Very fast interactive visualization of large sets of high-dimensional data

Procedia Computer Science

Volumn 51, Issue 1, 2015, Pages 572-581

  Dzwinel, Witold ^a   Wcisło, Rafał ^a  

^a AGH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Poland)

Author keywords

Interactive visualization; Multidimensional scaling; Particle based stress minimization

Indexed keywords

ALGORITHMS; CLUSTERING ALGORITHMS; VISUALIZATION;

DATA REPOSITORIES; DIMENSIONALITY REDUCTION ALGORITHMS; HIGH DIMENSIONAL DATA; INTERACTIVE VISUALIZATIONS; MEMORY COMPLEXITY; MULTI-DIMENSIONAL SCALING; ORDERS OF MAGNITUDE; STATE OF THE ART;

DATA VISUALIZATION;

EID: 84939178884     PISSN: None     EISSN: 18770509     Source Type: Conference Proceeding    
DOI: 10.1016/j.procs.2015.05.325     Document Type: Conference Paper

References (20)

1. M. Andrecut. Molecular dynamics multidimensional scaling. Physics Letters A, 373(23-24):2001-2006, 2009.
2. Jan De Leeuw and Patrick Mair. Multidimensional scaling using majorization: Smacof in r. Department of Statistics, UCLA, 2011.
3. Witold Dzwinel and Jan Blasiak. Method of particles in visual clustering of multi-dimensional and large data sets. Future Generation Computer Systems, 15(3):365-379, 1999.
4. Samuel G. Fadel, Francisco M. Fatore, Felipe S. L. G. Duarte, and Fernando V. Paulovich. Loch: A neighborhood-based multidimensional projection technique for high-dimensional sparse spaces. Neurocomputing, 150, Part B (0): 546-556, 2015.
5. S. L. France and J. D. Carroll. Two-way multidimensional scaling: A review. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 41(5):644-661, Sept 2011.
6. G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
7. Stephen Ingram and Tamara Munzner. Dimensionality reduction for documents with nearest neighbor queries. Neurocomputing, 150, Part B (0): 557-569, 2015.
8. Stephen Ingram, Tamara Munzner, and Marc Olano. Glimmer: Multilevel mds on the gpu. Visualization and Computer Graphics, IEEE Transactions on, 15(2):249-261, March 2009.
9. Tomoharu Iwata, Neil Houlsby, and Zoubin Ghahramani. Active learning for interactive visualization. Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, pages 342-350, 2013.
10. Daniel Keim, Huamin Qu, and Kwan-Liu Ma. Big-data visualization. Computer Graphics and Applications, IEEE, 33(4):20-21, July 2013.
11. Robson Motta, Rosane Minghim, Alneu de Andrade Lopes, and Maria Cristina F. Oliveira. Graphbased measures to assist user assessment of multidimensional projections. Neurocomputing, 150, Part B (0): 583-598, 2015.
12. Piotr Pawliczek and Witold Dzwinel. Interactive data mining by using multidimensional scaling. Procedia Computer Science, 18(0):40-49, 2013. 2013 International Conference on Computational Science.
13. Piotr Pawliczek, Witold Dzwinel, and David A. Yuen. Visual exploration of data by using multidimensional scaling on multicore cpu, gpu, and mpi cluster. Concurrency and Computation: Practice and Experience, 26(3):662-682, 2014.
14. Piotr Pawliczek, Witold Dzwinel, and David A. Yuen. Interactive data exploration with multithread mic computer architecture. International Conference on Artificial Intelligence and Soft Computing. ICAISC-2015, June 14-18, Zakopane, Poland, 2015 (submitted for publication).
15. Ruslan Salakhutdinov and Geoffrey Hinton. Semantic hashing. International Journal of Approximate Reasoning, 50(7):969-978, 2009.
16. Joshua B. Tenenbaum, Vin de Silva, and John C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, 2000.
17. Laurens Van Der Maaten. Accelerating t-sne using tree-based algorithms. J. Mach. Learn. Res., 15(1):3221-3245, January 2014.
18. Laurens Van der Maaten and Geoffrey Hinton. Visualizing data using t-sne. Journal of Machine Learning Research, 9(2579-2605):85, 2008.
19. Laurens JP van der Maaten, Eric O Postma, and H Jaap van den Herik. Dimensionality reduction: A comparative review. Journal of Machine Learning Research, 10(1-41):66-71, 2009.
20. Zhao Zhang, Tommy W. S. Chow, and Mingbo Zhao. Trace ratio optimization-based semisupervised nonlinear dimensionality reduction for marginal manifold visualization. Knowledge and Data Engineering, IEEE Transactions on, 25(5):1148-1161, May 2013.