Neha S. Wadia

According to our database, Neha S. Wadia authored at least 6 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Gentle Introduction to Gradient-Based Optimization and Variational Inequalities for Machine Learning.

Neha S. Wadia, Yatin Dandi, Michael I. Jordan

CoRR, 2023

2022

Optimization: Stochastic thermodynamics, machine learning, and numerical algorithms

Neha S. Wadia

PhD thesis, 2022

2021

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses.

Charles G. Frye, James Simon, Neha S. Wadia, Andrew Ligeralde, Michael Robert DeWeese, Kristofer E. Bouchard

Neural Comput., 2021

Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization.

Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Whitening and second order optimization both destroy information about the dataset, and can make generalization impossible.

Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein

CoRR, 2020

2019

Numerically Recovering the Critical Points of a Deep Linear Autoencoder.

Charles G. Frye, Neha S. Wadia, Michael Robert DeWeese, Kristofer E. Bouchard

CoRR, 2019