Saturday, May 06, 2017

Saturday Morning Videos: Computational Challenges in Machine Learning, Simons Institute, May 1 – May 5, 2017

Santosh VempalaDavid BleiKatherine HellerJohn Langford and Le Song with the Simons Institute at UC Berkeley just organised a workshop on Computational Challenges in Machine Learning this week. The videos can be accessed by following each link.

The aim of this workshop is to bring together a broad set of researchers looking at algorithmic questions that arise in machine learning. The primary target areas will be large-­scale learning, including algorithms for Bayesian estimation and variational inference, nonlinear and nonparametric function estimation, reinforcement learning, and stochastic processes including diffusion, point processes and MCMC. While many of these methods have been central to statistical modeling and machine learning, recent advances in their scope and applicability lead to basic questions about their computational efficiency. The latter is often linked to modeling assumptions and objectives. The workshop will examine progress and challenges and include a set of tutorials on the state of the art by leading experts.

Credits: NASA/JPL-Caltech/SwRI/MSSS/Jason Major
This image, taken by the JunoCam imager on NASA’s Juno spacecraft, highlights a swirling storm just south of one of the white oval storms on Jupiter.
The image was taken on March 27, 2017, at 2:12 a.m. PDT (5:12 a.m. EDT), as the Juno spacecraft performed a close flyby of Jupiter. At the time the image was taken, the spacecraft was about 12,400 miles (20,000 kilometers) from the planet.
Citizen scientist Jason Major enhanced the color and contrast in this image, turning the picture into a Jovian work of art. He then cropped it to focus our attention on this beautiful example of Jupiter’s spinning storms.

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