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» Learning and Inference with Constraints
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IJCNN
2006
IEEE
14 years 1 months ago
Constraints on the Design Process for Systems with Human Level Intelligence
—Any system which must learn to perform a large number of behavioral features with limited information handling resources will tend to be constrained within a set of architectura...
L. Andrew Coward
ICML
2009
IEEE
14 years 8 months ago
Bayesian inference for Plackett-Luce ranking models
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
John Guiver, Edward Snelson
ECML
2007
Springer
14 years 1 months ago
Bayesian Inference for Sparse Generalized Linear Models
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
ICML
2010
IEEE
13 years 8 months ago
Accelerated dual decomposition for MAP inference
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
Vladimir Jojic, Stephen Gould, Daphne Koller
LATA
2009
Springer
14 years 2 months ago
Hypothesis Spaces for Learning
In this paper we survey some results in inductive inference showing how learnability of a class of languages may depend on hypothesis space chosen. We also discuss results which co...
Sanjay Jain