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ICML
1999
IEEE
14 years 10 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ICML
1996
IEEE
14 years 10 months ago
On the Learnability of the Uncomputable
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Richard H. Lathrop
SIGMOD
2009
ACM
185views Database» more  SIGMOD 2009»
14 years 9 months ago
Attacks on privacy and deFinetti's theorem
In this paper we present a method for reasoning about privacy using the concepts of exchangeability and deFinetti's theorem. We illustrate the usefulness of this technique by...
Daniel Kifer
ALT
2004
Springer
14 years 6 months ago
Prediction with Expert Advice by Following the Perturbed Leader for General Weights
When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of complexity/current loss renders the analys...
Marcus Hutter, Jan Poland
ICML
2009
IEEE
14 years 3 months ago
Grammatical inference as a principal component analysis problem
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Raphaël Bailly, François Denis, Liva R...