We study the spectral norm of matrices M that can be factored as M = BA, where A is a random matrix with independent mean zero entries and B is a fixed matrix. Under the (4 + )-th ...
We present a deterministic, log-space algorithm that solves st-connectivity in undirected graphs. The previous bound on the space complexity of undirected st-connectivity was log4...
Our main result is a reduction from worst-case lattice problems such as GAPSVP and SIVP to a certain learning problem. This learning problem is a natural extension of the `learnin...
We present a new constant round protocol for non-malleable zero-knowledge. Using this protocol as a subroutine, we obtain a new constant-round protocol for non-malleable commitmen...
In this paper, we study the problem of learning phylogenies and hidden Markov models. We call the Markov model nonsingular if all transtion matrices have determinants bounded away...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...