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» On an Optimization Problem in Sensor Selection*
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CORR
2010
Springer
125views Education» more  CORR 2010»
15 years 7 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»
16 years 7 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
16 years 1 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»
15 years 7 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
15 years 8 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