Mishkin, Aaron

11 publications

ICLR 2025 Exploring the Loss Landscape of Regularized Neural Networks via Convex Duality Sungyoon Kim, Aaron Mishkin, Mert Pilanci

AISTATS 2025 Level Set Teleportation: An Optimization Perspective Aaron Mishkin, Alberto Bietti, Robert M. Gower

NeurIPS 2024 Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin, Ahmed Khaled, Yuanhao Wang, Aaron Defazio, Robert M. Gower

NeurIPSW 2023 A Novel Analysis of Gradient Descent Under Directional Smoothness Aaron Mishkin, Ahmed Khaled, Aaron Defazio, Robert M. Gower

NeurIPSW 2023 Level Set Teleportation: The Good, the Bad, and the Ugly Aaron Mishkin, Alberto Bietti, Robert M. Gower

ICML 2023 Optimal Sets and Solution Paths of ReLU Networks Aaron Mishkin, Mert Pilanci

NeurIPSW 2022 Fast Convergence of Greedy 2-Coordinate Updates for Optimizing with an Equality Constraint Amrutha Varshini Ramesh, Aaron Mishkin, Mark Schmidt

ICML 2022 Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions Aaron Mishkin, Arda Sahiner, Mert Pilanci

NeurIPSW 2022 The Solution Path of the Group Lasso Aaron Mishkin, Mert Pilanci

NeurIPS 2019 Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani, Aaron Mishkin, Issam Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

NeurIPS 2018 SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan