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ICDE
2006
IEEE
201views Database» more  ICDE 2006»
14 years 9 months ago
Approximate Data Collection in Sensor Networks using Probabilistic Models
Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has propo...
David Chu, Amol Deshpande, Joseph M. Hellerstein, ...
CCE
2004
13 years 7 months ago
Optimization under uncertainty: state-of-the-art and opportunities
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncer...
Nikolaos V. Sahinidis
CDC
2010
IEEE
167views Control Systems» more  CDC 2010»
13 years 3 months ago
Numerical methods for the optimization of nonlinear stochastic delay systems, and an application to internet regulation
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
Harold J. Kushner
CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 2 months ago
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
ICCVW
1999
Springer
14 years 6 days ago
Bundle Adjustment - A Modern Synthesis
This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the p...
Bill Triggs, Philip F. McLauchlan, Richard I. Hart...