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NIPS
2007
13 years 10 months ago
Distributed Inference for Latent Dirichlet Allocation
We investigate the problem of learning a widely-used latent-variable model – the Latent Dirichlet Allocation (LDA) or “topic” model – using distributed computation, where ...
David Newman, Arthur Asuncion, Padhraic Smyth, Max...
CVPR
2012
IEEE
11 years 11 months ago
Bridging the past, present and future: Modeling scene activities from event relationships and global rules
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
CIKM
2009
Springer
14 years 1 months ago
Probabilistic models for topic learning from images and captions in online biomedical literatures
Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and pro...
Xin Chen, Caimei Lu, Yuan An, Palakorn Achananupar...
NEUROSCIENCE
2001
Springer
14 years 1 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
IJCNN
2008
IEEE
14 years 3 months ago
A formula of equations of states in singular learning machines
Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
Sumio Watanabe