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» Complexity of Inference in Graphical Models
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SIGIR
2010
ACM
15 years 6 months ago
Probabilistic latent maximal marginal relevance
Diversity has been heavily motivated in the information retrieval literature as an objective criterion for result sets in search and recommender systems. Perhaps one of the most w...
Shengbo Guo, Scott Sanner
WSCG
2001
77views more  WSCG 2001»
15 years 3 months ago
Physics-Enhanced L-Systems
In computer graphics and engineering many classes of complex objects can be designed with L-systems. We present a concept for enhancing timed and parametric L-systems with physics...
Hansrudi Noser, S. Rudolph, Peter Stucki
131
Voted
ICIP
2008
IEEE
16 years 4 months ago
Variational Bayesian image processing on stochastic factor graphs
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
Xin Li
122
Voted
CEC
2007
IEEE
15 years 9 months ago
A Utile Function Optimizer
Abstract— We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasi...
Christopher K. Monson, Kevin D. Seppi, James L. Ca...
112
Voted
AAMAS
2007
Springer
15 years 8 months ago
Optimal Control in Large Stochastic Multi-agent Systems
Abstract. We study optimal control in large stochastic multi-agent systems in continuous space and time. We consider multi-agent systems where agents have independent dynamics with...
Bart van den Broek, Wim Wiegerinck, Bert Kappen