Liang, Yingyu

77 publications

ICLR 2025 Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou

AISTATS 2025 Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-Context by Multi-Step Gradient Descent Bo Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song

CPAL 2025 Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang

WACV 2025 Differential Privacy Mechanisms in Neural Tangent Kernel Regression Jiuxiang Gu, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song

ICML 2025 Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies Yuefan Cao, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Jiahao Zhang

ICLRW 2025 Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies Yuefan Cao, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Jiahao Zhang

ICLRW 2025 Fast Gradient Computation for RoPE Attention in Almost Linear Time Yifang Chen, Jiayan Huo, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song

CPAL 2025 Fast John Ellipsoid Computation with Differential Privacy Optimization Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Junwei Yu

AISTATS 2025 Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Tianyi Zhou

ICML 2025 Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song

CPAL 2025 HSR-Enhanced Sparse Attention Acceleration Bo Chen, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song

ICLRW 2025 High-Order Matching for One-Step Shortcut Diffusion Models Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan

NeurIPS 2025 Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning Dechen Zhang, Zhenmei Shi, Yi Zhang, Yingyu Liang, Difan Zou

ICCV 2025 Learning to Inference Adaptively for Multimodal Large Language Models Zhuoyan Xu, Khoi Duc Nguyen, Preeti Mukherjee, Saurabh Bagchi, Somali Chaterji, Yingyu Liang, Yin Li

AISTATS 2025 Looped ReLU MLPs May Be All You Need as Practical Programmable Computers Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Yufa Zhou

UAI 2025 NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Xugang Ye

ICLRW 2025 RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation Yuefan Cao, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song

CPAL 2025 The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song

ICLRW 2025 Towards Infinite-Long Prefix in Transformers Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang

ICCV 2025 Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan, Yufa Zhou

AISTATS 2025 When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time? Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song

NeurIPSW 2024 A Tighter Complexity Analysis of SparseGPT Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song

ICMLW 2024 AdaInf: Adaptive Inference for Resource-Constrained Foundation Models Zhuoyan Xu, Khoi Duc Nguyen, Preeti Mukherjee, Somali Chaterji, Yingyu Liang, Yin Li

NeurIPSW 2024 Differential Privacy of Cross-Attention with Provable Guarantee Yingyu Liang, Zhenmei Shi, Zhao Song, Yufa Zhou

ICLRW 2024 Do Large Language Models Have Compositional Ability? an Investigation into Limitations and Scalability Zhuoyan Xu, Zhenmei Shi, Yingyu Liang

CPAL 2024 Domain Generalization via Nuclear Norm Regularization Zhenmei Shi, Yifei Ming, Ying Fan, Frederic Sala, Yingyu Liang

NeurIPSW 2024 Multi-Layer Transformers Gradient Can Be Approximated in Almost Linear Time Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Yufa Zhou

NeurIPSW 2024 Tensor Attention Training: Provably Efficient Learning of Higher-Order Transformers Yingyu Liang, Zhenmei Shi, Zhao Song, Yufa Zhou

ICLR 2024 Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, Yingyu Liang

ICML 2024 Two Heads Are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha

ICML 2024 Why Larger Language Models Do In-Context Learning Differently? Zhenmei Shi, Junyi Wei, Zhuoyan Xu, Yingyu Liang

ICLRW 2023 Improving Foundation Models for Few-Shot Learning via Multitask Finetuning Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Yin Li, Yingyu Liang

NeurIPS 2023 Provable Guarantees for Neural Networks via Gradient Feature Learning Zhenmei Shi, Junyi Wei, Yingyu Liang

ICML 2023 Stratified Adversarial Robustness with Rejection Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha

ICLR 2023 The Trade-Off Between Universality and Label Efficiency of Representations from Contrastive Learning Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

NeurIPS 2023 What Knowledge Gets Distilled in Knowledge Distillation? Utkarsh Ojha, Yuheng Li, Anirudh Sundara Rajan, Yingyu Liang, Yong Jae Lee

ICML 2023 When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis Yiyou Sun, Zhenmei Shi, Yingyu Liang, Yixuan Li

NeurIPSW 2023 Why Larger Language Models Do In-Context Learning Differently? Zhenmei Shi, Junyi Wei, Zhuoyan Xu, Yingyu Liang

ICLR 2022 A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features Zhenmei Shi, Junyi Wei, Yingyu Liang

TMLR 2022 Attentive Walk-Aggregating Graph Neural Networks Mehmet F Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang

NeurIPSW 2022 Best of Both Worlds: Towards Adversarial Robustness with Transduction and Rejection Nils Palumbo, Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang, Somesh Jha

WACV 2022 Deep Online Fused Video Stabilization Zhenmei Shi, Fuhao Shi, Wei-Sheng Lai, Chia-Kai Liang, Yingyu Liang

NeurIPSW 2022 Domain Generalization with Nuclear Norm Regularization Zhenmei Shi, Yifei Ming, Ying Fan, Frederic Sala, Yingyu Liang

ICMLW 2022 The Trade-Off Between Label Efficiency and Universality of Representations from Contrastive Learning Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

ICLR 2022 Towards Evaluating the Robustness of Neural Networks Learned by Transduction Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha

ECML-PKDD 2021 ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha

NeurIPS 2021 Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-Training Ensembles Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha

NeurIPS 2020 Functional Regularization for Representation Learning: A Unified Theoretical Perspective Siddhant Garg, Yingyu Liang

ICLR 2020 Gradients as Features for Deep Representation Learning Fangzhou Mu, Yingyu Liang, Yin Li

AISTATS 2020 Learning Entangled Single-Sample Distributions via Iterative Trimming Hui Yuan, Yingyu Liang

COLT 2020 Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model Yingyu Liang, Hui Yuan

AAAI 2020 Learning Relationships Between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis Zhongkai Sun, Prathusha Kameswara Sarma, William A. Sethares, Yingyu Liang

AISTATS 2020 Sketching Transformed Matrices with Applications to Natural Language Processing Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang

NeurIPS 2019 Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang

AAAI 2019 Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning Shengchao Liu, Yingyu Liang, Anthony Gitter

NeurIPS 2019 N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules Shengchao Liu, Mehmet F Demirel, Yingyu Liang

JMLR 2019 Non-Convex Matrix Completion and Related Problems via Strong Duality Maria-Florina Balcan, Yingyu Liang, Zhao Song, David P. Woodruff, Hongyang Zhang

AISTATS 2019 Recovery Guarantees for Quadratic Tensors with Sparse Observations Hongyang Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang

NeurIPS 2019 Robust Attribution Regularization Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha

COLT 2018 Learning Mixtures of Linear Regressions with Nearly Optimal Complexity Yuanzhi Li, Yingyu Liang

NeurIPS 2018 Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li, Yingyu Liang

ICLR 2017 A Simple but Tough-to-Beat Baseline for Sentence Embeddings Sanjeev Arora, Yingyu Liang, Tengyu Ma

ICML 2017 Differentially Private Clustering in High-Dimensional Euclidean Spaces Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang

AISTATS 2017 Diverse Neural Network Learns True Target Functions Bo Xie, Yingyu Liang, Le Song

ICML 2017 Generalization and Equilibrium in Generative Adversarial Nets (GANs) Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang

ICML 2017 Provable Alternating Gradient Descent for Non-Negative Matrix Factorization with Strong Correlations Yuanzhi Li, Yingyu Liang

JMLR 2017 Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks Nan Du, Yingyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song

NeurIPS 2016 Recovery Guarantee of Non-Negative Matrix Factorization via Alternating Updates Yuanzhi Li, Yingyu Liang, Andrej Risteski

ICML 2016 Recovery Guarantee of Weighted Low-Rank Approximation via Alternating Minimization Yuanzhi Li, Yingyu Liang, Andrej Risteski

NeurIPS 2015 Scale up Nonlinear Component Analysis with Doubly Stochastic Gradients Bo Xie, Yingyu Liang, Le Song

NeurIPS 2014 Improved Distributed Principal Component Analysis Yingyu Liang, Maria-Florina F Balcan, Vandana Kanchanapally, David Woodruff

ICML 2014 Influence Function Learning in Information Diffusion Networks Nan Du, Yingyu Liang, Maria Balcan, Le Song

NeurIPS 2014 Learning Time-Varying Coverage Functions Nan Du, Yingyu Liang, Maria-Florina F Balcan, Le Song

JMLR 2014 Robust Hierarchical Clustering Maria-Florina Balcan, Yingyu Liang, Pramod Gupta

NeurIPS 2014 Scalable Kernel Methods via Doubly Stochastic Gradients Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina F Balcan, Le Song

NeurIPS 2013 Distributed $k$-Means and $k$-Median Clustering on General Topologies Maria-Florina F Balcan, Steven Ehrlich, Yingyu Liang

ICML 2013 Efficient Semi-Supervised and Active Learning of Disjunctions Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang