Jadbabaie, Ali

40 publications

ICML 2025 Fast Tensor Completion via Approximate Richardson Iteration Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook, Ali Jadbabaie

NeurIPS 2025 Is Your Diffusion Model Actually Denoising? Daniel Pfrommer, Zehao Dou, Christopher Scarvelis, Max Simchowitz, Ali Jadbabaie

ICML 2025 On the Emergence of Position Bias in Transformers Xinyi Wu, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLRW 2025 On the Emergence of Position Bias in Transformers Xinyi Wu, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLR 2025 Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs Michael Scholkemper, Xinyi Wu, Ali Jadbabaie, Michael T Schaub

COLT 2025 The Pitfalls of Imitation Learning When Actions Are Continuous Max Simchowitz, Daniel Pfrommer, Ali Jadbabaie

ICML 2024 How to Escape Sharp Minima with Random Perturbations Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra

ICLR 2024 Linear Attention Is (maybe) All You Need (to Understand Transformer Optimization) Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra

NeurIPS 2024 On the Role of Attention Masks and LayerNorm in Transformers Xinyi Wu, Amir Ajorlou, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLR 2023 A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie

NeurIPS 2023 Convergence of Adam Under Relaxed Assumptions Haochuan Li, Alexander Rakhlin, Ali Jadbabaie

NeurIPS 2023 Convex and Non-Convex Optimization Under Generalized Smoothness Haochuan Li, Jian Qian, Yi Tian, Alexander Rakhlin, Ali Jadbabaie

NeurIPS 2023 Demystifying Oversmoothing in Attention-Based Graph Neural Networks Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie

NeurIPSW 2023 Linear Attention Is (maybe) All You Need (to Understand Transformer Optimization) Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra

L4DC 2023 Model Predictive Control via On-Policy Imitation Learning Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie

NeurIPS 2023 Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake

ICML 2022 Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

ICML 2022 Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie

ICML 2022 On Convergence of Gradient Descent Ascent: A Tight Local Analysis Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie

L4DC 2022 Time Varying Regression with Hidden Linear Dynamics Horia Mania, Ali Jadbabaie, Devavrat Shah, Suvrit Sra

NeurIPS 2021 Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie

COLT 2021 Open Problem: Can Single-Shuffle SGD Be Better than Reshuffling SGD and GD? Chulhee Yun, Suvrit Sra, Ali Jadbabaie

L4DC 2021 Preface Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger

ICML 2020 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie

NeurIPS 2020 Estimation of Skill Distribution from a Tournament Ali Jadbabaie, Anuran Makur, Devavrat Shah

AISTATS 2020 FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani

L4DC 2020 Preface Alexandre M. Bayen, Ali Jadbabaie, George Pappas, Pablo A. Parrilo, Benjamin Recht, Claire Tomlin, Melanie Zeilinger

NeurIPS 2020 Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie

ICLR 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie

NeurIPS 2019 Are Deep ResNets Provably Better than Linear Predictors? Chulhee Yun, Suvrit Sra, Ali Jadbabaie

AISTATS 2019 Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods Aryan Mokhtari, Asuman Ozdaglar, Ali Jadbabaie

ICLR 2019 Efficiently Testing Local Optimality and Escaping Saddles for ReLU Networks Chulhee Yun, Suvrit Sra, Ali Jadbabaie

COLT 2019 Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard Jan Hązła, Ali Jadbabaie, Elchanan Mossel, M. Amin Rahimian

ICLR 2019 Small Nonlinearities in Activation Functions Create Bad Local Minima in Neural Networks Chulhee Yun, Suvrit Sra, Ali Jadbabaie

NeurIPS 2019 Small ReLU Networks Are Powerful Memorizers: A Tight Analysis of Memorization Capacity Chulhee Yun, Suvrit Sra, Ali Jadbabaie

NeurIPS 2018 Direct Runge-Kutta Discretization Achieves Acceleration Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie

NeurIPS 2018 Escaping Saddle Points in Constrained Optimization Aryan Mokhtari, Asuman Ozdaglar, Ali Jadbabaie

ICLR 2018 Global Optimality Conditions for Deep Neural Networks Chulhee Yun, Suvrit Sra, Ali Jadbabaie

AISTATS 2015 Online Optimization : Competing with Dynamic Comparators Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan

NeurIPS 2013 Online Learning of Dynamic Parameters in Social Networks Shahin Shahrampour, Sasha Rakhlin, Ali Jadbabaie