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JMLR
2006
136views more  JMLR 2006»
13 years 5 months ago
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
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...
Tonatiuh Peña Centeno, Neil D. Lawrence
JMLR
2010
135views more  JMLR 2010»
13 years 4 months ago
Bundle Methods for Regularized Risk Minimization
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...
CEC
2011
IEEE
12 years 5 months ago
Curiosity-driven optimization
— 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...
RSS
2007
176views Robotics» more  RSS 2007»
13 years 7 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
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...
NECO
2011
13 years 21 days ago
Least Squares Estimation Without Priors or Supervision
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...
Martin Raphan, Eero P. Simoncelli