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» Reinforcement Learning with the Use of Costly Features
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TEC
2002
133views more  TEC 2002»
13 years 8 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
CVPR
2012
IEEE
11 years 11 months ago
Meta-class features for large-scale object categorization on a budget
In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...
Alessandro Bergamo, Lorenzo Torresani
JNCA
2006
92views more  JNCA 2006»
13 years 9 months ago
Cards-to-presentation on the web: generating multimedia contents featuring agent animations
With the goal of supporting the knowledge circulation and creation process in a society, we have studied story-based communication in a network community. On the basis of this res...
Yukiko I. Nakano, Toshihiro Murayama, Masashi Okam...
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
12 years 12 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
ICML
2005
IEEE
14 years 10 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...