Weiwei Liu

On the Robustness of Bandit Multiple Testing AAAI 2026 Rademacher Complexity for Distributionally Robust Learning AAAI 2026 An Error Analysis of Flow Matching for Deep Generative Modeling ICML 2025 Model Uncertainty Quantification by Conformal Prediction in Continual Learning ICML 2025 Towards Understanding Catastrophic Forgetting in Two-layer Convolutional Neural Networks ICML 2025 Nonconvex Theory of $M$-estimators with Decomposable Regularizers ICML 2025 A Closer Look at Generalized BH Algorithm for Out-of-Distribution Detection ICML 2025 An Online Statistical Framework for Out-of-Distribution Detection ICML 2025 DRF: Improving Certified Robustness via Distributional Robustness Framework AAAI 2024 Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data AAAI 2024 Sequential Kernel Goodness-of-fit Testing ICML 2024 A Provable Decision Rule for Out-of-Distribution Detection ICML 2024 A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks ICML 2024 The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NIPS 2024 LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation CVPR 2024 Zero-shot Learning for Preclinical Drug Screening IJCAI 2024 A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers NIPS 2024 Error Analysis of Spherically Constrained Least Squares Reformulation in Solving the Stackelberg Prediction Game NIPS 2024 A Closer Look at Curriculum Adversarial Training: From an Online Perspective AAAI 2024 Adversarial Self-Training Improves Robustness and Generalization for Gradual Domain Adaptation NIPS 2023 Characterization of Overfitting in Robust Multiclass Classification NIPS 2023 TraCo: Learning Virtual Traffic Coordinator for Cooperation with Multi-Agent Reinforcement Learning CORL 2023 RVCL: Evaluating the Robustness of Contrastive Learning via Verification JMLR 2023 Generalization Bounds for Adversarial Contrastive Learning JMLR 2023 WAT: Improve the Worst-Class Robustness in Adversarial Training AAAI 2023 Improved Bounds for Multi-task Learning with Trace Norm Regularization COLT 2023 Sample Complexity for Distributionally Robust Learning under chi-square divergence JMLR 2023 DDGR: Continual Learning with Deep Diffusion-based Generative Replay ICML 2023 Better Diffusion Models Further Improve Adversarial Training ICML 2023 Delving into Noisy Label Detection with Clean Data ICML 2023 Deep Partial Multi-Label Learning with Graph Disambiguation IJCAI 2023 A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications NIPS 2023 On the Adversarial Robustness of Out-of-distribution Generalization Models NIPS 2023 Defending Against Adversarial Attacks via Neural Dynamic System NIPS 2022 On the Tradeoff Between Robustness and Fairness NIPS 2022 Robustness Verification for Contrastive Learning ICML 2022 On Robust Multiclass Learnability NIPS 2022 MetaWeighting: Learning to Weight Tasks in Multi-Task Learning ACL 2022 BanditMTL: Bandit-based Multi-task Learning for Text Classification ACL 2021 BanditMTL: Bandit-based Multi-task Learning for Text Classification IJCNLP 2021 Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization IJCAI 2020 Temporal Network Embedding with High-Order Nonlinear Information AAAI 2020 Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification AAAI 2020 Tchebycheff Procedure for Multi-task Text Classification ACL 2020 Adaptive Adversarial Multi-task Representation Learning ICML 2020 Opinion Maximization in Social Trust Networks IJCAI 2020 Collaboration Based Multi-Label Propagation for Fraud Detection IJCAI 2020 Learning From Multi-Dimensional Partial Labels IJCAI 2020 Copula Multi-label Learning NIPS 2019 Discriminative and Correlative Partial Multi-Label Learning IJCAI 2019 Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification AAAI 2019 Sparse Extreme Multi-label Learning with Oracle Property ICML 2019 Ranking Preserving Nonnegative Matrix Factorization IJCAI 2018 Deep Discrete Prototype Multilabel Learning IJCAI 2018 Discrete Network Embedding IJCAI 2018 An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels JMLR 2017 Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions JMLR 2017 Sparse Embedded $k$-Means Clustering NIPS 2017 THU-EE System Description for NIST LRE 2015 INTERSPEECH 2016 On the Optimality of Classifier Chain for Multi-label Classification NIPS 2015