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» Feature selection in a kernel space
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NIPS
2001
13 years 9 months ago
Quantizing Density Estimators
We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
Peter Meinicke, Helge Ritter
PAMI
2006
206views more  PAMI 2006»
13 years 7 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
NATO
1993
13 years 11 months ago
METU Object-Oriented DBMS
METU Object-Oriented DBMS 1 includes the implementation of a database kernel, an object-oriented SQL-like language and a graphical user interface. Kernel functions are divided bet...
Asuman Dogac, Cetin Ozkan, Ismailcem Budak Arpinar...
ECML
2006
Springer
13 years 11 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
JMLR
2011
192views more  JMLR 2011»
13 years 2 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...