Abstract. We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase t...
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
An affine disperser over Fn 2 for sources of dimension d is a function f : Fn 2 F2 such that for any affine space S Fn 2 of dimension at least d, we have {f(s) : s S} = F2. Aff...
We describe a unified framework for random interpretation that generalizes previous randomized intraprocedural analyses, and also extends naturally to efficient interprocedural an...
We provide a deterministic algorithm that constructs small point sets exhibiting a low star discrepancy. The algorithm is based on recent results on randomized roundings respectin...