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» Capturing Data Uncertainty in High-Volume Stream Processing
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DSN
2011
IEEE
12 years 7 months ago
Modeling stream processing applications for dependability evaluation
— This paper describes a modeling framework for evaluating the impact of faults on the output of streaming ions. Our model is based on three abstractions: stream operators, strea...
Gabriela Jacques-Silva, Zbigniew Kalbarczyk, Bugra...
ASPDAC
2008
ACM
174views Hardware» more  ASPDAC 2008»
13 years 9 months ago
Chebyshev Affine Arithmetic based parametric yield prediction under limited descriptions of uncertainty
In modern circuit design, it is difficult to provide reliable parametric yield prediction since the real distribution of process data is hard to measure. Most existing approaches ...
Jin Sun, Yue Huang, Jun Li, Janet Meiling Wang
PODS
2004
ACM
147views Database» more  PODS 2004»
14 years 7 months ago
Flexible Time Management in Data Stream Systems
Continuous queries in a Data Stream Management System (DSMS) rely on time as a basis for windows on streams and for defining a consistent semantics for multiple streams and updata...
Utkarsh Srivastava, Jennifer Widom
ICDCS
2006
IEEE
14 years 1 months ago
Greedy is Good: On Service Tree Placement for In-Network Stream Processing
This paper is concerned with reducing communication costs when executing distributed user tasks in a sensor network. We take a service-oriented abstraction of sensor networks, whe...
Zoë Abrams, Jie Liu
PAMI
2008
182views more  PAMI 2008»
13 years 7 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann