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122
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EMNLP
2004
15 years 4 months ago
Sentiment Analysis using Support Vector Machines with Diverse Information Sources
This paper introduces an approach to sentiment analysis which uses support vector machines (SVMs) to bring together diverse sources of potentially pertinent information, including...
Tony Mullen, Nigel Collier
137
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ASC
2008
15 years 2 months ago
Dynamic classification for video stream using support vector machine
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...
Mariette Awad, Yuichi Motai
135
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CVBIA
2005
Springer
15 years 8 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
111
Voted
PR
2007
104views more  PR 2007»
15 years 2 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
122
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CONEXT
2007
ACM
15 years 4 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek