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IJCAI
2001
13 years 11 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
ICCV
2009
IEEE
15 years 3 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
ATAL
2008
Springer
14 years 9 days 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»
13 years 10 months 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
POPL
2008
ACM
14 years 10 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