← Authors

Hongyuan Zha

102 papers · 2007–2025 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (11) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (13) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (32) 🌟 Keyword Trendsetter Combo (12) 🏠 Conference Loyalist (25) πŸ† Grand Slam 🀝 Dynamic Duo (16) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (15) πŸ† Keyword Champion (5) ⚑ Prolific Year (9) πŸ“ˆ Trend Setter πŸ’Ž Century Club (102) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (98) πŸ”₯ Unstoppable (13)

Conferences

NIPS (25) ICML (19) IJCAI (13) ICLR (10) AAAI (8) AISTATS (8) CVPR (5) ICCV (5) JMLR (4) UAI (2) ACL (1) ECCV (1) NAACL (1)

Top co-authors

Junchi Yan (16) Le Song (15) Hongteng Xu (14) Mehrdad Farajtabar (11) Xiaojing Ye (10) Tuo Zhao (9) Xiangfeng Wang (9) Wenhao Li (8) Bo Jin (8) Jiachen Yang (7)

Research topics

Privacy (2)

Keywords

point process (13) hawkes process (12) convex optimization (8) social network (7) optimal transport (7) temporal point process (6) event sequence (5) domain adaptation (5) wasserstein distance (4) graph matching (4) multi-agent reinforcement learning (4) graph neural network (4) influence maximization (3) reinforcement learning (3) backdoor attack (3) generative model (3) transfer learning (3) alternating optimization (3) probabilistic modeling (3) manifold learning (3)

Papers

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