Lei, Qi

51 publications

ICLR 2025 Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang

UAI 2025 Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

ICCV 2025 Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective Hoang Phan, Lam Tran, Quyen Tran, Ngoc Tran, Tuan Truong, Qi Lei, Nhat Ho, Dinh Phung, Trung Le

CPAL 2025 Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tao Wen, Elynn Chen, Yuzhou Chen, Qi Lei

AISTATS 2025 Bridging Domains with Approximately Shared Features Ziliang Samuel Zhong, Xiang Pan, Qi Lei

AISTATS 2025 Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu, Zihan Wang, Yuxiao Chen, Qi Lei

ICML 2025 Discrepancies Are Virtue: Weak-to-Strong Generalization Through Lens of Intrinsic Dimension Yijun Dong, Yicheng Li, Yunai Li, Jason D. Lee, Qi Lei

AISTATS 2025 Elastic Representation: Mitigating Spurious Correlations for Group Robustness Tao Wen, Zihan Wang, Quan Zhang, Qi Lei

CPAL 2025 Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining Jianwei Li, Yijun Dong, Qi Lei

NeurIPS 2025 Hyperparameter Transfer Enables Consistent Gains of Matrix-Preconditioned Optimizers Across Scales Shikai Qiu, Zixi Chen, Hoang Phan, Qi Lei, Andrew Gordon Wilson

CVPR 2025 Mono3DVLT: Monocular-Video-Based 3D Visual Language Tracking Hongkai Wei, Yang Yang, Shijie Sun, Mingtao Feng, Xiangyu Song, Qi Lei, Hongli Hu, Rong Wang, Huansheng Song, Naveed Akhtar, Ajmal Saeed Mian

NeurIPS 2025 Performative Risk Control: Calibrating Models for Reliable Deployment Under Performativity Victor Li, Baiting Chen, Yuzhen Mao, Qi Lei, Zhun Deng

ICML 2024 An Information-Theoretic Analysis of In-Context Learning Hong Jun Jeon, Jason D. Lee, Qi Lei, Benjamin Van Roy

ICML 2024 Controllable Prompt Tuning for Balancing Group Distributional Robustness Hoang Phan, Andrew Gordon Wilson, Qi Lei

CPAL 2024 Exploring Minimally Sufficient Representation in Active Learning Through Label-Irrelevant Patch Augmentation Zhiyu Xue, Yinlong Dai, Qi Lei

NeurIPSW 2024 Randomly Pivoted V-Optimal Design: Fast Data Selection Under Low Intrinsic Dimension Yijun Dong, Xiang Pan, Hoang Phan, Qi Lei

NeurIPS 2024 Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning Yijun Dong, Hoang Phan, Xiang Pan, Qi Lei

NeurIPS 2024 Stochastic Zeroth-Order Optimization Under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee

NeurIPSW 2023 Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning Jianwei Li, Sheng Liu, Qi Lei

NeurIPS 2023 Cluster-Aware Semi-Supervised Learning: Relational Knowledge Distillation Provably Learns Clustering Yijun Dong, Kevin Miller, Qi Lei, Rachel Ward

AISTATS 2023 Optimal Sample Complexity Bounds for Non-Convex Optimization Under Kurdyka-Lojasiewicz Condition Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee

ICML 2023 Optimization for Amortized Inverse Problems Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

AISTATS 2023 Provable Hierarchy-Based Meta-Reinforcement Learning Kurtland Chua, Qi Lei, Jason Lee

AISTATS 2023 Reconstructing Training Data from Model Gradient, Provably Zihan Wang, Jason Lee, Qi Lei

NeurIPS 2023 Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason Lee

AISTATS 2023 Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei

IJCAI 2022 CAT: Customized Adversarial Training for Improved Robustness Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh

AISTATS 2021 Last Iterate Convergence in No-Regret Learning: Constrained Min-Max Optimization for Convex-Concave Landscapes Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang

ICML 2021 A Theory of Label Propagation for Subpopulation Shift Tianle Cai, Ruiqi Gao, Jason Lee, Qi Lei

ICLR 2021 Few-Shot Learning via Learning the Representation, Provably Simon Shaolei Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei

NeurIPS 2021 Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang, Kaixuan Huang, Sham Kakade, Jason Lee, Qi Lei, Runzhe Wang, Jiaqi Yang

NeurIPS 2021 How Fine-Tuning Allows for Effective Meta-Learning Kurtland Chua, Qi Lei, Jason Lee

ICML 2021 Near-Optimal Linear Regression Under Distribution Shift Qi Lei, Wei Hu, Jason Lee

NeurIPS 2021 Optimal Gradient-Based Algorithms for Non-Concave Bandit Optimization Baihe Huang, Kaixuan Huang, Sham Kakade, Jason Lee, Qi Lei, Runzhe Wang, Jiaqi Yang

NeurIPSW 2021 PANOM: Automatic Hyper-Parameter Tuning for Inverse Problems Tianci Liu, Quan Zhang, Qi Lei

NeurIPS 2021 Predicting What You Already Know Helps: Provable Self-Supervised Learning Jason Lee, Qi Lei, Nikunj Saunshi, Jiacheng Zhuo

ICML 2021 Solving Inverse Problems with a Flow-Based Noise Model Jay Whang, Qi Lei, Alex Dimakis

AISTATS 2020 Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-Norm Balls Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis

NeurIPSW 2020 Compressed Sensing with Invertible Generative Models and Dependent Noise Jay Whang, Qi Lei, Alex Dimakis

NeurIPS 2020 Fast Convergence of Langevin Dynamics on Manifold: Geodesics Meet Log-Sobolev Xiao Wang, Qi Lei, Ioannis Panageas

ICML 2020 SGD Learns One-Layer Networks in WGANs Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis

NeurIPS 2019 Inverting Deep Generative Models, One Layer at a Time Qi Lei, Ajil Jalal, Inderjit S Dhillon, Alexandros G Dimakis

NeurIPS 2019 Primal-Dual Block Generalized Frank-Wolfe Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S Dhillon, Alexandros G Dimakis

IJCAI 2019 Similarity Preserving Representation Learning for Time Series Clustering Qi Lei, Jinfeng Yi, Roman Vaculín, Lingfei Wu, Inderjit S. Dhillon

NeurIPS 2018 Hessian-Based Analysis of Large Batch Training and Robustness to Adversaries Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney

AISTATS 2018 Random Warping Series: A Random Features Method for Time-Series Embedding Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock

ICML 2018 Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization Jiong Zhang, Qi Lei, Inderjit Dhillon

NeurIPS 2017 A Greedy Approach for Budgeted Maximum Inner Product Search Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S Dhillon

ICML 2017 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar

ICML 2017 Gradient Coding: Avoiding Stragglers in Distributed Learning Rashish Tandon, Qi Lei, Alexandros G. Dimakis, Nikos Karampatziakis

NeurIPS 2016 Coordinate-Wise Power Method Qi Lei, Kai Zhong, Inderjit S Dhillon