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» Reasoning about Knowledge Using Rough Sets
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121
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IJCAI
2001
15 years 2 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
113
Voted
ICCV
2009
IEEE
16 years 5 months ago
Time Series Prediction by Chaotic Modeling of Nonlinear Dynamical Systems
We use concepts from chaos theory in order to model nonlinear dynamical systems that exhibit deterministic behavior. Observed time series from such a system can be embedded into...
Arslan Basharat, Mubarak Shah
122
Voted
ATAL
2008
Springer
15 years 2 months ago
Sequential decision making in repeated coalition formation under uncertainty
The problem of coalition formation when agents are uncertain about the types or capabilities of their potential partners is a critical one. In [3] a Bayesian reinforcement learnin...
Georgios Chalkiadakis, Craig Boutilier
JVCA
2000
232views more  JVCA 2000»
15 years 18 days ago
Realistic surface reconstruction of 3D scenes from uncalibrated image sequences
This contribution addresses the problem of obtaining 3D models from image sequences. A 3D surface description of the scene is extracted completely from a set of uncalibrated camer...
Reinhard Koch, Marc Pollefeys, Luc J. Van Gool
197
Voted
POPL
2008
ACM
16 years 1 months ago
Foundations for structured programming with GADTs
GADTs are at the cutting edge of functional programming and become more widely used every day. Nevertheless, the semantic foundations underlying GADTs are not well understood. In ...
Patricia Johann, Neil Ghani