We study the problem of learning causal representations from unknown, la...
Given a graph and an integer k, Densest k-Subgraph is the algorithmic
ta...
We develop new tools in the theory of nonlinear random matrices and appl...
Analyzing concentration of large random matrices is a common task in a w...
We investigate robustness properties of pre-trained neural models for
au...
We study the Sum of Squares (SoS) Hierarchy with a view towards combinat...
We prove identifiability of a broad class of deep latent variable models...
The Sum-of-Squares (SoS) hierarchy of semidefinite programs is a powerfu...
Greedy algorithms have long been a workhorse for learning graphical mode...
We study the problem of reconstructing a causal graphical model from dat...
In this paper, we construct general machinery for proving Sum-of-Squares...
The Sum-of-Squares (SoS) hierarchy is a semi-definite programming
meta-a...