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» On an Optimization Problem in Sensor Selection*
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CORR
2010
Springer
125views Education» more  CORR 2010»
14 years 10 months ago
Near-Optimal Bayesian Active Learning with Noisy Observations
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Daniel Golovin, Andreas Krause, Debajyoti Ray
SIGMOD
2002
ACM
236views Database» more  SIGMOD 2002»
15 years 10 months ago
The Cougar Approach to In-Network Query Processing in Sensor Networks
The widespread distribution and availability of smallscale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such examp...
Yong Yao, Johannes Gehrke
SUTC
2008
IEEE
15 years 4 months ago
Training Data Compression Algorithms and Reliability in Large Wireless Sensor Networks
With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different typ...
Vasanth Iyer, Rammurthy Garimella, M. B. Srinivas
CORR
2010
Springer
146views Education» more  CORR 2010»
14 years 10 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
ESANN
2006
14 years 11 months ago
Optimal design of hierarchical wavelet networks for time-series forecasting
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...
Yuehui Chen, Bo Yang, Ajith Abraham