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» On the Noise Model of Support Vector Machines Regression
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NIPS
2003
13 years 10 months ago
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not on...
William M. Campbell, Joseph P. Campbell, Douglas A...
CNSM
2010
13 years 5 months ago
Risk management in VoIP infrastructures using support vector machines
Telephony over IP is exposed to multiple security threats. Conventional protection mechanisms do not fit into the highly dynamic, open and large-scale settings of VoIP infrastructu...
Mohamed Nassar, Oussema Dabbebi, Remi Badonnel, Ol...
TNN
2010
159views Management» more  TNN 2010»
13 years 3 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
ECAI
2004
Springer
14 years 2 months ago
A Generalized Quadratic Loss for Support Vector Machines
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Filippo Portera, Alessandro Sperduti
IJCNLP
2005
Springer
14 years 2 months ago
Assigning Polarity Scores to Reviews Using Machine Learning Techniques
We propose a novel type of document classification task that quantifies how much a given document (review) appreciates the target object using not binary polarity (good or bad) b...
Daisuke Okanohara, Jun-ichi Tsujii