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» Adapting SVM Classifiers to Data with Shifted Distributions
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EMNLP
2008
15 years 1 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
IJON
2006
95views more  IJON 2006»
14 years 11 months ago
Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis
A correlation-based similarity measure is derived for generalized relevance learning vector quantization (GRLVQ). The resulting GRLVQ-C classifier makes Pearson correlation availa...
Marc Strickert, Udo Seiffert, Nese Sreenivasulu, W...
ICCV
2003
IEEE
16 years 1 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
CVPR
2004
IEEE
16 years 1 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
84
Voted
ESANN
2006
15 years 1 months ago
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM)
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...
Tong Boon Tang, Alan F. Murray