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AAAI
2008
15 years 7 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
JMLR
2010
134views more  JMLR 2010»
14 years 11 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
CSCW
2010
ACM
16 years 1 months ago
Are you having difficulty?
It would be useful if software engineers/instructors could be aware that remote team members/students are having difficulty with their programming tasks. We have developed an appr...
Jason Carter, Prasun Dewan
GECCO
2004
Springer
119views Optimization» more  GECCO 2004»
15 years 10 months ago
Learning Environment for Life Time Value Calculation of Customers in Insurance Domain
A critical success factor in Insurance business is its ability to use information sources and contained knowledge in the most effective way. Its profitability is obtained through t...
Andrea Tettamanzi, Luca Sammartino, Mikhail Simono...
ICML
2006
IEEE
16 years 5 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence