The Gibbs Sampler is a general method for sampling high-dimensional
dist...
Can linear systems be solved faster than matrix multiplication? While th...
We show that the popular k-means clustering algorithm (Lloyd's heuristic...
We introduce and study a matrix decomposition that is a common generaliz...
We give an efficient algorithm for robustly clustering of a mixture of
a...
Motivated by the Dikin walk, we develop aspects of an interior-point the...
Password users frequently employ passwords that are too simple, or they ...
We model "fair" dimensionality reduction as an optimization problem. A
c...
We investigate whether the standard dimensionality reduction technique o...
We analyze linear independence of rank one tensors produced by tensor po...
We analyze Gradient Descent applied to learning a bounded target functio...
Reusing passwords across multiple websites is a common practice that
com...
A wide variety of complex networks (social, biological, information etc....
The stunning empirical successes of neural networks currently lack rigor...
What can humans compute in their heads? We are thinking of a variety of
...
We consider the following general hidden hubs model: an n × n random
mat...
We consider the problem of estimating the mean and covariance of a
distr...
We study Boolean functions of an arbitrary number of input variables tha...
Fourier PCA is Principal Component Analysis of a matrix obtained from hi...