The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...
Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automa...
Branislav Kveton, Milos Hauskrecht, Carlos Guestri...
Due to recent breakthroughs in hash functions cryptanalysis, some new hash schemes have been proposed. GRINDAHL is a novel hash function, designed by Knudsen, Rechberger and Thomse...
We show that linear probing requires 5-independent hash functions for expected constant-time performance, matching an upper bound of [Pagh et al. STOC’07]. For (1 + ε)-approxima...
Scientists need customizable tools to help them with discovery. We present an adjustable heuristic function for scientific discovery. This function may be considered in either a Mi...