Abstract. In recent years, probabilistic analyses of algorithms have received increasing attention. Despite results on the average-case complexity and smoothed complexity of exact ...
We consider a model of learning Boolean functions from examples generated by a uniform random walk on {0, 1}n . We give a polynomial time algorithm for learning decision trees and...
Nader H. Bshouty, Elchanan Mossel, Ryan O'Donnell,...
Complex virtual environments can be simulated with physical or procedural motion. Physical motion is more realistic, but requires the integration of an ordinary differential equat...
We present a new technique called balanced randomized tree splitting. It is useful in constructing unknown trees recursively. By applying it we obtain two new results on efficient ...
Abstract. We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase t...