Efficient training of high-order hidden Markov models using first-order representations

ISSN： 0885-2308

Source： Computer Speech & Language, Vol.12, Iss.1, 1998-01, pp. : 23-39

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models

By Siu Tak-Kuen Ching Wai-Ki Fung Eric Ng Michael

Computational Economics, Vol. 26, Iss. 3-4, 2005-11 ,pp. : 69-102

Springer Publishing Company

Access to resources Recommend Favorite

Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models

By Siu Tak-Kuen Ching Wai-Ki Fung Eric Ng Michael

Computational Economics, Vol. 29, Iss. 3-4, 2007-05 ,pp. : 425-425

Springer Publishing Company

Access to resources Recommend Favorite

EFFICIENT INDUCTION AND EFFECTIVE USE OF FIRST-ORDER KNOWLEDGE

By Pompe Uros Kononenko Igor

Applied Artificial Intelligence, Vol. 12, Iss. 5, 1998-07 ,pp. : 421-453

Taylor & Francis Ltd

Access to resources Recommend Favorite

Design of abstract domains using first-order logic

By Marchiori E.

Theoretical Computer Science, Vol. 222, Iss. 1, 1999-07 ,pp. : 153-179

Elsevier

Access to resources Recommend Favorite

Hardness Results for Learning First-Order Representations and Programming by Demonstration

By Cohen W.W.

Machine Learning, Vol. 30, Iss. 1, 1998-01 ,pp. : 57-87

Springer Publishing Company

Access to resources Recommend Favorite