Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks

By Andreas Krause, Jure Leskovec, Carlos Guestrin, Jeanne M. VanBriesen, Christos Faloutsos. 2008

423 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Ocean Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f90ddac506a7e19c71849bd1aeeffac5324e89bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Andreas Krause
2. D. Golovin
3. Carla P. Gomes
4. Moran Feldman
5. Niv Buchbinder
6. Roy Schwartz
7. Carlos Guestrin
8. Laks V. S. Lakshmanan

In Ocean Engineering

1. Carla P. Gomes
2. Niv Buchbinder
3. Roy Schwartz
4. Moran Feldman
5. Andreas Krause
6. Carlos Guestrin

In Water Science and Technology

1. Carla P. Gomes
2. Niv Buchbinder
3. Roy Schwartz
4. Moran Feldman
5. Andreas Krause
6. Carlos Guestrin

Citations in the corpus

• Submodular Maximization with Cardinality Constraints (2014, methodology): “In machine learning, maximization of submodular functions has been used for document summarization [41, 42], sensor placement [36, 38, 35], and information gathering [37] (consult the references therein for additional applications in AI).”
• Near-optimal Observation Selection using Submodular Functions (2007, methodology): “In our recent work (Krause & Guestrin 2005c; Guestrin, Krause, & Singh 2005; Krause et al. 2006; 2007; Singh et al. 2007), we have presented several efficient algorithms for approximately solving these optimization problems .”
• Submodular Function Maximization (2014, methodology): “Krause et al. (2008c) develop Saturate , an algorithm that is guaranteed to efficiently obtain a set S such that f min ( S ) ≥ OPT k , and | S | ≤ 1 + max v ln i f i ( { v } ) k .”
• Computational Sustainability (2011, methodology): “For example, when using wireless networks to monitor spatial phenomena, the selection of the best sensor placement in order to maximize the information gain while minimizing communication costs is a complex optimization problem requiring new solution techniques (Krause et al. 2006, 2008).”
• Optimal Value of Information in Graphical Models (2009, background): “The authors showed (Krause & Guestrin, 2005a; Krause et al., 2007; Krause, Leskovec, Guestrin, VanBriesen, & Faloutsos, 2008 ) that a large number of practical objective functions satisfy an intuitive diminishing returns property: Adding a new observation helps more if we have few observations so f”
• Online Submodular Maximization with Preemption (2015, methodology): “In machine learning, submodular maximization has been used for document summarization [46, 47], sensor placement [41, 42, 44], and information gathering [43].”