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ICML
1999
IEEE
16 years 7 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
ATAL
2008
Springer
15 years 8 months ago
Stochastic search methods for nash equilibrium approximation in simulation-based games
We define the class of games called simulation-based games, in which the payoffs are available as an output of an oracle (simulator), rather than specified analytically or using a...
Yevgeniy Vorobeychik, Michael P. Wellman
AAAI
1992
15 years 7 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...
TON
2008
76views more  TON 2008»
15 years 6 months ago
Minimizing file download time in stochastic peer-to-peer networks
The peer-to-peer (P2P) file-sharing applications are becoming increasingly popular and account for more than 70% of the Internet's bandwidth usage. Measurement studies show th...
Yuh-Ming Chiu, Do Young Eun
RTAS
2010
IEEE
15 years 4 months ago
A Stochastic Framework for Multiprocessor Soft Real-Time Scheduling
Prior work has shown that the global earliest-deadline-first (GEDF) scheduling algorithm ensures bounded deadline tardiness on multiprocessors with no utilization loss; therefore...
Alex F. Mills, James H. Anderson