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Aaron Mishkin
Publication Activity (10 Years)
Years Active: 2018-2023
Publications (10 Years): 10
Top Topics
Convergence Rate
Convex Optimization
Stochastic Gradient
Global Convergence
Top Venues
CoRR
ICML
NeurIPS
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Publications
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Aaron Mishkin
,
Mert Pilanci
Optimal Sets and Solution Paths of ReLU Networks.
CoRR
(2023)
Amrutha Varshini Ramesh
,
Aaron Mishkin
,
Mark Schmidt
,
Yihan Zhou
,
Jonathan Wilder Lavington
,
Jennifer She
Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm.
CoRR
(2023)
Aaron Mishkin
,
Mert Pilanci
Optimal Sets and Solution Paths of ReLU Networks.
ICML
(2023)
Aaron Mishkin
,
Arda Sahiner
,
Mert Pilanci
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions.
ICML
(2022)
Aaron Mishkin
,
Arda Sahiner
,
Mert Pilanci
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions.
CoRR
(2022)
Sharan Vaswani
,
Reza Babanezhad
,
Jose Gallego
,
Aaron Mishkin
,
Simon Lacoste-Julien
,
Nicolas Le Roux
To Each Optimizer a Norm, To Each Norm its Generalization.
CoRR
(2020)
Sharan Vaswani
,
Aaron Mishkin
,
Issam H. Laradji
,
Mark Schmidt
,
Gauthier Gidel
,
Simon Lacoste-Julien
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.
NeurIPS
(2019)
Sharan Vaswani
,
Aaron Mishkin
,
Issam H. Laradji
,
Mark Schmidt
,
Gauthier Gidel
,
Simon Lacoste-Julien
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.
CoRR
(2019)
Aaron Mishkin
,
Frederik Kunstner
,
Didrik Nielsen
,
Mark Schmidt
,
Mohammad Emtiyaz Khan
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient.
NeurIPS
(2018)
Aaron Mishkin
,
Frederik Kunstner
,
Didrik Nielsen
,
Mark Schmidt
,
Mohammad Emtiyaz Khan
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient.
CoRR
(2018)