With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
We consider a fundamental problem in data structures, static predecessor searching: Given a subset S of size n from the universe [m], store S so that queries of the form “What i...
Many machine learning algorithms require the summation of Gaussian kernel
functions, an expensive operation if implemented straightforwardly. Several methods
have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithm...
Romeil Sandhu, Samuel Dambreville, Allen Tannenbau...