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» Optimization of Machine Descriptions for Efficient Use
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ICML
2005
IEEE
14 years 8 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore

Lab
652views
15 years 7 months ago
Electronic Enterprises Laboratory
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...
CEAS
2007
Springer
13 years 12 months ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
VLDB
2005
ACM
87views Database» more  VLDB 2005»
14 years 1 months ago
An Efficient SQL-based RDF Querying Scheme
Devising a scheme for efficient and scalable querying of Resource Description Framework (RDF) data has been an active area of current research. However, most approaches define new...
Eugene Inseok Chong, Souripriya Das, George Eadon,...
ICML
2006
IEEE
14 years 8 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...