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CIMCA
2008
IEEE
16 years 1 months ago
Tree Exploration for Bayesian RL Exploration
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Christos Dimitrakakis
JMLR
2012
13 years 9 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ICIP
2005
IEEE
16 years 8 months ago
Beyond interpolation: optimal reconstruction by quasi-interpolation
We investigate the use of quasi-interpolating approximation schemes, to construct an estimate of an unknown function from its given discrete samples. We show theoretically and wit...
Laurent Condat, Thierry Blu, Michael Unser
EMSOFT
2006
Springer
15 years 10 months ago
Compiler-assisted leakage energy optimization for clustered VLIW architectures
Miniaturization of devices and the ensuing decrease in the threshold voltage has led to a substantial increase in the leakage component of the total processor energy consumption. ...
Rahul Nagpal, Y. N. Srikant
WSC
2004
15 years 8 months ago
Global Likelihood Optimization Via the Cross-Entropy Method, with an Application to Mixture Models
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
Zdravko I. Botev, Dirk P. Kroese