LCCC : NIPS
2010 Workshop on |
Call For Papers========================================================================= CALL FOR PAPERS Learning on Cores, Clusters, and Clouds NIPS 2010 Workshop, Whistler, British Columbia, Canada http://lccc.eecs.berkeley.edu/ -- Submission Deadline: October 17, 2010 -- ========================================================================= |
In the current era of web-scale datasets, high throughput biology, and
multilanguage machine translation, modern datasets no longer fit on a
single computer and traditional machine learning algorithms often have
prohibitively long running times. Parallel and distributed machine
learning is no longer a luxury; it has become a necessity. Moreover,
industry leaders have already declared that clouds are the future of
computing, and new computing platforms such as Microsoft's Azure and
Amazon's EC2 are bringing distributed computing to the masses.
The machine learning community is reacting to this trend in computing by developing new parallel and distributed machine learning techniques. However, many important challenges remain unaddressed. Practical distributed learning algorithms must deal with limited network resources, node failures and nonuniform network latencies. In cloud environments, where network latencies are especially large, distributed learning algorithms should take advantage of asynchronous updates. Many similar issues have been addressed in other fields, where distributed computation is more mature, such as convex optimization and numerical computation. We can learn from their successes and their failures. The one day workshop on "Learning on Cores, Clusters, and Clouds" aims to bring together experts in the field and curious newcomers, to present the state-of-the-art in applied and theoretical distributed learning, and to map out the challenges ahead. The workshop will include invited and contributed presentations from leaders in distributed learning and adjacent fields. We would like to invite short high-quality submissions on the following topics:
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