We propose an efficient deep learning method for single image defocus
de...
Given a traversal algorithm, cover time is the expected number of steps
...
Learning from noisy labels is an important and long-standing problem in
...
This paper investigates the spectral norm version of the column subset
s...
A promising paradigm for offline reinforcement learning (RL) is to const...
Affine phase retrieval is the problem of recovering signals from the
mag...
Fourier phase retrieval, which seeks to reconstruct a signal from its Fo...
Unsupervised video domain adaptation is a practical yet challenging task...
The recovery of a signal from the intensity measurements with some entri...
The aim of this paper is to study the performance of the amplitude-based...
In this paper, we propose two new definitions of local differential priv...
In this paper, we focus on the nonlinear least squares:
_𝐱∈ℍ^d |A𝐱|-𝐛 wh...
The aim of sparse phase retrieval is to recover a k-sparse signal
𝐱_0∈ℂ^...
Graph sparsification is to approximate an arbitrary graph by a sparse gr...
The aim of noisy phase retrieval is to estimate a signal x_0∈C^d from m ...
We study the stable recovery of complex k-sparse signals from as few
pha...
The aim of generalized phase retrieval is to recover x∈F^d from the quad...
Suppose that y= Ax_0+η where x_0∈R^d is the target signal and η∈R^m is a...
Subset selection for matrices is the task of extracting a column sub-mat...
In this paper, we develop a new computational approach which is based on...
In this paper, we study the restricted isometry property of partial rand...
We consider the rank minimization problem from quadratic measurements, i...
In this paper, we consider the generalized phase retrieval from affine
m...
In this paper, we consider the generalized phase retrieval from affine
m...
We study the stochastic Riemannian gradient algorithm for matrix
eigen-d...
Spline wavelet tight frames of Ron-Shen have been used widely in frame b...
In this paper, several discrete schemes for Gaussian curvature are surve...