Lutz Kettner and Emo Welzl. One sided error predicates in geometric computing. In Kurt Mehlhorn, editor, Proc. 15th IFIP World Computer Congress, Fundamentals - Foundations of Computer Science, pages 13--26, 1998. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Robust Geometric Computation - Yap (1997) (19 citations) (Correct)
....are treated in [FvW93b, Fun97] Filters can been elaborated in several ways. First, we can use a cascade of filters [BFS98] The steps of an algorithm which are being filtered can be defined at di#erent levels of granularity. One extreme is to consider an entire algorithm as one step [MNS 96, KW98] A general formulation structural filtering is proposed in [FMN99] Probabilistic analysis [DP99] shows the e#cacy of arithmetic filters. The filtering of determinants is treated in several papers [Cla92, BBP01, PY01, BY00] Filtering is related to program checking [BK95, BLR93] View a ....
Lutz Kettner and Emo Welzl. One sided error predicates in geometric computing. In Kurt Mehlhorn, editor, Proc. 15th IFIP World Computer Congress, Fundamentals - Foundations of Computer Science, pages 13--26, 1998.
Combinatorial Curve Reconstruction and the Efficient Exact.. - Funke (Correct)
....the repair step is non trivial if the floating point algorithm does not come with a strong guarantee of what it computes. The purpose of restricting filtering to the search steps is precisely to guarantee that errors in predicate evaluations do not corrupt the data structure. Only the paper [KW98] discusses filtering at the algorithm level and the repair step. The main disadvantage of filtering at the algorithm level is that there are no widely applicable techniques for obtaining robust floating point implementations. Of course, filtering at the algorithm level approach also has its ....
L. Kettner and E. Welzl. One sided error predicates in geometric computing. In Kurt Mehlhorn, editor, Proc. 15th IFIP World Computer Congress, Fundamentals - Foundations of Computer Science, pages 13--26, 1998.
Pitfalls in Computing with Pseudorandom Determinants - Gärtner (1999) (Correct)
....will get many duplicates. A huge number of orientation determinants D of point triples will then actually be zero. This means, a point configuration obtained in this way is extremely degenerate, just not what you would expect from truly random points. Exactly in this context, Kettner and Welzl [9] have performed tests to evaluate the precision of floating point arithmetic, as follows. A sequence of n random points is generated, and the consistency of every triple is checked. A triple is called consistent if the different ways to assign the points to p; q and r in (5) all lead to the same ....
L. Kettner and E. Welzl. One sided error predicates in geometric computing. In K. Mehlhorn, editor, Proc. 15th IFIP World Computer Congress, Fundamentals--Foundations of Computer Science, pages 13--26, 1998.
Structural Filtering - A Paradigm for Efficient and Exact .. - Funke, Mehlhorn, Näher (1999) (Correct)
....Second, the repair step is non trivial if the oating point algorithm does not come with a strong guarantee of what it computes. The purpose of restricting ltering to the search steps is precisely to guarantee that errors in predicate evaluations do not corrupt the data structure. Only the paper [KW98] discusses ltering at the algorithm level and the repair step. The main disadvantage of ltering at the algorithm level is that there are no widely applicable techniques for obtaining robust oating point implementations. Of course, ltering at the algorithm level approach also has its ....
L. Kettner and E. Welzl. One Sided Error Predicates in Geometric Computing. In Proc. 15th IFIP World Computer Congress, Fundamentals - Foundations of Computer Science, Kurt Mehlhorn (Eds.), pp. 13-26, August 1998.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC