research
∙
06/30/2020
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
We consider the problem of factorizing a structured 3-way tensor into it...
share
research
∙
06/27/2020
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R
This paper describes an R package named flare, which implements a family...
research
∙
02/16/2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
Adversarial training is a popular method to give neural nets robustness ...
research
∙
01/09/2020
On Computation and Generalization of Generative Adversarial Imitation Learning
Generative Adversarial Imitation Learning (GAIL) is a powerful and pract...
research
∙
01/08/2020
On Recoverability of Randomly Compressed Tensors with Low CP Rank
Our interest lies in the recoverability properties of compressed tensors...
research
∙
10/28/2019
On Generalization Bounds of a Family of Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been widely applied to sequential ...
research
∙
10/15/2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
The adaptive momentum method (AdaMM), which uses past gradients to updat...
research
∙
02/28/2019
NOODL: Provable Online Dictionary Learning and Sparse Coding
We consider the dictionary learning problem, where the aim is to model t...
research
∙
02/26/2019
Target-based Hyperspectral Demixing via Generalized Robust PCA
Localizing targets of interest in a given hyperspectral (HS) image has a...
research
∙
02/26/2019
A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing
We consider the task of localizing targets of interest in a hyperspectra...
research
∙
02/21/2019
A Dictionary-Based Generalization of Robust PCA Part I: Study of Theoretical Properties
We consider the decomposition of a data matrix assumed to be a superposi...
research
∙
02/21/2019
A Dictionary Based Generalization of Robust PCA
We analyze the decomposition of a data matrix, assumed to be a superposi...
research
∙
06/13/2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond
Our paper proposes a generalization error bound for a general family of ...
research
∙
06/13/2018
On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization
We study constrained nonconvex optimization problems in machine learning...
research
∙
11/08/2017
Deep Hyperspherical Learning
Convolution as inner product has been the founding basis of convolutiona...
research
∙
10/21/2017
Towards Black-box Iterative Machine Teaching
In this paper, we make an important step towards the black-box machine t...
research
∙
09/20/2017
Near Optimal Sketching of Low-Rank Tensor Regression
We study the least squares regression problem _Θ∈S_ D,RAΘ-b_2, where S_...
research
∙
06/19/2017
On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions
We propose a DC proximal Newton algorithm for solving nonconvex regulari...
research
∙
12/29/2016
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization
We propose a general theory for studying the geometry of nonconvex objec...
research
∙
07/10/2016
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
The cyclic block coordinate descent-type (CBCD-type) methods, which perf...
research
∙
05/25/2016
A First Order Free Lunch for SQRT-Lasso
Many statistical machine learning techniques sacrifice convenient comput...
research
∙
05/09/2016
Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction
We propose a stochastic variance reduced optimization algorithm for solv...
research
∙
07/01/2014
