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» Arguing and Explaining Classifications
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UAI
2004
13 years 8 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
JMLR
2002
138views more  JMLR 2002»
13 years 7 months ago
Text Chunking based on a Generalization of Winnow
This paper describes a text chunking system based on a generalization of the Winnow algorithm. We propose a general statistical model for text chunking which we then convert into ...
Tong Zhang, Fred Damerau, David Johnson
CDC
2009
IEEE
149views Control Systems» more  CDC 2009»
13 years 8 months ago
Context-dependent multi-class classification with unknown observation and class distributions with applications to bioinformatic
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...
Alex S. Baras, John S. Baras
ACMDIS
2006
ACM
14 years 1 months ago
The origin and design of intentional affordances
Gibson’s seminal concept of affordance could have real design power if it could be adequately explained as a phenomenon that happens within the scale of human lifetime. Today th...
Antonio Rizzo
VL
2009
IEEE
126views Visual Languages» more  VL 2009»
14 years 2 months ago
Visual explanations of probabilistic reasoning
Continuing our research in explanation-oriented language design, we present a domain-specific visual language for explaining probabilistic reasoning. Programs in this language, c...
Martin Erwig, Eric Walkingshaw