research
∙
01/29/2023
Implicit Regularization for Group Sparsity
We study the implicit regularization of gradient descent towards structu...
share
research
∙
08/12/2021
Implicit Sparse Regularization: The Impact of Depth and Early Stopping
In this paper, we study the implicit bias of gradient descent for sparse...
research
∙
02/25/2021
Provable Compressed Sensing with Generative Priors via Langevin Dynamics
Deep generative models have emerged as a powerful class of priors for si...
research
∙
08/24/2020
Active learning of deep surrogates for PDEs: Application to metasurface design
Surrogate models for partial-differential equations are widely used in t...
research
∙
05/07/2020
Learning Robust Models for e-Commerce Product Search
Showing items that do not match search query intent degrades customer ex...
research
∙
11/27/2019
Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis
A remarkable recent discovery in machine learning has been that deep neu...
research
∙
06/02/2018
Autoencoders Learn Generative Linear Models
Recent progress in learning theory has led to the emergence of provable ...
research
∙
04/24/2018
On Learning Sparsely Used Dictionaries from Incomplete Samples
Most existing algorithms for dictionary learning assume that all entries...
research
∙
11/16/2017
A Forward-Backward Approach for Visualizing Information Flow in Deep Networks
We introduce a new, systematic framework for visualizing information flo...
research
∙
11/09/2017
