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» Compositional Methods for Probabilistic Systems
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AR
2011
14 years 8 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
ACL
2009
14 years 11 months ago
Learning a Compositional Semantic Parser using an Existing Syntactic Parser
We present a new approach to learning a semantic parser (a system that maps natural language sentences into logical form). Unlike previous methods, it exploits an existing syntact...
Ruifang Ge, Raymond J. Mooney
ATAL
2008
Springer
15 years 3 months ago
An adaptive probabilistic trust model and its evaluation
In open settings, the participants are autonomous and there is no central authority to ensure the felicity of their interactions. When agents interact in such settings, each relie...
Chung-Wei Hang, Yonghong Wang, Munindar P. Singh
JSW
2008
202views more  JSW 2008»
15 years 1 months ago
Change Prediction in Object-Oriented Software Systems: A Probabilistic Approach
An estimation of change-proneness of parts of a software system is an active topic in the area of software engineering. Such estimates can be used to predict changes to different c...
Ali R. Sharafat, Ladan Tahvildari
DEDS
2007
111views more  DEDS 2007»
15 years 1 months ago
Compositional Synthesis of Maximally Permissive Supervisors Using Supervision Equivalence
This paper presents a general framework for efficient synthesis of supervisors for discrete event systems. The approach is based on compositional minimisation, using concepts of p...
Hugo Flordal, Robi Malik, Martin Fabian, Knut &Ari...