We consider the problem of factorizing a structured 3-way tensor into it...
This paper describes an R package named flare, which implements a family...
Adversarial training is a popular method to give neural nets robustness
...
Generative Adversarial Imitation Learning (GAIL) is a powerful and pract...
Our interest lies in the recoverability properties of compressed tensors...
Recurrent Neural Networks (RNNs) have been widely applied to sequential ...
The adaptive momentum method (AdaMM), which uses past gradients to updat...
We consider the dictionary learning problem, where the aim is to model t...
Localizing targets of interest in a given hyperspectral (HS) image has
a...
We consider the task of localizing targets of interest in a hyperspectra...
We consider the decomposition of a data matrix assumed to be a superposi...
We analyze the decomposition of a data matrix, assumed to be a superposi...
Our paper proposes a generalization error bound for a general family of ...
We study constrained nonconvex optimization problems in machine learning...
Convolution as inner product has been the founding basis of convolutiona...
In this paper, we make an important step towards the black-box machine
t...
We study the least squares regression problem _Θ∈S_ D,RAΘ-b_2, where
S_...
We propose a DC proximal Newton algorithm for solving nonconvex regulari...
We propose a general theory for studying the geometry of nonconvex objec...
The cyclic block coordinate descent-type (CBCD-type) methods, which perf...
Many statistical machine learning techniques sacrifice convenient
comput...
We propose a stochastic variance reduced optimization algorithm for solv...
This paper examines the problem of locating outlier columns in a large,
...