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» Support Vector Machines: Theory and Applications
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NIPS
1996
13 years 9 months ago
Improving the Accuracy and Speed of Support Vector Machines
Support Vector Learning Machines (SVM) are nding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very genera...
Christopher J. C. Burges, Bernhard Schölkopf
ML
2002
ACM
223views Machine Learning» more  ML 2002»
13 years 8 months ago
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
Edda Leopold, Jörg Kindermann
AAAI
2008
13 years 10 months ago
In-the-Dark Network Traffic Classification Using Support Vector Machines
This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
William H. Turkett Jr., Andrew V. Karode, Errin W....
ICPR
2002
IEEE
14 years 9 months ago
Object Detection in Images: Run-Time Complexity and Parameter Selection of Support Vector Machines
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
Nicola Ancona, Grazia Cicirelli, Ettore Stella, Ar...
ICCV
2007
IEEE
13 years 10 months ago
Combined Support Vector Machines and Hidden Markov Models for Modeling Facial Action Temporal Dynamics
The analysis of facial expression temporal dynamics is of great importance for many real-world applications. Being able to automatically analyse facial muscle actions (Action Units...
Michel François Valstar, Maja Pantic