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ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 8 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
ICML
2007
IEEE
16 years 2 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
AAAI
2010
15 years 3 months ago
Gaussian Mixture Model with Local Consistency
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Jialu Liu, Deng Cai, Xiaofei He
PODC
2012
ACM
13 years 4 months ago
On the price of equivocation in byzantine agreement
In the Byzantine agreement problem, a set of n processors, any f of whom may be arbitrarily faulty, must reach agreement on a value proposed by one of the correct processors. It i...
Alexander Jaffe, Thomas Moscibroda, Siddhartha Sen
CORR
2007
Springer
97views Education» more  CORR 2007»
15 years 1 months ago
Estimation of the Rate-Distortion Function
—Motivated by questions in lossy data compression and by theoretical considerations, the problem of estimating the rate-distortion function of an unknown (not necessarily discret...
Matthew T. Harrison, Ioannis Kontoyiannis