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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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ML
2002
ACM
128views Machine Learning» more  ML 2002»
14 years 9 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
ACL
2006
14 years 11 months ago
Weakly Supervised Named Entity Transliteration and Discovery from Multilingual Comparable Corpora
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised d...
Alexandre Klementiev, Dan Roth
TKDE
2010
168views more  TKDE 2010»
14 years 8 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
ICML
2010
IEEE
14 years 10 months ago
Multi-agent Learning Experiments on Repeated Matrix Games
This paper experimentally evaluates multiagent learning algorithms playing repeated matrix games to maximize their cumulative return. Previous works assessed that Qlearning surpas...
Bruno Bouzy, Marc Métivier
CSL
2010
Springer
14 years 9 months ago
Evaluation of a hierarchical reinforcement learning spoken dialogue system
We describe an evaluation of spoken dialogue strategies designed using hierarchical reinforcement learning agents. The dialogue strategies were learnt in a simulated environment a...
Heriberto Cuayáhuitl, Steve Renals, Oliver ...