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ICPR
2000
IEEE
14 years 10 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes
VTC
2008
IEEE
178views Communications» more  VTC 2008»
14 years 3 months ago
Downlink Linear Max-MSE Transceiver Design for Multiuser MIMO Systems Via Dual Decomposition
—This paper addresses the problem of joint linear transceiver design in the downlink of multiuser MIMO systems. We define the performance criterion as minimizing the maximal mea...
Yuanzhang Xiao, Shidong Zhou
LSSC
2007
Springer
14 years 3 months ago
Application of Hierarchical Decomposition: Preconditioners and Error Estimates for Conforming and Nonconforming FEM
A successive refinement of a finite element grid provides a sequence of nested grids and hierarchy of nested finite element spaces as well as a natural hierarchical decompositio...
Radim Blaheta
FOIKS
2008
Springer
13 years 10 months ago
Autonomous Sets - A Method for Hypergraph Decomposition with Applications in Database Theory
We present a method for decomposing a hypergraph with certain regularities into smaller hypergraphs. By applying this to the set of all canonical covers of a given set of functiona...
Henning Köhler
JSAC
2006
180views more  JSAC 2006»
13 years 9 months ago
A Tutorial on Decomposition Methods for Network Utility Maximization
A systematic understanding of the decomposability structures in network utility maximization is key to both resource allocation and functionality allocation. It helps us obtain the...
Daniel Pérez Palomar, Mung Chiang