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SAC
2005
ACM
14 years 2 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
ISMIR
2005
Springer
145views Music» more  ISMIR 2005»
14 years 2 months ago
An Investigation of Feature Models for Music Genre Classification Using the Support Vector Classifier
In music genre classification the decision time is typically of the order of several seconds, however, most automatic music genre classification systems focus on short time feat...
Anders Meng, John Shawe-Taylor
JCP
2008
166views more  JCP 2008»
13 years 8 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...
JMLR
2010
115views more  JMLR 2010»
13 years 3 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
BMCBI
2008
141views more  BMCBI 2008»
13 years 9 months ago
MiRTif: a support vector machine-based microRNA target interaction filter
Background: MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the...
Yuchen Yang, Yu-Ping Wang, Kuo-Bin Li