All Images
Research News
Learning from distributed data
A graphical example of a probabilistic model used to classify stars from the Kepler
Dataset. Different colors represent different types of stars projected into a 3-D feature space.
Credit: Trilce Estrada, Deptartment of Computer Science, University of New Mexico
Download the high-resolution PNG version of the image. (291.7 KB)
Use your mouse to right-click (Mac users may need to Ctrl-click) the link above and choose the option that will save the file or target to your computer.
_f.jpg)
Trilce Estrada-Piedra, an assistant professor in the Department of Computer Science, University of New Mexico.
Credit: Trilce Estrada, Department of Computer Science, University of New Mexico
Download the high-resolution JPG version of the image. (51.2 KB)
Use your mouse to right-click (Mac users may need to Ctrl-click) the link above and choose the option that will save the file or target to your computer.
The goal of this project is to enable distributed learning in domains where the standalone or centralized processing of results are infeasible. Distributed learning -- allowing scientists to learn from datasets that cannot be shared or placed in a central location -- is important for scientific discovery.
Credit: Trilce Estrada, Department of Computer Science, University of New Mexico
Download the high-resolution JPG version of the image. (301.7 KB)
Use your mouse to right-click (Mac users may need to Ctrl-click) the link above and choose the option that will save the file or target to your computer.