Minkowski's convex body theorem and integer programming
Mathematics of Operations Research
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Fixed-Parameter Complexity and Cryptography
AAECC-10 Proceedings of the 10th International Symposium on Applied Algebra, Algebraic Algorithms and Error-Correcting Codes
Approximation algorithms for minimizing segments in radiation therapy
Information Processing Letters
Efficient and effective explanation of change in hierarchical summaries
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Decomposition of integer matrices and multileaf collimator sequencing
Discrete Applied Mathematics
A note on improving the performance of approximation algorithms for radiation therapy
Information Processing Letters
A shortest path-based approach to the multileaf collimator sequencing problem
Discrete Applied Mathematics
Parameterizing by the Number of Numbers
Theory of Computing Systems
European Journal of Combinatorics
Faster optimal algorithms for segment minimization with small maximal value
Discrete Applied Mathematics
New Limits to Classical and Quantum Instance Compression
FOCS '12 Proceedings of the 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science
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We extend previous studies on NP-hard problems dealing with the decomposition of nonnegative integer vectors into sums of few homogeneous segments. These problems are motivated by radiation therapy and database applications. If the segments may have only positive integer entries, then the problem is called Vector Explanation+. If arbitrary integer entries are allowed in the decomposition, then the problem is called Vector Explanation. Considering several natural parameterizations (including maximum vector entry, maximum difference between consecutive vector entries, maximum segment length), we obtain a refined picture of the computational (in-)tractability of these problems. In particular, we show that in relevant cases Vector Explanation+ is algorithmically harder than Vector Explanation .