-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathreferences.tex
58 lines (42 loc) · 3.12 KB
/
references.tex
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
%%%%%%%%%%%%%%%%%%%%%%%% referenc.tex %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% sample references
% %
% Use this file as a template for your own input.
%
%%%%%%%%%%%%%%%%%%%%%%%% Springer-Verlag %%%%%%%%%%%%%%%%%%%%%%%%%%
%
% BibTeX users please use
% \bibliographystyle{}
% \bibliography{}
%
\begin{thebibliography}{99.}%
% and use \bibitem to create references.
%
% Use the following syntax and markup for your references if
% the subject of your book is from the field
% "Mathematics, Physics, Statistics, Computer Science"
%
% Contribution
\bibitem{H.Samet} H. Samet. The Design and Analysis of Spatial Data Structures. Addison-Wesley, Reading, MA, 1989.
\bibitem{D.E.Knuth} D. E. Knuth.: The Art of Computer Programming: Sorting and Searching, vol. 3. In:Addison-Wesley, Reading, MA, 1973.
\bibitem{J.L.Bentley} J. L. Bentley and J. H. Friedman. Data structures for range searching. ACM Computing Surveys, 11(4):397–409, December 1979.
\bibitem{R.A.Finkel} R. A. Finkel and J. L. Bentley. Quadtrees: A data structure for retrieval on composite keys. Acta Informatica, 4(1):1–9, 1974.
\bibitem{J.A.Orenstein} J. A. Orenstein. Multidimensional tries used for associative searching. Information Processing Letters, 14(4):150–157, June 1982.
\bibitem{M.Tamminen} M. Tamminen. The EXCELL method for efficient geometric access to data. Series Acta Polytechnica Scandinavica, 1981. Also Mathematics and Computer Science Series No. 34.
\bibitem{J.Nievergelt} J. Nievergelt, H. Hinterberger, and K. C. Sevcik. The grid file: An adaptable, symmetric multikey file structure. ACM Transactions on Database Systems, 9(1):38–71, March 1984.
\bibitem{Olivier Bachem} Olivier Bachem, Mario Lucic, and Andreas Krause. 2018. Scalable k -Means Clustering via Lightweight Coresets. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '18). ACM, New York, NY, USA, 1119-1127. DOI: https://doi.org/10.1145/3219819.3219973
\bibitem{Songrit Maneewongvatana} Songrit Maneewongvatana and David M. Mount: Its okay to be skinny, if your friends are fat. 4th Annual CGC Workshop on Comptutational Geometry, 1999.
\bibitem{Ashok Suthar} Ashok Suthar, Kumari Oseen Gupta, Pasunuri Raghunadh, Vadlamudi China Venkaiah, Subba Rao Y V and Rukma Rekha N: CKDTree: An improved KD-Tree Construction Algorithm Using Coresets for k-NN based Classification. Communicated, 2019.
% Online Document
\bibitem{Spatial KDTree} Spatial KDTree,
\url{https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.KDTree.html}
\bibitem{J.L.Bentley1} J. L. Bentley. Decomposable searching problems. Inform. Process. Lett., 8:244–
251, 1979.
% Online Document
\bibitem{Dataset} Datasets,
\url{https://archive.ics.uci.edu/ml/datasets.php, \\ https://archive.ics.uci.edu/ml/datasets.php}
\bibitem{Parikshit Ram} Parikshit Ram, Kaushik Sinha: Revisiting kd-tree for Nearest Neighbor Search, KDD ’19, August 4–8, 2019, Anchorage, AK, USA.
\bibitem{Meena Mahajana} Meena Mahajana, Prajakta Nimbhorkara, Kasturi Varadarajanb: The Planar k-means Problem is NP-hard, Theoretical Computer Science,
Volume 442, 13 July 2012, Pages 13-21.
%
\end{thebibliography}