We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability m...
Robert Krauthgamer, James R. Lee, Manor Mendel, As...
We investigate the feasibility of a variety of cryptographic tasks with imperfect randomness. The kind of imperfect randomness we consider are entropy sources, such as those consi...
Yevgeniy Dodis, Shien Jin Ong, Manoj Prabhakaran, ...
We study the learning models defined in [AKST97]: Learning with equivalence and limited membership queries and learning with equivalence and malicious membership queries. We show ...
We study a simple Markov chain, known as the Glauber dynamics, for generating a random k-coloring of a n-vertex graph with maximum degree . We prove that, for every > 0, the d...
Martin E. Dyer, Alan M. Frieze, Thomas P. Hayes, E...