PIVE: Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering

Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, Haesun Park

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

One of the key advantages of visual analytics is its capability to leverage both humans's visual perception and the power of computing. A big obstacle in integrating machine learning with visual analytics is its high computing cost. To tackle this problem, this paper presents PIVE (Per-Iteration Visualization Environment) that supports real-time interactive visualization with machine learning. By immediately visualizing the intermediate results from algorithm iterations, PIVE enables users to quickly grasp insights and interact with the intermediate output, which then affects subsequent algorithm iterations. In addition, we propose a widely-applicable interaction methodology that allows efficient incorporation of user feedback into virtually any iterative computational method without introducing additional computational cost. We demonstrate the application of PIVE for various dimension reduction algorithms such as multidimensional scaling and t-SNE and clustering and topic modeling algorithms such as k-means and latent Dirichlet allocation.

Original languageEnglish
Pages1001-1009
Number of pages9
Publication statusPublished - 2017 Jan 1
Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
Duration: 2017 Feb 42017 Feb 10

Other

Other31st AAAI Conference on Artificial Intelligence, AAAI 2017
CountryUnited States
CitySan Francisco
Period17/2/417/2/10

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Visualization
Learning systems
Computational methods
Costs
Feedback

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Kim, H., Choo, J., Lee, C., Lee, H., Reddy, C. K., & Park, H. (2017). PIVE: Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering. 1001-1009. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.

PIVE : Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering. / Kim, Hannah; Choo, Jaegul; Lee, Changhyun; Lee, Hanseung; Reddy, Chandan K.; Park, Haesun.

2017. 1001-1009 Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.

Research output: Contribution to conferencePaper

Kim, H, Choo, J, Lee, C, Lee, H, Reddy, CK & Park, H 2017, 'PIVE: Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering' Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States, 17/2/4 - 17/2/10, pp. 1001-1009.
Kim H, Choo J, Lee C, Lee H, Reddy CK, Park H. PIVE: Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering. 2017. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.
Kim, Hannah ; Choo, Jaegul ; Lee, Changhyun ; Lee, Hanseung ; Reddy, Chandan K. ; Park, Haesun. / PIVE : Per-Iteration visualization environment for real-time interactions with dimension reduction and clustering. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.9 p.
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