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NPL
1998
135views more  NPL 1998»
13 years 7 months ago
Local Adaptive Subspace Regression
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
Sethu Vijayakumar, Stefan Schaal
PR
2007
129views more  PR 2007»
13 years 7 months ago
EROS: Ensemble rough subspaces
Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
Qinghua Hu, Daren Yu, Zongxia Xie, Xiaodong Li
ICASSP
2011
IEEE
12 years 11 months ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee
IDA
2009
Springer
13 years 5 months ago
Hierarchical Extraction of Independent Subspaces of Unknown Dimensions
Abstract. Independent Subspace Analysis (ISA) is an extension of Independent Component Analysis (ICA) that aims to linearly transform a random vector such as to render groups of it...
Peter Gruber, Harold W. Gutch, Fabian J. Theis
SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 7 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal