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CDC
2009
IEEE
156views Control Systems» more  CDC 2009»
13 years 11 months ago
Input design using Markov chains for system identification
This paper studies the input design problem for system identification where time domain constraints have to be considered. A finite Markov chain is used to model the input of the s...
Chiara Brighenti, Bo Wahlberg, Cristian R. Rojas
ESA
2010
Springer
246views Algorithms» more  ESA 2010»
13 years 8 months ago
Estimating the Average of a Lipschitz-Continuous Function from One Sample
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abhimanyu Das, David Kempe
PRL
2007
138views more  PRL 2007»
13 years 7 months ago
Ent-Boost: Boosting using entropy measures for robust object detection
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
Duy-Dinh Le, Shin'ichi Satoh
JACM
2012
11 years 10 months ago
Continuous sampling from distributed streams
A fundamental problem in data management is to draw and maintain a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With la...
Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang
UAI
2000
13 years 9 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling