Algorithms in combinatorial geometry
Algorithms in combinatorial geometry
Topologically sweeping an arrangement
Journal of Computer and System Sciences - 18th Annual ACM Symposium on Theory of Computing (STOC), May 28-30, 1986
Discrete Mathematics - Topological, algebraical and combinatorial structures; Froli´k's memorial volume
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
On degeneracy in geometric computations
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Fast implementation of depth contours using topological sweep
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
On Removing Non-degeneracy Assumptions in Computational Geometry
CIAC '97 Proceedings of the Third Italian Conference on Algorithms and Complexity
A dual-space approach to tracking and sensor management in wireless sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
A practical approximation algorithm for the LMS line estimator
Computational Statistics & Data Analysis
Combinatorial Approaches for Mass Spectra Recalibration
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Computational Geometric Approach to Submodular Function Minimization for Multiclass Queueing Systems
IPCO '07 Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization
Topological sweep of the complete graph
Discrete Applied Mathematics
Computing the least median of squares estimator in time O(nd)
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
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Topological sweep can contribute to efficient implementations of various algorithms for data analysis. Real data, however, has degeneracies. The modification of the topological sweep algorithm presented here handles degenerate cases such as parallel or multiply concurrent lines without requiring numerical perturbations to achieve general position. Our method maintains the O(n2) and O(n) time and space complexities of the original algorithm, and is robust and easy to implement. We present experimental results.