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» Support Vector Machines: Theory and Applications
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AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
15 years 5 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao
CSFW
2010
IEEE
15 years 3 months ago
A Machine-Checked Formalization of Sigma-Protocols
—Zero-knowledge proofs have a vast applicability in the domain of cryptography, stemming from the fact that they can be used to force potentially malicious parties to abide by th...
Gilles Barthe, Daniel Hedin, Santiago Zanella B&ea...
ICWSM
2009
14 years 9 months ago
Delta TFIDF: An Improved Feature Space for Sentiment Analysis
Mining opinions and sentiment from social networking sites is a popular application for social media systems. Common approaches use a machine learning system with a bag of words f...
Justin Martineau, Tim Finin
COLT
2005
Springer
15 years 5 months ago
Ranking and Scoring Using Empirical Risk Minimization
A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
Stéphan Clémençon, Gáb...
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 3 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa