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» Using a Non-prior Training Active Feature Model
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PAMI
2002
112views more  PAMI 2002»
14 years 9 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
SIGIR
2008
ACM
14 years 9 months ago
A bayesian logistic regression model for active relevance feedback
Relevance feedback, which traditionally uses the terms in the relevant documents to enrich the user's initial query, is an effective method for improving retrieval performanc...
Zuobing Xu, Ram Akella
ICDM
2005
IEEE
128views Data Mining» more  ICDM 2005»
15 years 3 months ago
An Expected Utility Approach to Active Feature-Value Acquisition
In many classification tasks training data have missing feature values that can be acquired at a cost. For building accurate predictive models, acquiring all missing values is of...
Prem Melville, Foster J. Provost, Raymond J. Moone...
PR
2008
218views more  PR 2008»
14 years 9 months ago
Automatic feature localisation with constrained local models
We present an efficient and robust method of locating a set of feature points in an object of interest. From a training set we construct a joint model of the appearance of each fe...
David Cristinacce, Timothy F. Cootes
ICANN
2003
Springer
15 years 2 months ago
The Spike Response Model: A Framework to Predict Neuronal Spike Trains
We propose a simple method to map a generic threshold model, namely the Spike Response Model, to artificial data of neuronal activity using a minimal amount of a priori informatio...
Renaud Jolivet, Timothy J. Lewis, Wulfram Gerstner