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ACL
1994
13 years 8 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
AIPS
2009
13 years 8 months ago
Flexible Execution of Plans with Choice
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executive...
Patrick R. Conrad, Julie A. Shah, Brian C. William...
BMCBI
2010
124views more  BMCBI 2010»
13 years 7 months ago
Estimation and efficient computation of the true probability of recurrence of short linear protein sequence motifs in unrelated
Background: Large datasets of protein interactions provide a rich resource for the discovery of Short Linear Motifs (SLiMs) that recur in unrelated proteins. However, existing met...
Norman E. Davey, Richard J. Edwards, Denis C. Shie...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
BMCBI
2010
111views more  BMCBI 2010»
13 years 7 months ago
Functional Analysis: Evaluation of Response Intensities - Tailoring ANOVA for Lists of Expression Subsets
Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions....
Fabrice Berger, Bertrand De Meulder, Anthoula Gaig...