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» Structured Learning with Approximate Inference
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106
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COGSCI
2008
129views more  COGSCI 2008»
15 years 2 months ago
A Rational Analysis of Rule-Based Concept Learning
We propose a new model of human concept learning that provides a rational analysis for learning of feature-based concepts. This model is built upon Bayesian inference for a gramma...
Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldma...
134
Voted
JMLR
2010
134views more  JMLR 2010»
14 years 9 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
127
Voted
ICPR
2008
IEEE
16 years 3 months ago
A discriminative semi-Markov model for robust scene text recognition
We present a semi-Markov model for recognizing scene text that integrates character and word segmentation with recognition. Using wavelet features, it requires only approximate lo...
Allen R. Hanson, Erik G. Learned-Miller, Jerod J. ...
131
Voted
ICCV
2009
IEEE
15 years 8 days ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos
131
Voted
ICML
2006
IEEE
16 years 3 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty