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125
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PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
15 years 1 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
131
Voted
ICPR
2010
IEEE
15 years 21 days ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu
97
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
98
Voted
NIPS
2007
15 years 4 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
121
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AAAI
2006
15 years 4 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...