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» Learning of Boolean Functions Using Support Vector Machines
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PR
2006
110views more  PR 2006»
15 years 2 months ago
Classifying protein sequences using hydropathy blocks
The annotation of proteins can be achieved by classifying the protein of interest into a certain known protein family to induce its functional and structural features. This paper ...
De-Shuang Huang, Xing-Ming Zhao, Guang-Bin Huang, ...
PPSN
2010
Springer
15 years 16 days ago
Comparison-Based Optimizers Need Comparison-Based Surrogates
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
90
Voted
ACL
2010
15 years 5 days ago
A Study of Information Retrieval Weighting Schemes for Sentiment Analysis
Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated fea...
Georgios Paltoglou, Mike Thelwall
86
Voted
ICML
2003
IEEE
16 years 2 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
134
Voted
ICPR
2008
IEEE
16 years 3 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...