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» Learning for Dynamic Subsumption
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ECAI
2008
Springer
14 years 11 months ago
From Belief Change to Preference Change
Various tasks need to consider preferences in a dynamic way. We start by discussing several possible meanings of preference change, and then focus on the one we think is the most n...
Jérôme Lang, Leendert van der Torre
AAAI
2010
14 years 11 months ago
Integrated Systems for Inducing Spatio-Temporal Process Models
Quantitative modeling plays a key role in the natural sciences, and systems that address the task of inductive process modeling can assist researchers in explaining their data. In...
Chunki Park, Will Bridewell, Pat Langley
CAINE
2007
14 years 11 months ago
Interactive Thin Shells - A Model Interface for the Analysis of Physically-based Animation
Realism has always been a goal in computer graphics. However, the algorithms involved in mimicking ical world are often complex, abstract, and sensitive to changes in experimental...
James Skorupski, Zoë J. Wood, Alex Pang
EMNLP
2008
14 years 11 months ago
Sparse Multi-Scale Grammars for Discriminative Latent Variable Parsing
We present a discriminative, latent variable approach to syntactic parsing in which rules exist at multiple scales of refinement. The model is formally a latent variable CRF gramm...
Slav Petrov, Dan Klein
EMNLP
2008
14 years 11 months ago
A Generative Model for Parsing Natural Language to Meaning Representations
In this paper, we present an algorithm for learning a generative model of natural language sentences together with their formal meaning representations with hierarchical structure...
Wei Lu, Hwee Tou Ng, Wee Sun Lee, Luke S. Zettlemo...