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ICANN
2009
Springer
14 years 1 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
ILP
2007
Springer
14 years 2 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 8 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
ICASSP
2011
IEEE
13 years 14 days ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
ICCV
2007
IEEE
14 years 10 months ago
Proximity Distribution Kernels for Geometric Context in Category Recognition
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...
Haibin Ling, Stefano Soatto