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» Broadcasting with Selective Reduction
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AI
2004
Springer
13 years 7 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
ECWEB
2009
Springer
204views ECommerce» more  ECWEB 2009»
14 years 2 months ago
Computational Complexity Reduction for Factorization-Based Collaborative Filtering Algorithms
Abstract. Alternating least squares (ALS) is a powerful matrix factorization (MF) algorithm for both implicit and explicit feedback based recommender systems. We show that by using...
István Pilászy, Domonkos Tikk
ICNC
2005
Springer
14 years 1 months ago
Genetic Algorithms for Thyroid Gland Ultrasound Image Feature Reduction
The problem of automatic classification of ultrasound images is addressed. For texture analysis of ultrasound images quantifiable indexes, called features, are used. Classificat...
Ludvík Tesar, Daniel Smutek, Jan Jiskra
ACTAC
1999
81views more  ACTAC 1999»
13 years 7 months ago
Test Suite Reduction in Conformance Testing
Conformance testing is based on a test suite. Standardization committees release standard test suites, which consist of hundreds of test cases. The main problem of conformance tes...
Tibor Csöndes, Sarolta Dibuz, Balázs K...
ICASSP
2011
IEEE
12 years 11 months ago
Exemplar-based Sparse Representation phone identification features
Exemplar-based techniques, such as k-nearest neighbors (kNNs) and Sparse Representations (SRs), can be used to model a test sample from a few training points in a dictionary set. ...
Tara N. Sainath, David Nahamoo, Bhuvana Ramabhadra...