In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
— The principle of artificial curiosity directs active exploration towards the most informative or most interesting data. We show its usefulness for global black box optimizatio...
Tom Schaul, Yi Sun, Daan Wierstra, Faustino J. Gom...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...