Differentially private synthetic data provide a powerful mechanism to en...
We present a highly effective algorithmic approach for generating
ε-diff...
We show how randomized rounding based on Grothendieck's identity can be ...
High-dimensional multimodal data arises in many scientific fields. The
i...
Differential privacy is a mathematical concept that provides an
informat...
Attention plays a fundamental role in both natural and artificial
intell...
In a world where artificial intelligence and data science become omnipre...
Privacy-preserving data analysis is emerging as a challenging problem wi...
The protection of private information is of vital importance in data-dri...
Motivated by biological considerations, we study sparse neural maps from...
Overwhelming theoretical and empirical evidence shows that mildly
overpa...
In recent literature, a general two step procedure has been formulated f...
A long standing open problem in the theory of neural networks is the
dev...
Random matrix theory has played an important role in recent work on
stat...
The problem of Non-Gaussian Component Analysis (NGCA) is about finding a...
Community detection is one of the fundamental problems of network analys...