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» Using Gaussian Processes to Optimize Expensive Functions
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IJCAI
2003
13 years 8 months ago
Gaussian Process Models of Spatial Aggregation Algorithms
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...
Naren Ramakrishnan, Christopher Bailey-Kellogg
JMLR
2008
159views more  JMLR 2008»
13 years 7 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
IROS
2007
IEEE
168views Robotics» more  IROS 2007»
14 years 1 months ago
Improving humanoid locomotive performance with learnt approximated dynamics via Gaussian processes for regression
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
CEC
2011
IEEE
12 years 7 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...
AIME
2009
Springer
14 years 3 days ago
Prediction of Mechanical Lung Parameters Using Gaussian Process Models
Abstract. Mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. We introduce a Machine Learning approach to predict the pressure-dependent...
Steven Ganzert, Stefan Kramer, Knut Möller, D...