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» Learning Behavior Models for Hybrid Timed Systems
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DSN
2008
IEEE
15 years 10 months ago
Anomaly? application change? or workload change? towards automated detection of application performance anomaly and change
: Automated tools for understanding application behavior and its changes during the application life-cycle are essential for many performance analysis and debugging tasks. Applicat...
Ludmila Cherkasova, Kivanc M. Ozonat, Ningfang Mi,...
ICRA
2006
IEEE
87views Robotics» more  ICRA 2006»
15 years 10 months ago
Learning to Predict Slip for Ground Robots
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
ICPR
2004
IEEE
16 years 5 months ago
Probabilistic People Tracking for Occlusion Handling
This work presents a novel people tracking approach, able to cope with frequent shape changes and large occlusions. In particular, the tracks are described by means of probabilist...
Rita Cucchiara, Costantino Grana, Giovanni Tardini...
DATE
2009
IEEE
116views Hardware» more  DATE 2009»
15 years 11 months ago
An MDE methodology for the development of high-integrity real-time systems
—This paper reports on experience gained and lessons learned from an intensive investigation of model-driven engineering methodology and technology for application to high-integr...
Silvia Mazzini, Stefano Puri, Tullio Vardanega
VLDB
2001
ACM
190views Database» more  VLDB 2001»
15 years 8 months ago
LEO - DB2's LEarning Optimizer
Most modern DBMS optimizers rely upon a cost model to choose the best query execution plan (QEP) for any given query. Cost estimates are heavily dependent upon the optimizer’s e...
Michael Stillger, Guy M. Lohman, Volker Markl, Mok...