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» A distributed machine learning framework
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NIPS
2000
15 years 4 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
ICML
1999
IEEE
16 years 3 months ago
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
Rajesh Parekh, Vasant Honavar
123
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COLCOM
2009
IEEE
15 years 7 months ago
The PEI framework for application-centric security
This paper motivates the fundamental importance of application context for security. It then gives an overview of the PEI framework for application-centric security and outlines s...
Ravi S. Sandhu
COLT
1995
Springer
15 years 6 months ago
On the Learnability and Usage of Acyclic Probabilistic Finite Automata
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Dana Ron, Yoram Singer, Naftali Tishby
ICML
2007
IEEE
16 years 3 months ago
Bayesian actor-critic algorithms
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Mohammad Ghavamzadeh, Yaakov Engel