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Computational complexity theory / Submodular set function / Matroid theory / Greedy algorithm / Algorithm / Optimization problem / Selection algorithm / Time complexity / Reduction / Theoretical computer science / Mathematics / Applied mathematics


Journal of Machine Learning Research[removed]2801 Submitted 1/08; Revised 9/08; Published[removed]Robust Submodular Observation Selection Andreas Krause
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Document Date: 2009-08-13 03:47:05

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Pittsburgh / /

Company

COM Google Inc. / GOOGLE / Water Sensor Networks / /

Event

Reorganization / /

Facility

Machine Learning Department Carnegie Mellon University / EDU Computer Science Department Carnegie Mellon University / /

IndustryTerm

greedy solution / good approximation algorithm / submodular saturation algorithm / approximation algorithm / feasible solution / polynomial time approximation algorithm / binary search / polynomial time algorithm / binary search procedure / greedy algorithm / search interval / approximate solution / myopic algorithm / greedy forward-selection algorithm / cmax cmin search interval / approximate algorithm / candidate solutions / municipal water distribution network / water distribution networks / feasible solutions / approximation algorithms / /

Organization

EDU Computer Science Department / Carnegie Mellon University / EDU Computer Science Department Carnegie Mellon University / Computer Science Department / /

Person

Anupam Gupta / Chris Williams Abstract / Andreas Krause / H. Brendan McMahan / Carlos Guestrin / /

Position

Editor / /

ProvinceOrState

Pennsylvania / /

PublishedMedium

Journal of Machine Learning Research / /

Technology

greedy forward-selection algorithm / polynomial time algorithm / approximation algorithm / Submodular Saturation algorithm / approximate algorithm / greedy algorithm / 4.2 Algorithm / good approximation algorithm / approximation algorithms / SDP-based algorithms / Machine Learning / GPC algorithm / polynomial time approximation algorithm / 4.1 Algorithm / /

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