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Fast convex optimization for two-layer relu networks: Equivalent model classes and cone decompositions
We develop fast algorithms and robust software for convex optimization of two-layer neural
networks with ReLU activation functions. Our work leverages a convex re-formulation of the …
networks with ReLU activation functions. Our work leverages a convex re-formulation of the …
Evaluation methodology for deep learning imputation models
There is growing interest in imputing missing data in tabular datasets using deep learning.
Existing deep learning–based imputation models have been commonly evaluated using root …
Existing deep learning–based imputation models have been commonly evaluated using root …
[PDF][PDF] Globally convergent derivative-free methods in nonconvex optimization with and without noise
PD Khanh, BS Mordukhovich, DB Tran - 2024 - optimization-online.org
This paper addresses the study of nonconvex derivative-free optimization problems, where
only information of either smooth objective functions or their noisy approximations is …
only information of either smooth objective functions or their noisy approximations is …
Interpolation, growth conditions, and stochastic gradient descent
A Mishkin - 2020 - open.library.ubc.ca
Current machine learning practice requires solving huge-scale empirical risk minimization
problems quickly and robustly. These problems are often highly under-determined and …
problems quickly and robustly. These problems are often highly under-determined and …
Glocal Smoothness: Line Search can really help!
Iteration complexities are bounds on the number of iterations of an algorithm. Iteration
complexities for first-order numerical optimization algorithms are typically stated in terms of a …
complexities for first-order numerical optimization algorithms are typically stated in terms of a …
Evaluation methodology for deep learning imputation models
R Samavi, O Boursalie, TE Doyle - rshare.library.torontomu.ca
There is growing interest in imputing missing data in tabular datasets using deep learning.
Existing deep learning–based imputation models have been commonly evaluated using root …
Existing deep learning–based imputation models have been commonly evaluated using root …