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» Language model adaptation using Random Forests
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TKDE
2008
123views more  TKDE 2008»
13 years 7 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
INTERSPEECH
2010
13 years 2 months ago
SCARF: a segmental conditional random field toolkit for speech recognition
This paper describes a new toolkit - SCARF - for doing speech recognition with segmental conditional random fields. It is designed to allow for the integration of numerous, possib...
Geoffrey Zweig, Patrick Nguyen
CEAS
2006
Springer
13 years 11 months ago
An Adaptive, Semi-Structured Language Model Approach to Spam Filtering on a New Corpus
Motivated by current efforts to construct more realistic spam filtering experimental corpora, we present a newly assembled, publicly available corpus of genuine and unsolicited (s...
Ben Medlock
EUROPLOP
2006
13 years 9 months ago
Meta-Specification and Cataloging of Software Patterns with Domain Specific Languages and Adaptive Object Models
Writing patterns is a very important task for leveraging knowledge within an organization or in the software engineering community as a whole. Patterns are more than text, diagram...
León Welicki, Juan Manuel Cueva Lovelle, Lu...
TNN
2008
177views more  TNN 2008»
13 years 7 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal