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» Learning via Finitely Many Queries
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SIGIR
2012
ACM
11 years 7 months ago
Robust ranking models via risk-sensitive optimization
Many techniques for improving search result quality have been proposed. Typically, these techniques increase average effectiveness by devising advanced ranking features and/or by...
Lidan Wang, Paul N. Bennett, Kevyn Collins-Thompso...
LATIN
2004
Springer
13 years 10 months ago
Approximating the Expressive Power of Logics in Finite Models
Abstract. We present a probability logic (essentially a first order language extended with quantifiers that count the fraction of elements in a model that satisfy a first order ...
Argimiro Arratia, Carlos E. Ortiz
ALT
2010
Springer
13 years 5 months ago
Recursive Teaching Dimension, Learning Complexity, and Maximum Classes
This paper is concerned with the combinatorial structure of concept classes that can be learned from a small number of examples. We show that the recently introduced notion of recu...
Thorsten Doliwa, Hans-Ulrich Simon, Sandra Zilles
TCSV
2008
195views more  TCSV 2008»
13 years 5 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
ICFP
2008
ACM
14 years 5 months ago
Write it recursively: a generic framework for optimal path queries
Optimal path queries are queries to obtain an optimal path specified by a given criterion of optimality. There have been many studies to give efficient algorithms for classes of o...
Akimasa Morihata, Kiminori Matsuzaki, Masato Takei...