Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
The standard language for describing the asymptotic behavior of algorithms is theoretical computational complexity. We propose a method for describing the asymptotic behavior of p...
Simon Goldsmith, Alex Aiken, Daniel Shawcross Wilk...
Hardware compilation techniques which use highlevel programming languages to describe and synthesize hardware are gaining popularity. They are especially useful for reconfigurable...
In this paper, we show that for every constant 0 < < 1/2 and for every constant d 2, the minimum size of a depth d Boolean circuit that -approximates Majority function on n ...