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» Modeling Classification and Inference Learning
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107
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CVPR
2010
IEEE
15 years 8 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
PAMI
2008
119views more  PAMI 2008»
15 years 18 days ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
89
Voted
COGSCI
2008
129views more  COGSCI 2008»
15 years 23 days 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...
74
Voted
ACSW
2004
15 years 2 months ago
A Market-based Rule Learning System
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market...
Qingqing Zhou, Martin K. Purvis
115
Voted
ICML
2008
IEEE
16 years 1 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray