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» Constraint Programming for Data Mining and Machine Learning
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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
15 years 7 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 5 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
UIST
2010
ACM
14 years 11 months ago
Gestalt: integrated support for implementation and analysis in machine learning
We present Gestalt, a development environment designed to support the process of applying machine learning. While traditional programming environments focus on source code, we exp...
Kayur Patel, Naomi Bancroft, Steven M. Drucker, Ja...
ANNPR
2006
Springer
15 years 5 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe
138
Voted
NIPS
2004
15 years 3 months ago
Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...