30 citations · 110 across the 21 of their papers we have counts for
6 papers · 1 filter
Implicit Regularization for Group Sparsity
Jiangyuan Li, Thanh V. Nguyen, Chinmay Hegde +1
We study the implicit regularization of gradient descent towards structured sparsity via a novel neural reparameterization, which we call a diagonally grouped linear neural network…
Median Matrix Completion: from Embarrassment to Optimality
Weidong Liu, Xiaojun Mao, Raymond K. W. Wong
In this paper, we consider matrix completion with absolute deviation loss and obtain an estimator of the median matrix. Despite several appealing properties of median, the non-smoo…
Matrix Completion under Low-Rank Missing Mechanism
Xiaojun Mao, Raymond K. W. Wong, Song Xi Chen
Matrix completion is a modern missing data problem where both the missing structure and the underlying parameter are high dimensional. Although missing structure is a key component…
Autoencoders Learn Generative Linear Models
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
We provide a series of results for unsupervised learning with autoencoders. Specifically, we study shallow two-layer autoencoder architectures with shared weights. We focus on thre…
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…
Matrix Completion with Noisy Entries and Outliers
Raymond K. W. Wong, Thomas C. M. Lee
This paper considers the problem of matrix completion when the observed entries are noisy and contain outliers. It begins with introducing a new optimization criterion for which th…