Ali Jadbabaie

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning ALT 2026 Fast Tensor Completion via Approximate Richardson Iteration ICML 2025 On the Emergence of Position Bias in Transformers ICML 2025 Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs ICLR 2025 The Pitfalls of Imitation Learning when Actions are Continuous COLT 2025 How to Escape Sharp Minima with Random Perturbations ICML 2024 Linear attention is (maybe) all you need (to understand Transformer optimization) ICLR 2024 On the Role of Attention Masks and LayerNorm in Transformers NeurIPS 2024 A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks ICLR 2023 Convergence of Adam Under Relaxed Assumptions NeurIPS 2023 Convex and Non-convex Optimization Under Generalized Smoothness NeurIPS 2023 Demystifying Oversmoothing in Attention-Based Graph Neural Networks NeurIPS 2023 Model Predictive Control via On-Policy Imitation Learning L4DC 2023 Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior NeurIPS 2023 Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity ICML 2022 Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective ICML 2022 On Convergence of Gradient Descent Ascent: A Tight Local Analysis ICML 2022 Time Varying Regression with Hidden Linear Dynamics L4DC 2022 Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization NeurIPS 2021 Open Problem: Can Single-Shuffle SGD be Better than Reshuffling SGD and GD? COLT 2021 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions ICML 2020 Estimation of Skill Distribution from a Tournament NeurIPS 2020 FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization AISTATS 2020 Robust Federated Learning: The Case of Affine Distribution Shifts NeurIPS 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity ICLR 2020 Are deep ResNets provably better than linear predictors? NeurIPS 2019 Efficiently testing local optimality and escaping saddles for ReLU networks ICLR 2019 Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods AISTATS 2019 Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard COLT 2019 Small nonlinearities in activation functions create bad local minima in neural networks ICLR 2019 Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity NeurIPS 2019 Direct Runge-Kutta Discretization Achieves Acceleration NeurIPS 2018 Escaping Saddle Points in Constrained Optimization NeurIPS 2018 Global Optimality Conditions for Deep Neural Networks ICLR 2018 Online Optimization : Competing with Dynamic Comparators AISTATS 2015 Online Learning of Dynamic Parameters in Social Networks NeurIPS 2013 Bearing-Only Control Laws For Balanced Circular Formations of Ground Robots RSS 2008 Vision-based Distributed Coordination and Flocking of Multi-agent Systems RSS 2005