On the complexity of nonconvex covering
SIAM Journal on Computing
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
The computational complexity of abduction
Artificial Intelligence - Special issue on knowledge representation
AI Communications
The complexity of logic-based abduction
Journal of the ACM (JACM)
The role of abduction in database view updating
Journal of Intelligent Information Systems
A survey of approximately optimal solutions to some covering and packing problems
ACM Computing Surveys (CSUR)
On the hardness of approximating minimization problems
Journal of the ACM (JACM)
Approximation algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Introduction to Algorithms
IEEE Transactions on Knowledge and Data Engineering
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Database Updates through Abduction
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
An efficient distributed algorithm for constructing small dominating sets
Distributed Computing - Special issue: Selected papers from PODC '01
Constant-time distributed dominating set approximation
Proceedings of the twenty-second annual symposium on Principles of distributed computing
Constrained Clustering: Advances in Algorithms, Theory, and Applications
Constrained Clustering: Advances in Algorithms, Theory, and Applications
Introduction to Machine Learning
Introduction to Machine Learning
Noise and the common sense informatic situation for a mobile robot
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Adversarial Geospatial Abduction Problems
ACM Transactions on Intelligent Systems and Technology (TIST)
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There are many applications where we observe various phenomena in space (e.g., locations of victims of a serial killer), and where we want to infer “partner” locations (e.g., the location where the killer lives) that are geospatially related to the observed phenomena. In this article, we define geospatial abduction problems (GAPs for short). We analyze the complexity of GAPs, develop exact and approximate algorithms (often with approximation guarantees) for these problems together with analyses of these algorithms, and develop a prototype implementation of our GAP framework. We demonstrate accuracy of our algorithms on a real world data set consisting of insurgent IED (improvised explosive device) attacks against U.S. forces in Iraq (the observations were the locations of the attacks, while the “partner” locations we were trying to infer were the locations of IED weapons caches).