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» A Theory of Mean Field Approximation
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NIPS
2008
14 years 11 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
KR
2000
Springer
15 years 1 months ago
Approximate Objects and Approximate Theories
We propose to extend the ontology of logical AI to include approximate objects, approximate predicates and approximate theories. Besides the ontology we treat the relations among ...
John McCarthy
ICIP
2006
IEEE
15 years 4 months ago
A Theory of Aliasing Separation for Light Field Data
A light field means a 4-D function which characterizes the flow of light rays from a target scene, and used for image-based rendering. This paper presents a novel theoretical fr...
Keita Takahashi, Takeshi Naemura
NIPS
2000
14 years 11 months ago
High-temperature Expansions for Learning Models of Nonnegative Data
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Oliver B. Downs
IJCNN
2008
IEEE
15 years 4 months ago
On the sample mean of graphs
— We present an analytic and geometric view of the sample mean of graphs. The theoretical framework yields efficient subgradient methods for approximating a structural mean and ...
Brijnesh J. Jain, Klaus Obermayer