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JCP
2008
166views more  JCP 2008»
13 years 9 months ago
Water Demand Prediction using Artificial Neural Networks and Support Vector Regression
Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts...
ICML
2007
IEEE
14 years 10 months ago
Multiclass core vector machine
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
TNN
2010
143views Management» more  TNN 2010»
13 years 3 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
ICIP
2000
IEEE
14 years 10 months ago
Dynamic Memory Model Based Optimization of Scalar and Vector Quantizer for Fast Image Encoding
The rapid progress of computers and today's heterogeneous computing environment means computation-intensive signal processing algorithms must be optimized for performance in ...
Gene Cheung, Steven McCanne
BMCBI
2008
88views more  BMCBI 2008»
13 years 9 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...