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NIPS
2001
13 years 9 months 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
CORR
2011
Springer
215views Education» more  CORR 2011»
12 years 11 months ago
Lasserre Hierarchy, Higher Eigenvalues, and Approximation Schemes for Quadratic Integer Programming with PSD Objectives
We present an approximation scheme for optimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. Thi...
Venkatesan Guruswami, Ali Kemal Sinop
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
ATAL
2010
Springer
13 years 8 months ago
Asynchronous algorithms for approximate distributed constraint optimization with quality bounds
Distributed Constraint Optimization (DCOP) is a popular framework for cooperative multi-agent decision making. DCOP is NPhard, so an important line of work focuses on developing f...
Christopher Kiekintveld, Zhengyu Yin, Atul Kumar, ...
COMPUTING
2008
174views more  COMPUTING 2008»
13 years 7 months ago
Multilevel algorithms for Rannacher-Turek finite element approximation of 3D elliptic problems
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
Ivan Georgiev, Johannes Kraus, Svetozar Margenov