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 ...
We study a simple Markov chain, known as the Glauber dynamics, for randomly sampling (proper) k-colorings of an input graph G on n vertices with maximum degree ∆ and girth g. We...
We combine three threads of research on approximate dynamic programming: sparse random sampling of states, value function and policy approximation using local models, and using lo...
This paper describes and evaluates an efficient technique that allows the fast generation of 3D triangular meshes from range images avoiding optimization procedures. Such a tool ...
A major bottleneck in implementing sampling as a primitive relational operation is the ine ciency ofsampling the output of a query. It is not even known whether it is possible to ...
Surajit Chaudhuri, Rajeev Motwani, Vivek R. Narasa...