Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum...
Rex A. Kerr, Thomas M. Bartol, Boris Kaminsky, Mar...
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Abstract. Recent advances in high-throughput experimental techniques have enabled the production of a wealth of protein interaction data, rich in both quantity and variety. While t...
Allister Bernard, David S. Vaughn, Alexander J. Ha...
We present a new method for user controlled morphing of two homeomorphic triangle meshes of arbitrary topology. In particular we focus on the problem of establishing a corresponde...
Aaron W. F. Lee, David P. Dobkin, Wim Sweldens, Pe...