We consider a variant of the classical notion of noise on the Boolean
hy...
We develop a novel connection between discrepancy minimization and (quan...
In recent times the cavity method, a statistical physics-inspired heuris...
Learning from data in the presence of outliers is a fundamental problem ...
We study efficient algorithms for linear regression and covariance estim...
Random constraint satisfaction problems (CSPs) such as random 3-SAT are
...
We propose a new hierarchy of semidefinite programming relaxations for
i...
The degree-4 Sum-of-Squares (SoS) SDP relaxation is a powerful algorithm...
In the list-decodable learning setup, an overwhelming majority (say a
1-...
Estimation is the computational task of recovering a hidden parameter x
...
The Generalized Lax Conjecture asks whether every hyperbolicity cone is ...
We study planted problems---finding hidden structures in random noisy
in...
We introduce a new technique for reducing the dimension of the ambient s...
We prove the following strong hardness result for learning: Given a
dist...