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» Learning Nonlinear Dynamic Models from Non-sequenced Data
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ICML
2000
IEEE
14 years 8 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
IEEEICCI
2009
IEEE
13 years 5 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
IROS
2008
IEEE
191views Robotics» more  IROS 2008»
14 years 1 months ago
Local Gaussian process regression for real-time model-based robot control
— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
Duy Nguyen-Tuong, Jan Peters
SIGMETRICS
2003
ACM
115views Hardware» more  SIGMETRICS 2003»
14 years 24 days ago
Dynamic resource allocation for shared data centers using online measurements
Since web workloads are known to vary dynamically with time, in this paper, we argue that dynamic resource allocation techniques are necessary to provide guarantees to web applicat...
Abhishek Chandra, Weibo Gong, Prashant J. Shenoy
DSP
2007
13 years 7 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...