We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
This paper presents an image processing framework for assessing molecular activity changes from fluorescent data in time-dependent geometries. The aim of our work is to provide th...
Kostas Marias, Stelios C. Orphanoudakis, Jorge Rip...
This paper is concerned with the problem of computing the image of a set by a polynomial function. Such image computations constitute a crucial component in typical tools for set-b...
Directed test program-based verification or formal verification methods are usually quite ineffective on large cachecoherent, non-uniform memory access (CC-NUMA) multiprocessors b...
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio