We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
In many different application areas, e.g. space observation systems or engineering systems of world-wide operating companies, there is a need for an efficient distributed intersect...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
In this paper, we propose an approximation of the relative phase probability function (RP pdf) and use it to find a non-iterative estimator for the concentration parameter of the...
A fundamental problem in data management is to draw a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With large, streamin...
Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang