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COLT
1999
Springer
15 years 10 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
ECML
2003
Springer
15 years 11 months ago
Ensembles of Multi-instance Learners
In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. Through analyzin...
Zhi-Hua Zhou, Min-Ling Zhang
FLAIRS
2000
15 years 8 months ago
Learning to Transfer Knowledge between Reference Systems
Representationandinference of spatial knowledgeplay a fundamentalrole in spatial reasoning,whichitself is an important componentof manyapplications such as GeographicInformationSy...
Maria do Carmo Nicoletti, Jane Brennan
ICTAI
1993
IEEE
15 years 10 months ago
Robust Feature Selection Algorithms
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Haleh Vafaie, Kenneth DeJong
ICML
2009
IEEE
16 years 7 months ago
Factored conditional restricted Boltzmann Machines for modeling motion style
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
Graham W. Taylor, Geoffrey E. Hinton