Aaron Mishkin

According to our database1, Aaron Mishkin authored at least 10 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation.
CoRR, 2024

Directional Smoothness and Gradient Methods: Convergence and Adaptivity.
CoRR, 2024

Level Set Teleportation: An Optimization Perspective.
CoRR, 2024

A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features.
CoRR, 2024

2023
Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm.
CoRR, 2023

Optimal Sets and Solution Paths of ReLU Networks.
Proceedings of the International Conference on Machine Learning, 2023

2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions.
Proceedings of the International Conference on Machine Learning, 2022

2020
To Each Optimizer a Norm, To Each Norm its Generalization.
CoRR, 2020

2019
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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