This article aims at making iterative optimization practical and usable by speeding up the evaluation of a large range of optimizations. Instead of using a full run to evaluate a s...
Grigori Fursin, Albert Cohen, Michael F. P. O'Boyl...
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
We study the regret of an online learner playing a multi-round game in a Banach space B against an adversary that plays a convex function at each round. We characterize the minima...