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ATAL
2008
Springer
15 years 6 months ago
Multi-robot Markov random fields
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
NIPS
2008
15 years 5 months ago
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Indraneel Mukherjee, David M. Blei
FLAIRS
2001
15 years 5 months ago
Learning and Predicting User Behavior for Particular Resource Use
To successfully interact with users in providing useful information, intelligent user interfaces need a mechanism for recognizing, characterizing, and predicting user actions. In ...
Jung Jin Lee, Robert McCartney, Eugene Santos Jr.
ICML
2010
IEEE
15 years 5 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
CIKM
2010
Springer
15 years 2 months ago
Ranking under temporal constraints
This paper introduces the notion of temporally constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specifi...
Lidan Wang, Donald Metzler, Jimmy Lin