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AGENTS
1999
Springer
13 years 11 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
CICLING
2007
Springer
14 years 1 months ago
Handling Conjunctions in Named Entities
Although the literature contains reports of very high accuracy figures for the recognition of named entities in text, there are still some named entity phenomena that remain probl...
Robert Dale, Pawel P. Mazur
BMCBI
2006
119views more  BMCBI 2006»
13 years 7 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
KDD
2010
ACM
249views Data Mining» more  KDD 2010»
13 years 9 months ago
Semi-supervised sparse metric learning using alternating linearization optimization
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
Wei Liu, Shiqian Ma, Dacheng Tao, Jianzhuang Liu, ...
ICML
2004
IEEE
14 years 8 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...