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» Monte Carlo Methods for Process Algebra
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ICCV
2007
IEEE
14 years 9 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
ICML
2000
IEEE
14 years 8 months ago
Eligibility Traces for Off-Policy Policy Evaluation
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh

Book
519views
15 years 6 months ago
Information Theory, Inference, and Learning Algorithms
This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...
David J. C. MacKay
VLDB
2009
ACM
182views Database» more  VLDB 2009»
14 years 7 months ago
Guessing the extreme values in a data set: a Bayesian method and its applications
For a largenumber of data management problems, it would be very useful to be able to obtain a few samples from a data set, and to use the samples to guess the largest (or smallest)...
Mingxi Wu, Chris Jermaine
ICML
2007
IEEE
14 years 8 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...