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» On learning with dissimilarity functions
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SIGIR
2008
ACM
15 years 6 months ago
Novelty and diversity in information retrieval evaluation
Evaluation measures act as objective functions to be optimized by information retrieval systems. Such objective functions must accurately reflect user requirements, particularly w...
Charles L. A. Clarke, Maheedhar Kolla, Gordon V. C...
LPAR
2010
Springer
15 years 4 months ago
Semiring-Induced Propositional Logic: Definition and Basic Algorithms
In this paper we introduce an extension of propositional logic that allows clauses to be weighted with values from a generic semiring. The main interest of this extension is that ...
Javier Larrosa, Albert Oliveras, Enric Rodrí...

Book
640views
17 years 5 months ago
Introduction to Pattern Recognition
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
Sargur Srihari
CVPR
2009
IEEE
17 years 2 months ago
Regularized Multi-Class Semi-Supervised Boosting
Many semi-supervised learning algorithms only deal with binary classification. Their extension to the multi-class problem is usually obtained by repeatedly solving a set of bina...
Amir Saffari, Christian Leistner, Horst Bischof
284
Voted
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu