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» Approximate Temporal Aggregation
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CISS
2011
IEEE
12 years 11 months ago
Improving aggregated forecasts of probability
—The Coherent Approximation Principle (CAP) is a method for aggregating forecasts of probability from a group of judges by enforcing coherence with minimal adjustment. This paper...
Guanchun Wang, Sanjeev R. Kulkarni, H. Vincent Poo...
FTDB
2011
98views more  FTDB 2011»
12 years 11 months ago
Secure Distributed Data Aggregation
We present a survey of the various families of approaches to secure aggregation in distributed networks such as sensor networks. In our survey, we focus on the important algorithm...
Haowen Chan, Hsu-Chun Hsiao, Adrian Perrig, Dawn S...
INFOCOM
2006
IEEE
14 years 1 months ago
On the Potential of Structure-Free Data Aggregation in Sensor Networks
— Data aggregation protocols can reduce the cost of communication, thereby extending the lifetime of sensor networks. Prior work on data aggregation protocols has focused on tree...
Kai-Wei Fan, Sha Liu, Prasun Sinha
ML
2002
ACM
154views Machine Learning» more  ML 2002»
13 years 7 months ago
Technical Update: Least-Squares Temporal Difference Learning
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
Justin A. Boyan
JAIR
2010
108views more  JAIR 2010»
13 years 5 months ago
Kalman Temporal Differences
This paper deals with value (and Q-) function approximation in deterministic Markovian decision processes (MDPs). A general statistical framework based on the Kalman filtering pa...
Matthieu Geist, Olivier Pietquin