77 citations · 97 across the 9 of their papers we have counts for
10 papers
Provably Accurate Double-Sparse Coding
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
Sparse coding is a crucial subroutine in algorithms for various signal processing, deep learning, and other machine learning applications. The central goal is to learn an overcompl…
Fast Low-Rank Matrix Estimation without the Condition Number
Mohammadreza Soltani, Chinmay Hegde
In this paper, we study the general problem of optimizing a convex function over the set of matrices, subject to rank constraints on . However, existing firs…
A Forward-Backward Approach for Visualizing Information Flow in Deep Networks
Aditya Balu, Thanh V. Nguyen, Apurva Kokate +2
We introduce a new, systematic framework for visualizing information flow in deep networks. Specifically, given any trained deep convolutional network model and a given test image,…
Reconstruction from Periodic Nonlinearities, With Applications to HDR Imaging
Viraj Shah, Mohammadreza Soltani, Chinmay Hegde
We consider the problem of reconstructing signals and images from periodic nonlinearities. For such problems, we design a measurement scheme that supports efficient reconstruction;…
Demixing Structured Superposition Signals from Periodic and Aperiodic Nonlinear Observations
Mohammadreza Soltani, Chinmay Hegde
We consider the demixing problem of two (or more) structured high-dimensional vectors from a limited number of nonlinear observations where this nonlinearity is due to either a per…
Fast Algorithms for Learning Latent Variables in Graphical Models
Mohammadreza Soltani, Chinmay Hegde
We study the problem of learning latent variables in Gaussian graphical models. Existing methods for this problem assume that the precision matrix of the observed variables is the…