Peng Zhao
64 papers · 2006–2026 · 13 venues · across top CS/AI venues
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Research topics
Machine Learning
(58)
Optimization & Theory
(43)
Mathematics & Optimization
(36)
Optimization
(35)
Learning Types Β· Machine Learning
(32)
Artificial Intelligence
(15)
Application Areas
(10)
Core Methods
(10)
Core AI
(9)
Reinforcement Learning
(7)
Learning Paradigms
(7)
Methods
(7)
Deep Learning
(6)
Computer Vision
(4)
Learning Types Β· Deep Learning
(3)
Keywords
dynamic regret
(23)
online learning
(23)
regret bound
(13)
online convex optimization
(11)
stochastic optimization
(7)
non-stationary environment
(6)
gradient variation
(6)
distribution shift
(4)
strongly convex function
(4)
convex optimization
(4)
bandit convex optimization
(3)
linear mixture mdp
(3)
domain adaptation
(3)
online mirror descent
(3)
reinforcement learning
(3)
markov decision process
(2)
contrastive learning
(2)
adversarial learning
(2)
model compression
(2)
sequential decision making
(2)
Papers
A simple, optimal and efficient algorithm for online exp-concave optimization
COLT 2026
Efficient Few-Step Solution Generation via Discrete Flow Matching for Combinatorial Optimization
AAAI 2026
FB-CLIP: Fine-Grained Zero-Shot Anomaly Detection with Foreground-Background Disentanglement
CVPR 2026
Gradient-Variation Regret Bounds for Unconstrained Online Learning
COLT 2026
DGL: Dynamic Global-Local Information Aggregation for Scalable VRP Generalization with Self-Improvement Learning
IJCAI 2025
Efficient Methods for Non-stationary Online Learning
JMLR 2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
ICML 2025
M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation
ACL 2025
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
ICML 2025
TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
ICML 2025
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization
JMLR 2024
A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
NeurIPS 2024
CEAN: Contrastive Event Aggregation Network with LLM-based Augmentation for Event Extraction
EACL 2024
Dynamic Regret of Adversarial MDPs with Unknown Transition and Linear Function Approximation
AAAI 2024
Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
ICML 2024
Generative Model-Based Feature Knowledge Distillation for Action Recognition
AAAI 2024
Gradient-Variation Online Learning under Generalized Smoothness
NeurIPS 2024
Handling Heterogeneous Curvatures in Bandit LQR Control
ICML 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition
AISTATS 2024
Language Without Borders: A Dataset and Benchmark for Code-Switching Lip Reading
NeurIPS 2024
Learning with Adaptive Resource Allocation
ICML 2024
Multi-Attention Based Visual-Semantic Interaction for Few-Shot Learning
IJCAI 2024
Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
NeurIPS 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
JMLR 2024
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
NeurIPS 2024
Structured Optimal Variational Inference for Dynamic Latent Space Models
JMLR 2024
Universal Online Convex Optimization with $1$ Projection per Round
NeurIPS 2024
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation
NeurIPS 2023
Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions
AISTATS 2023
Dynamic Regret of Adversarial Linear Mixture MDPs
NeurIPS 2023
Fast Rates in Time-Varying Strongly Monotone Games
ICML 2023
Non-stationary Online Learning with Memory and Non-stochastic Control
JMLR 2023
Online Non-stochastic Control with Partial Feedback
JMLR 2023
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
ICML 2023
Revisiting Weighted Strategy for Non-stationary Parametric Bandits
AISTATS 2023
Stochastic Approximation Approaches to Group Distributionally Robust Optimization
NeurIPS 2023
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
NeurIPS 2023
Weakly-Supervised Action Localization by Hierarchically-Structured Latent Attention Modeling
ICCV 2023
Adapting to Online Label Shift with Provable Guarantees
NeurIPS 2022
Adaptive Bandit Convex Optimization with Heterogeneous Curvature
COLT 2022
Contrastive Multi-view Hyperbolic Hierarchical Clustering
IJCAI 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits
COLT 2022
Dynamic Regret of Online Markov Decision Processes
ICML 2022
Efficient Methods for Non-stationary Online Learning
NeurIPS 2022
Non-stationary Online Learning with Memory and Non-stochastic Control
AISTATS 2022
No-Regret Learning in Time-Varying Zero-Sum Games
ICML 2022
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits
AISTATS 2022
Bandit Convex Optimization in Non-stationary Environments
JMLR 2021
Exploratory Machine Learning with Unknown Unknowns
AAAI 2021
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions
L4DC 2021
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling
AAAI 2021
Storage Fit Learning with Feature Evolvable Streams
AAAI 2021
Towards Enabling Learnware to Handle Unseen Jobs
AAAI 2021
An Unbiased Risk Estimator for Learning with Augmented Classes
NeurIPS 2020
A Simple Approach for Non-stationary Linear Bandits
AISTATS 2020
A Simple Online Algorithm for Competing with Dynamic Comparators
UAI 2020
Bandit Convex Optimization in Non-stationary Environments
AISTATS 2020
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning
IJCAI 2020
Dynamic Regret of Convex and Smooth Functions
NeurIPS 2020
Learning with Feature and Distribution Evolvable Streams
ICML 2020
Optimal Margin Distribution Learning in Dynamic Environments
AAAI 2020
Robust Softmax Regression for Multi-class Classification with Self-Paced Learning
IJCAI 2017
Stagewise Lasso
JMLR 2007
On Model Selection Consistency of Lasso
JMLR 2006