An accelerated sequential algorithm for producing D-optimal designs
SIAM Journal on Scientific and Statistical Computing
Constructing exact D-optimal experimental designs by simulated annealing
American Journal of Mathematical and Management Sciences
Elements of information theory
Elements of information theory
Information-based objective functions for active data selection
Neural Computation
A review of some exchange algorithms for constructing discrete D-optimal designs
Computational Statistics & Data Analysis - Second special issue on optimization techniques in statistics
Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
A randomized art-gallery algorithm for sensor placement
SCG '01 Proceedings of the seventeenth annual symposium on Computational geometry
Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Gaussian Process Regression: Active Data Selection and Test Point Rejection
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Convex Optimization
Near-optimal sensor placements in Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Asymptotic Theory of Information-Theoretic Experimental Design
Neural Computation
Near-optimal sensor placements: maximizing information while minimizing communication cost
Proceedings of the 5th international conference on Information processing in sensor networks
Deploying wireless sensors to achieve both coverage and connectivity
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Generalized spectral bounds for sparse LDA
ICML '06 Proceedings of the 23rd international conference on Machine learning
Active learning via transductive experimental design
ICML '06 Proceedings of the 23rd international conference on Machine learning
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach
Proceedings of the 24th international conference on Machine learning
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Algorithms for subset selection in linear regression
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Efficient planning of informative paths for multiple robots
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Energy-efficient deployment of Intelligent Mobile sensor networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A note on maximizing a submodular set function subject to a knapsack constraint
Operations Research Letters
Gaussian process dynamic programming
Neurocomputing
Non-monotone submodular maximization under matroid and knapsack constraints
Proceedings of the forty-first annual ACM symposium on Theory of computing
Simultaneous placement and scheduling of sensors
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Learning Preferences with Hidden Common Cause Relations
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Overview based example selection in end user interactive concept learning
Proceedings of the 22nd annual ACM symposium on User interface software and technology
Efficient informative sensing using multiple robots
Journal of Artificial Intelligence Research
Optimal value of information in graphical models
Journal of Artificial Intelligence Research
Machine learning in ecosystem informatics and sustainability
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Nonmyopic adaptive informative path planning for multiple robots
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Mobile sensor networks for learning anisotropic Gaussian processes
ACC'09 Proceedings of the 2009 conference on American Control Conference
Multiscale sensing with stochastic modeling
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Placement quality in structured light systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Can you see me now? sensor positioning for automated and persistent surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Gaussian Processes for Object Categorization
International Journal of Computer Vision
SFO: A Toolbox for Submodular Function Optimization
The Journal of Machine Learning Research
IEEE Transactions on Signal Processing
Bayesian optimization for sensor set selection
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Online distributed sensor selection
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Planning to see: A hierarchical approach to planning visual actions on a robot using POMDPs
Artificial Intelligence
Submodular fractional programming for balanced clustering
Pattern Recognition Letters
Robust sensor placements at informative and communication-efficient locations
ACM Transactions on Sensor Networks (TOSN)
Network optimization algorithms and scenarios in the context of automatic mapping
Computers & Geosciences
Maximizing Nonmonotone Submodular Functions under Matroid or Knapsack Constraints
SIAM Journal on Discrete Mathematics
A case study of participatory data transfer for urban temperature monitoring
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
Adaptive compression for 3D laser data
International Journal of Robotics Research
Active Markov information-theoretic path planning for robotic environmental sensing
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Designing for effective end-user interaction with machine learning
Proceedings of the 24th annual ACM symposium adjunct on User interface software and technology
The Journal of Machine Learning Research
Active learning of visual descriptors for grasping using non-parametric smoothed beta distributions
Robotics and Autonomous Systems
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime
Journal of Computational Neuroscience
Robotic object detection: learning to improve the classifiers using sparse graphs for path planning
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Adaptive data compression for robot perception
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Active learning for online bayesian matrix factorization
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Following the electrons: methods for power management in commercial buildings
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Automatica (Journal of IFAC)
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Active visual sensing and collaboration on mobile robots using hierarchical POMDPs
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Efficient space-time modeling for informative sensing
Proceedings of the Sixth International Workshop on Knowledge Discovery from Sensor Data
Distributed robotic sensor networks: An information-theoretic approach
International Journal of Robotics Research
Value of information and mobility constraints for sampling with mobile sensors
Computers & Geosciences
Swarm interpolation using an approximate chebyshev distribution
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
Active learning of inverse models with intrinsically motivated goal exploration in robots
Robotics and Autonomous Systems
On assessing the accuracy of positioning systems in indoor environments
EWSN'13 Proceedings of the 10th European conference on Wireless Sensor Networks
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Automated generation of interaction graphs for value-factored dec-POMDPs
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Automatica (Journal of IFAC)
Computational Statistics & Data Analysis
Dynamic Data Driven Application System for Plume Estimation Using UAVs
Journal of Intelligent and Robotic Systems
Collecting data in ad-hoc networks with reduced uncertainty
Ad Hoc Networks
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When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the points of highest entropy (variance) in the GP model, and A-, D-, or E-optimal design. In this paper, we tackle the combinatorial optimization problem of maximizing the mutual information between the chosen locations and the locations which are not selected. We prove that the problem of finding the configuration that maximizes mutual information is NP-complete. To address this issue, we describe a polynomial-time approximation that is within (1-1/e) of the optimum by exploiting the submodularity of mutual information. We also show how submodularity can be used to obtain online bounds, and design branch and bound search procedures. We then extend our algorithm to exploit lazy evaluations and local structure in the GP, yielding significant speedups. We also extend our approach to find placements which are robust against node failures and uncertainties in the model. These extensions are again associated with rigorous theoretical approximation guarantees, exploiting the submodularity of the objective function. We demonstrate the advantages of our approach towards optimizing mutual information in a very extensive empirical study on two real-world data sets.