Hongyuan Zha

Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment ACL 2026 A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations ICLR 2025 Backdoor Mitigation by Distance-Driven Detoxification ICCV 2025 Balancing Two Classifiers via A Simplex ETF Structure for Model Calibration CVPR 2025 Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning ICML 2025 Multi-Agent Credit Assignment with Pretrained Language Models AISTATS 2025 Reward Translation via Reward Machine in Semi-Alignable MDPs ICML 2025 A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs AAAI 2024 Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process ICML 2024 Carbon Market Simulation with Adaptive Mechanism Design IJCAI 2024 Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification ICML 2024 Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization NeurIPS 2024 Learning to Optimize Permutation Flow Shop Scheduling via Graph-Based Imitation Learning AAAI 2024 Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor NeurIPS 2024 Transfer Learning for Diffusion Models NeurIPS 2024 F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning JMLR 2023 Hierarchical Diffusion for Offline Decision Making ICML 2023 Information Design in Multi-Agent Reinforcement Learning NeurIPS 2023 Low-rank matrix recovery with unknown correspondence UAI 2023 Mean Parity Fair Regression in RKHS AISTATS 2023 Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features NeurIPS 2023 Reinforcement Learning for Adaptive Mesh Refinement AISTATS 2023 Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples NeurIPS 2023 SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process ICML 2023 Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport NeurIPS 2022 Dealing with Non-Stationarity in MARL via Trust-Region Decomposition ICLR 2022 Hessian-Free High-Resolution Nesterov Acceleration For Sampling ICML 2022 Learning Prototype-oriented Set Representations for Meta-Learning ICLR 2022 Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification NeurIPS 2022 Self-Training with Differentiable Teacher NAACL 2022 Sqrt(d) Dimension Dependence of Langevin Monte Carlo ICLR 2022 Structural Landmarking and Interaction Modelling: A “SLIM” Network for Graph Classification AAAI 2022 VMAgent: A Practical Virtual Machine Scheduling Platform IJCAI 2022 A Hypergradient Approach to Robust Regression without Correspondence ICLR 2021 Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators NeurIPS 2021 Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances AAAI 2021 Graph-Based Tri-Attention Network for Answer Ranking in CQA AAAI 2021 Learning Graphons via Structured Gromov-Wasserstein Barycenters AAAI 2021 Learning Stochastic Behaviour from Aggregate Data ICML 2021 Random Noise Defense Against Query-Based Black-Box Attacks NeurIPS 2021 Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach ICML 2021 AutoMix: Mixup Networks for Sample Interpolation via Cooperative Barycenter Learning ECCV 2020 CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning ICLR 2020 Differentiable Top-k with Optimal Transport NeurIPS 2020 GraphOpt: Learning Optimization Models of Graph Formation ICML 2020 Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning AAAI 2020 Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies ICLR 2020 Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption AAAI 2020 Learning Strategic Network Emergence Games NeurIPS 2020 Learning to Incentivize Other Learning Agents NeurIPS 2020 Network Diffusions via Neural Mean-Field Dynamics NeurIPS 2020 Single Episode Policy Transfer in Reinforcement Learning ICLR 2020 Transformer Hawkes Process ICML 2020 A Fast Proximal Point Method for Computing Exact Wasserstein Distance UAI 2019 DyRep: Learning Representations over Dynamic Graphs ICLR 2019 Gromov-Wasserstein Learning for Graph Matching and Node Embedding ICML 2019 Joint Link Prediction and Network Alignment via Cross-graph Embedding IJCAI 2019 Learning to Match via Inverse Optimal Transport JMLR 2019 Meta Learning with Relational Information for Short Sequences NeurIPS 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport ICML 2019 Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management IJCAI 2018 Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning IJCAI 2018 Iterative Learning With Open-Set Noisy Labels CVPR 2018 Learning Deep Mean Field Games for Modeling Large Population Behavior ICLR 2018 Learning Registered Point Processes from Idiosyncratic Observations ICML 2018 Learning Sequential Correlation for User Generated Textual Content Popularity Prediction IJCAI 2018 LinkNBed: Multi-Graph Representation Learning with Entity Linkage ACL 2018 A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering NeurIPS 2017 COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution JMLR 2017 Fake News Mitigation via Point Process Based Intervention ICML 2017 Fractal Dimension Invariant Filtering and Its CNN-Based Implementation CVPR 2017 Learning Hawkes Processes from Short Doubly-Censored Event Sequences ICML 2017 Linking Micro Event History to Macro Prediction in Point Process Models AISTATS 2017 Predicting User Activity Level In Point Processes With Mass Transport Equation NeurIPS 2017 Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks JMLR 2017 Wasserstein Learning of Deep Generative Point Process Models NeurIPS 2017 Household Structure Analysis via Hawkes Processes for Enhancing Energy Disaggregation IJCAI 2016 Learning Granger Causality for Hawkes Processes ICML 2016 Modeling Contagious Merger and Acquisition via Point Processes with a Profile Regression Prior IJCAI 2016 Multistage Campaigning in Social Networks NeurIPS 2016 On Modeling and Predicting Individual Paper Citation Count over Time IJCAI 2016 A Matrix Decomposition Perspective to Multiple Graph Matching ICCV 2015 Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades AISTATS 2015 COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution NeurIPS 2015 Discrete Hyper-Graph Matching CVPR 2015 Multi-Task Multi-Dimensional Hawkes Processes for Modeling Event Sequences IJCAI 2015 Portfolio Choices with Orthogonal Bandit Learning IJCAI 2015 Trailer Generation via a Point Process-Based Visual Attractiveness Model IJCAI 2015 Unsupervised Trajectory Clustering via Adaptive Multi-Kernel-Based Shrinkage ICCV 2015 Manifold Based Dynamic Texture Synthesis from Extremely Few Samples CVPR 2014 Shaping Social Activity by Incentivizing Users NeurIPS 2014 Joint Optimization for Consistent Multiple Graph Matching ICCV 2013 Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Learning Triggering Kernels for Multi-dimensional Hawkes Processes ICML 2013 Manifold Based Face Synthesis from Sparse Samples ICCV 2013 Mixture of Mutually Exciting Processes for Viral Diffusion ICML 2013 Scalable Influence Estimation in Continuous-Time Diffusion Networks NeurIPS 2013 Towards Effective Prioritizing Water Pipe Replacement and Rehabilitation IJCAI 2013 Uncover Topic-Sensitive Information Diffusion Networks AISTATS 2013 Bridging the Language Gap: Topic Adaptation for Documents with Different Technicality AISTATS 2011 Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora NeurIPS 2009 Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm NeurIPS 2008 A General Boosting Method and its Application to Learning Ranking Functions for Web Search NeurIPS 2007