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ACL
2007
15 years 5 months ago
A fully Bayesian approach to unsupervised part-of-speech tagging
Unsupervised learning of linguistic structure is a difficult problem. A common approach is to define a generative model and maximize the probability of the hidden structure give...
Sharon Goldwater, Tom Griffiths
140
Voted
ICML
2010
IEEE
15 years 4 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
CVPR
2010
IEEE
15 years 3 months ago
Modeling pixel means and covariances using factorized third-order boltzmann machines
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
Marc Aurelio Ranzato, Geoffrey E. Hinton
143
Voted
HUC
2010
Springer
15 years 3 months ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...
136
Voted
JMLR
2008
141views more  JMLR 2008»
15 years 3 months ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...