Peilin Zhao
92 papers · 2009–2026 · 13 conferences · across top CS/AI conferences
Achievements
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Prolific Year
(7)
Conferences
ICML (20)
IJCAI (16)
AAAI (14)
ICLR (12)
NIPS (12)
AISTATS (3)
CVPR (3)
JMLR (3)
ACL (2)
ACML (2)
EMNLP (2)
ICCV (2)
WACV (1)
Top co-authors
Research topics
Keywords
graph neural network
(11)
online learning
(10)
stochastic optimization
(4)
generative model
(3)
decentralized optimization
(3)
distributed learning
(3)
molecular representation
(3)
time series forecasting
(3)
regret bound
(3)
representation learning
(3)
multi-task learning
(3)
domain generalization
(3)
reaction prediction
(3)
in-context learning
(2)
test-time adaptation
(2)
reinforcement learning
(2)
deep reinforcement learning
(2)
similarity learning
(2)
video understanding
(2)
active learning
(2)
Papers
CrystalDiT: Simple Diffusion Transformers for Crystal Generation
AAAI 2026
The Stackelberg Speaker: Optimizing Persuasive Communication in Social Deduction Games
ACL 2026
Injecting Imbalance Sensitivity for Multi-Task Learning
IJCAI 2025
Measuring Diversity in Synthetic Datasets
ICML 2025
Test-time Adapted Reinforcement Learning with Action Entropy Regularization
ICML 2025
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
ICML 2025
Self-Bootstrapping for Versatile Test-Time Adaptation
ICML 2025
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
ICML 2025
Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity
ICML 2025
IgGM: A Generative Model for Functional Antibody and Nanobody Design
ICLR 2025
COME: Test-time Adaption by Conservatively Minimizing Entropy
ICLR 2025
TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
ICLR 2025
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
ICLR 2025
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model
AAAI 2025
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
ICLR 2025
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
AAAI 2025
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay
EMNLP 2024
SDformer: Similarity-driven Discrete Transformer For Time Series Generation
NIPS 2024
Latent Diffusion Transformer for Probabilistic Time Series Forecasting
AAAI 2024
WatME: Towards Lossless Watermarking Through Lexical Redundancy
ACL 2024
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
ICLR 2024
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
ICLR 2024
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution
ICLR 2024
Test-Time Model Adaptation with Only Forward Passes
ICML 2024
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
ICML 2024
Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations
IJCAI 2024
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
ICML 2023
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition
CVPR 2023
On the Pitfall of Mixup for Uncertainty Calibration
CVPR 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery β a Focus on Affinity Prediction Problems with Noise Annotations
AAAI 2023
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
AAAI 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
ICLR 2023
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion
ICLR 2023
Towards Stable Test-time Adaptation in Dynamic Wild World
ICLR 2023
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges
IJCAI 2023
Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction
IJCAI 2023
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification
AAAI 2023
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
NIPS 2023
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
NIPS 2023
Fairness-guided Few-shot Prompting for Large Language Models
NIPS 2023
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup
NIPS 2022
Learning Neural Set Functions Under the Optimal Subset Oracle
NIPS 2022
$p$-Laplacian Based Graph Neural Networks
ICML 2022
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks
AAAI 2022
Local Augmentation for Graph Neural Networks
ICML 2022
Efficient Test-Time Model Adaptation without Forgetting
ICML 2022
SVIP: Sequence VerIfication for Procedures in Videos
CVPR 2022
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
AISTATS 2021
Context-Aware Domain Adaptation in Semantic Segmentation
WACV 2021
AdaXpert: Adapting Neural Architecture for Growing Data
ICML 2021
Meta-learning Hyperparameter Performance Prediction with Neural Processes
ICML 2021
Meta-learning with an Adaptive Task Scheduler
NIPS 2021
Hierarchical Graph Capsule Network
AAAI 2021
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
ICCV 2021
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning
AAAI 2021
RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist
NIPS 2020
Towards Fast Adaptation of Neural Architectures with Meta Learning
ICLR 2020
Aggregated Gradient Langevin Dynamics
AAAI 2020
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
AAAI 2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
AAAI 2020
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
ICML 2020
Adversarial Sparse Transformer for Time Series Forecasting
NIPS 2020
Contextualized Point-of-Interest Recommendation
IJCAI 2020
Relation-Aware Transformer for Portfolio Policy Learning
IJCAI 2020
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
NIPS 2019
Confidence Weighted Multitask Learning
AAAI 2019
Decentralized Optimization with Edge Sampling
IJCAI 2019
Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies
IJCAI 2019
Graph Convolutional Networks for Temporal Action Localization
ICCV 2019
Complexities in Projection-Free Stochastic Non-convex Minimization
AISTATS 2019
Hyperparameter Learning via Distributional Transfer
NIPS 2019
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
ICML 2018
Bandit Online Learning on Graphs via Adaptive Optimization
IJCAI 2018
High-dimensional Similarity Learning via Dual-sparse Random Projection
IJCAI 2018
Learning User Dependencies for Recommendation
IJCAI 2017
Locally Linear Factorization Machines
IJCAI 2017
Online Multitask Relative Similarity Learning
IJCAI 2017
Projection-free Distributed Online Learning in Networks
ICML 2017
Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data
EMNLP 2016
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization
ICML 2016
Cost Sensitive Online Multiple Kernel Classification
ACML 2016
Large Scale Online Kernel Learning
JMLR 2016
Online Learning to Rank for Content-Based Image Retrieval
IJCAI 2015
Adaptive Stochastic Alternating Direction Method of Multipliers
ICML 2015
Stochastic Optimization with Importance Sampling for Regularized Loss Minimization
ICML 2015
A Boosting Algorithm for Item Recommendation with Implicit Feedback
IJCAI 2015
Online Passive Aggressive Active Learning and Its Applications
ACML 2014
LIBOL: A Library for Online Learning Algorithms
JMLR 2014
Large Scale Online Kernel Classification
IJCAI 2013
Double Updating Online Learning
JMLR 2011
Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection
AISTATS 2011
DUOL: A Double Updating Approach for Online Learning
NIPS 2009