— A computation-aware motion estimation algorithm is proposed in this paper. Its goal is to find the best block matching results in a computation-limited and computation-variant...
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
We present an "adaptive multi-start" genetic algorithm for the Euclidean traveling salesman problem that uses a population of tours locally optimized by the Lin-Kernigha...
Dan Bonachea, Eugene Ingerman, Joshua Levy, Scott ...
In this paper we look at combining and compressing a set of workflows, such that computation can be minimized. In this context, we look at two novel theoretical problems with appl...
Dhrubajyoti Saha, Abhishek Samanta, Smruti R. Sara...