In this paper, we investigate the impact of imbalanced data on the
conve...
In the past several decades, the world's economy has become increasingly...
We formulate the problem of performing optimal data compression under th...
In this paper, we consider the problem of designing optimal pooling matr...
We consider a novel method to increase the reliability of COVID-19 virus...
We consider the theoretical problem of designing an optimal adversarial
...
Coronavirus disease 2019 (COVID-19) is an ongoing pandemic infectious di...
Recent works have demonstrated the existence of adversarial examples
ta...
Deep-learning based classification algorithms have been shown to be
susc...
Removing undesired reflections from images taken through the glass is of...
We present a simple hypothesis about a compression property of artificia...
Donald Trump was lagging behind in nearly all opinion polls leading up t...
This paper considers the problem of recovering signals from compressed
m...
In this paper, we solve the sum mean-squared error (MSE)-optimal 1-bit
q...
Low-rank matrix recovery has found many applications in science and
engi...
The maximum-likelihood (ML) decoder for symbol detection in large
multip...
Characterizing the phase transitions of convex optimizations in recoveri...
This paper explores robust recovery of a superposition of R distinct
com...
Recent research in off-the-grid compressed sensing (CS) has demonstrated...
In compressed sensing problems, ℓ_1 minimization or Basis Pursuit was
kn...
In this paper, we propose new efficient algorithms to verify the null sp...
In this paper, we consider using total variation minimization to recover...
Minimizing the rank of a matrix subject to constraints is a challenging
...