← Authors

Lijun Zhang

141 papers · 2013–2026 · 16 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (32) 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (12) 🌍 Conference Polyglot (16) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (33) πŸ‘‘ Domain Dominant (34) πŸ”¬ Deep Specialist (24) πŸ† Grand Slam 🀝 Dynamic Duo (32) πŸ† Keyword Champion (10) πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter ⚑ Prolific Year (12) πŸ—ƒοΈ Keyword Collector (145) πŸ”₯ Unstoppable (13) πŸš€ Conference Pioneer πŸ’Ž Century Club (138) ❓ The Questioner (2)

Conferences

ICML (33) NIPS (33) IJCAI (18) AAAI (17) JMLR (9) AISTATS (6) COLT (6) ICLR (4) CVPR (3) ICCV (3) ECCV (2) MICCAI (2) UAI (2) AUTOML (1) L4DC (1) WACV (1)

Top co-authors

Tianbao Yang (32) Yuanyu Wan (22) Zhi-Hua Zhou (20) Rong Jin (18) Guanghui Wang (16) Yibo Wang (15) Wei Jiang (14) Jinfeng Yi (13) Shiyin Lu (12) Peng Zhao (12)

Keywords

regret bound (29) online convex optimization (26) online learning (26) dynamic regret (24) stochastic optimization (20) convex optimization (15) adaptive regret (11) strong convexity (8) online algorithm (7) strongly convex (7) convergence rate (7) gradient descent (6) non-stationary environment (6) projection-free algorithm (5) smooth function (5) variance reduction (5) distributed learning (5) compositional optimization (5) representation learning (4) stochastic gradient (4)

Papers

Parameter-Free Clustering via Self-Supervised Consensus Maximization AAAI 2026
BadThink: Triggered Overthinking Attacks on Chain-of-Thought Reasoning in Large Language Models AAAI 2026
SL-CBM: Enhancing Concept Bottleneck Models with Semantic Locality for Better Interpretability AAAI 2026
Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding CVPR 2025
Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning CVPR 2025
Optimal and Efficient Algorithms for Decentralized Online Convex Optimization JMLR 2025
Self-adaptive Vision-Language Model for 3D Segmentation of Pulmonary Artery and Vein MICCAI 2025
Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound JMLR 2025
Universal Online Convex Optimization Meets Second-order Bounds JMLR 2025
Efficient Methods for Non-stationary Online Learning JMLR 2025
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025
Dimension-Free Adaptive Subgradient Methods with Frequent Directions ICML 2025
Revisiting Projection-Free Online Learning with Time-Varying Constraints AAAI 2025
Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation AAAI 2025
External Knowledge Injection for CLIP-Based Class-Incremental Learning ICCV 2025
Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power ICLR 2025
On the Generalization of Feature Incremental Learning IJCAI 2025
Smoothed Online Convex Optimization with Delayed Feedback IJCAI 2025
Training Verification-Friendly Neural Networks via Neuron Behavior Consistency AAAI 2025
Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport MICCAI 2025
One-step Label Shift Adaptation via Robust Weight Estimation IJCAI 2025
Deep Semantic Graph Transformer for Multi-View 3D Human Pose Estimation AAAI 2024
Deep Homography Estimation for Visual Place Recognition AAAI 2024
Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees AAAI 2024
Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors ECCV 2024
OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS ICLR 2024
Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition ICLR 2024
Non-stationary Online Convex Optimization with Arbitrary Delays ICML 2024
Small-loss Adaptive Regret for Online Convex Optimization ICML 2024
Improved Regret for Bandit Convex Optimization with Delayed Feedback NIPS 2024
SuperVLAD: Compact and Robust Image Descriptors for Visual Place Recognition NIPS 2024
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions NIPS 2024
Universal Online Convex Optimization with $1$ Projection per Round NIPS 2024
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction NIPS 2024
Attack-Resilient Image Watermarking Using Stable Diffusion NIPS 2024
Online Non-convex Learning in Dynamic Environments NIPS 2024
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NIPS 2024
Online Composite Optimization Between Stochastic and Adversarial Environments NIPS 2024
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees NIPS 2024
Generalizablity of Memorization Neural Network NIPS 2024
Scalable Constrained Policy Optimization for Safe Multi-agent Reinforcement Learning NIPS 2024
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization ICML 2024
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond ICML 2024
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack ICML 2024
Efficient Stochastic Approximation of Minimax Excess Risk Optimization ICML 2024
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails ICML 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization JMLR 2024
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization JMLR 2024
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO ICML 2024
Nearly Optimal Regret for Decentralized Online Convex Optimization COLT 2024
CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition CVPR 2024
Asynchronous Large Language Model Enhanced Planner for Autonomous Driving ECCV 2024
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization ICML 2023
Improved Dynamic Regret for Online Frank-Wolfe COLT 2023
Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization ICML 2023
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models ICCV 2023
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization ICML 2023
Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023
Model Predictive Control with Reach-avoid Analysis IJCAI 2023
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards NIPS 2023
Stochastic Approximation Approaches to Group Distributionally Robust Optimization NIPS 2023
Flow: Per-instance Personalized Federated Learning NIPS 2023
Set-membership Belief State-based Reinforcement Learning for POMDPs ICML 2023
Stochastic Graphical Bandits with Heavy-Tailed Rewards UAI 2023
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance ICML 2022
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor NIPS 2022
Efficient Methods for Non-stationary Online Learning NIPS 2022
Online Frank-Wolfe with Arbitrary Delays NIPS 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization NIPS 2022
AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning NIPS 2022
A Tree-Structured Multi-Task Model Recommender AUTOML 2022
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization AISTATS 2022
Projection-free Distributed Online Learning with Sublinear Communication Complexity JMLR 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization ICML 2022
Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence ICML 2022
A Simple yet Universal Strategy for Online Convex Optimization ICML 2022
Synthesizing Good-Enough Strategies for LTLf Specifications IJCAI 2021
Deep Unified Cross-Modality Hashing by Pairwise Data Alignment IJCAI 2021
Projection-free Online Learning in Dynamic Environments AAAI 2021
Approximate Multiplication of Sparse Matrices with Limited Space AAAI 2021
Stochastic Bandits with Graph Feedback in Non-Stationary Environments AAAI 2021
Stochastic Graphical Bandits with Adversarial Corruptions AAAI 2021
Online Convex Optimization with Continuous Switching Constraint NIPS 2021
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions NIPS 2021
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions L4DC 2021
Revisiting Smoothed Online Learning NIPS 2021
Bandit Convex Optimization in Non-stationary Environments JMLR 2021
HRegNet: A Hierarchical Network for Large-Scale Outdoor LiDAR Point Cloud Registration ICCV 2021
Projection-free Online Learning over Strongly Convex Sets AAAI 2021
Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization AAAI 2020
Dynamic Regret of Convex and Smooth Functions NIPS 2020
How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks? NIPS 2020
Minimizing Dynamic Regret and Adaptive Regret Simultaneously AISTATS 2020
A Simple Approach for Non-stationary Linear Bandits AISTATS 2020
Bandit Convex Optimization in Non-stationary Environments AISTATS 2020
SAdam: A Variant of Adam for Strongly Convex Functions ICLR 2020
Projection-free Distributed Online Convex Optimization with $O(\sqrtT)$ Communication Complexity ICML 2020
Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs IJCAI 2020
Online Learning in Changing Environments IJCAI 2020
An Adversarial Domain Adaptation Network for Cross-Domain Fine-Grained Recognition WACV 2020
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate COLT 2019
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion JMLR 2019
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss IJCAI 2019
Multi-Objective Generalized Linear Bandits IJCAI 2019
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization UAI 2019
Adaptive Regret of Convex and Smooth Functions ICML 2019
Adaptive Online Learning in Dynamic Environments NIPS 2018
Dynamic Regret of Strongly Adaptive Methods ICML 2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NIPS 2018
$\ell_1$-regression with Heavy-tailed Distributions NIPS 2018
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer AISTATS 2018
Efficient Adaptive Online Learning via Frequent Directions IJCAI 2018
Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018
Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems IJCAI 2018
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates ICML 2017
Storage Fit Learning with Unlabeled Data IJCAI 2017
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization IJCAI 2017
Semi-Supervised Deep Hashing with a Bipartite Graph IJCAI 2017
Scalable Demand-Aware Recommendation NIPS 2017
Learning with Feature Evolvable Streams NIPS 2017
Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds COLT 2017
Improved Dynamic Regret for Non-degenerate Functions NIPS 2017
Online Stochastic Linear Optimization under One-bit Feedback ICML 2016
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016
Theory of Dual-sparse Regularized Randomized Reduction ICML 2015
A Simple Probabilistic Extension of Modal Mu-calculus IJCAI 2015
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection ICML 2015
Planning for Stochastic Games with Co-Safe Objectives IJCAI 2015
A Simple Homotopy Algorithm for Compressive Sensing AISTATS 2015
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization COLT 2015
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data ICML 2014
Efficient Algorithms for Robust One-bit Compressive Sensing ICML 2014
Online Kernel Learning with a Near Optimal Sparsity Bound ICML 2013
Recovering the Optimal Solution by Dual Random Projection COLT 2013
Linear Convergence with Condition Number Independent Access of Full Gradients NIPS 2013
Mixed Optimization for Smooth Functions NIPS 2013
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions ICML 2013
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion ICML 2013