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» Computing and using residuals in time series models
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CLOUD
2010
ACM
16 years 6 days ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
RTSS
2005
IEEE
16 years 21 days ago
Quantifying the Gap between Embedded Control Models and Time-Triggered Implementations
Mapping a set of feedback control components to executable code introduces errors due to a variety of factors such as discretization, computational delays, and scheduling policies...
Hakan Yazarel, Antoine Girard, George J. Pappas, R...
JMLR
2002
106views more  JMLR 2002»
15 years 6 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
ICPR
2004
IEEE
16 years 8 months ago
Vision Based Fire Detection
Vision based fire detection is potentially a useful technique. With the increase in the number of surveillance cameras being installed, a vision based fire detection capability ca...
Che-Bin Liu, Narendra Ahuja
ISMAR
2008
IEEE
16 years 1 months ago
OutlinAR: an assisted interactive model building system with reduced computational effort
This paper presents a system that allows online building of 3D wireframe models through a combination of user interaction and automated methods from a handheld camera-mouse. Cruci...
Pished Bunnun, Walterio W. Mayol-Cuevas