Making large-scale support vector machine learning practical
Advances in kernel methods
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Backcasting: adaptive sampling for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Habitat monitoring with sensor networks
Communications of the ACM - Wireless sensor networks
Wireless Sensor Devices for Animal Tracking and Control
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Ef.cient Continuous Mapping in Sensor Networks Using Isolines
MOBIQUITOUS '05 Proceedings of the The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services
Active learning for adaptive mobile sensing networks
Proceedings of the 5th international conference on Information processing in sensor networks
Contour estimation using collaborating mobile sensors
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Contour maps: monitoring and diagnosis in sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Contour approximation in sensor networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Collaborative sensing using sensors of uncoordinated mobility
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Random waypoint model in n-dimensional space
Operations Research Letters
Minimax Optimal Level-Set Estimation
IEEE Transactions on Image Processing
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We develop level set estimation algorithms for a novel low cost sensor network architecture, where sensors are mounted on agents moving without an explicit objective of sensing. A level set in a planar scalar field is the set of points with field values greater than or equal to a specified value. We model the problem as a classification problem and evaluate a heuristic to reduce the amount of communication assuming that the base station uses a Support Vector Machine classifier. We then develop a fully distributed, low complexity solution which uses opportunistic information exchange to estimate level set boundaries locally at nodes selected using leader election. We observe that the learning rates of the boundary in a locality is proportional to the complexity. Effectiveness of the proposed scheme is evaluated using simulations with data from both synthetic and measured fields. Random way point mobility model is used for node motion and trade off of accuracy and of coverage with communication costs is studied.