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» Comparing Computer Models Solving Number Series Problems
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TNN
2010
148views Management» more  TNN 2010»
14 years 4 months ago
Generalized low-rank approximations of matrices revisited
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
RAS
2007
102views more  RAS 2007»
14 years 9 months ago
Fast and accurate SLAM with Rao-Blackwellized particle filters
Rao-Blackwellized particle filters have become a popular tool to solve the simultaneous localization and mapping problem. This technique applies a particle filter in which each ...
Giorgio Grisetti, Gian Diego Tipaldi, Cyrill Stach...
ICA
2010
Springer
14 years 8 months ago
Second Order Subspace Analysis and Simple Decompositions
Abstract. The recovery of the mixture of an N-dimensional signal generated by N independent processes is a well studied problem (see e.g. [1,10]) and robust algorithms that solve t...
Harold W. Gutch, Takanori Maehara, Fabian J. Theis
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TASLP
2008
124views more  TASLP 2008»
14 years 9 months ago
Semantic Annotation and Retrieval of Music and Sound Effects
We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio c...
Douglas Turnbull, Luke Barrington, D. Torres, Gert...
JMLR
2008
230views more  JMLR 2008»
14 years 9 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...