509 search results - page 46 / 102 » Using Learning for Approximation in Stochastic Processes |
138
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KDD
2000
ACM
15 years 6 months ago
2000
ACM
Data--call records, internet packet headers, or other transaction records--are coming down a pipe at a ferocious rate, and we need to monitor statistics of the data. There is no r...
118
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ASC
2004
15 years 2 months ago
2004
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
144
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ICML
2008
IEEE
16 years 3 months ago
2008
IEEE
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
116
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EURONGI
2005
Springer
15 years 8 months ago
2005
Springer
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
126
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UAI
2000
15 years 3 months ago
2000
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...