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NIPS
2001
15 years 16 days ago
Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field
Reaching movements require the brain to generate motor commands that rely on an internal model of the task's dynamics. Here we consider the errors that subjects make early in...
O. Donchin, Reza Shadmehr
ICML
2010
IEEE
15 years 6 days ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...
HPDC
2008
IEEE
14 years 11 months ago
Code coverage, performance approximation and automatic recognition of idioms in scientific applications
Basic data flow patterns which we call idioms, such as stream, transpose, reduction, random access and stencil, are common in scientific numerical applications. We hypothesize tha...
Jiahua He, Allan Snavely, Rob F. Van der Wijngaart...
CORR
2011
Springer
192views Education» more  CORR 2011»
14 years 6 months ago
On cooperative patrolling: optimal trajectories, complexity analysis, and approximation algorithms
—The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal prop...
Fabio Pasqualetti, Antonio Franchi, Francesco Bull...
CVPR
2007
IEEE
16 years 1 months ago
Fast, Approximately Optimal Solutions for Single and Dynamic MRFs
A new efficient MRF optimization algorithm, called FastPD, is proposed, which generalizes -expansion. One of its main advantages is that it offers a substantial speedup over that ...
Nikos Komodakis, Georgios Tziritas, Nikos Paragios