💎 Century Club (39) 🚀 Conference Pioneer 📈 Trend Setter 🗃️ Keyword Collector (86) ⚡ Prolific Year (5) 🔥 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