We consider derivative free methods based on sampling approaches for nonlinear optimization problems where derivatives of the objective function are not available and cannot be dir...
A merger is a probabilistic procedure which extracts the randomness out of any (arbitrarily correlated) set of random variables, as long as one of them is uniform. Our main result...
We study local, distributed algorithms for the capacitated minimum dominating set (CapMDS) problem, which arises in various distributed network applications. Given a network graph...
In sequential, deterministic, non-redundant search the algorithm permutes a test function to obtain the search result. The mapping from test functions to search results is a one-to...
A classical learning problem in Inductive Inference consists of identifying each function of a given class of recursive functions from a finite number of its output values. Unifor...