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» Support Vector Machines: Theory and Applications
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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...
JCB
2000
107views more  JCB 2000»
13 years 8 months ago
A Discriminative Framework for Detecting Remote Protein Homologies
A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support...
Tommi Jaakkola, Mark Diekhans, David Haussler
ISCI
2008
165views more  ISCI 2008»
13 years 8 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
SIGIR
2006
ACM
14 years 2 months ago
Tensor space model for document analysis
Vector Space Model (VSM) has been at the core of information retrieval for the past decades. VSM considers the documents as vectors in high dimensional space. In such a vector spa...
Deng Cai, Xiaofei He, Jiawei Han
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 9 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...