Lijun Zhang

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