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ICALT
2008
IEEE
15 years 11 months ago
Designing a Dynamic Bayesian Network for Modeling Students' Learning Styles
When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
BMCBI
2007
105views more  BMCBI 2007»
15 years 5 months ago
Constrained hidden Markov models for population-based haplotyping
abstract Niels Landwehr1 , Taneli Mielik¨ainen2 , Lauri Eronen2 , Hannu Toivonen1,2 , and Heikki Mannila2 1 Machine Learning Lab, Dept. of Comp. Science, University of Freiburg, G...
Niels Landwehr, Taneli Mielikäinen, Lauri Ero...
ACL
1998
15 years 6 months ago
Automatic Acquisition of Hierarchical Transduction Models for Machine Translation
We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...
Hiyan Alshawi, Srinivas Bangalore, Shona Douglas
ECML
2007
Springer
15 years 11 months ago
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Xiao-Lin Li, Zhi-Hua Zhou
147
Voted
ML
2002
ACM
154views Machine Learning» more  ML 2002»
15 years 4 months ago
Technical Update: Least-Squares Temporal Difference Learning
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
Justin A. Boyan