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» A discriminative model for semi-supervised learning
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NIPS
2001
13 years 10 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
13 years 7 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...
ICML
2004
IEEE
14 years 9 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
AGI
2008
13 years 10 months ago
Cognitive Primitives for Automated Learning
Artificial Intelligence deals with the automated simulation of human intelligent behavior. Various aspects of human faculties are tackled using computational models. It is clear th...
Sudharsan Iyengar
CVPR
2008
IEEE
14 years 10 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...