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CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 2 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
132
Voted
IROS
2007
IEEE
168views Robotics» more  IROS 2007»
15 years 9 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...
129
Voted
AMAI
2006
Springer
15 years 2 months ago
Symmetric approximate linear programming for factored MDPs with application to constrained problems
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
Dmitri A. Dolgov, Edmund H. Durfee
102
Voted
ICC
2007
IEEE
15 years 9 months ago
On the Accuracy of the Gaussian Approximation for Performance Estimation in Optical DPSK Systems with In-Band Crosstalk
The Gaussian approximation is known to be quite accurate for estimating the system performance of an optically pre–amplified on-off keying (OOK) system in the presence of multipl...
Luís G. C. Cancela, João J. O. Pires
ICIP
2007
IEEE
15 years 9 months ago
Locally Competitive Algorithms for Sparse Approximation
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficie...
Christopher J. Rozell, Don H. Johnson, Richard G. ...