Join us on Monday, July 9th in San Francisco for a full-day workshop on Big Learning. Featuring CMU's Graphlab and including presentations from Twitter, Pandora, Netflix, Berkeley, GA Tech, Y!, IBM Watson, Intel Labs, MapR, and many more.
The MLconf workshop on large scale machine learning is a meeting place for both academia and industry to discuss upcoming challenges of large scale machine learning and solution methods. GraphLab is Carnegie Mellon’s large scale machine learning framework. The workshop will include demos and tutorials showcasing the next generation of the GraphLab framework, as well as lectures and demos from the top technology companies about their applied large scale machine learning solutions. The workshop will be held on Monday, July 9th in San Francisco. Register today to enjoy early bird registration fee!
Talks
GraphLab Version 2 Overview- Carlos Guestrin, Carnegie Mellon University Large scale ML challenges - Theodore Willke, Intel Labs TBD – Alexander Smola, Yahoo! Labs Bloom: Disorderly Programming for Distributed Systems – Joseph Hellerstein, UC Berkeley Large scale ML learning at MapR – Ted Dunning, MapR Technologies Large scale ML at Pandora – Tao Ye, Pandora Internet Radio TBD – Xavier Amatriain – Netflix Cassovary Graph Processing System – Pankaj Gupta, Twitter TBD – Amol Gothig, IBM Watson Machine learning in One Kings Lane – Mohit Singh, One Kings Lane More talks from our program committee/ external contributors to follow!
Posters/Demos
Green Marl graph processing framework – Dr. Sungpack Hong, Oracle Labs Machine learning benchmark framework – Nicholas Kolegraff, Accenture TBD – Prof. Alexander Gray, Georgia Tech Alpine and MADLib Demo – Steven Hilion, Alpine Data Labs Disk-based Massive Graph Computation – Aapo Kyrola, CMU
Platinum Sponsor: Intel
Gold Sponsors: MapR, Cloudera
Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. All other logos are trademarks of the companies who own them, respectivley.
For more Machine Learning events see mlconf.com and follow @mlconf on twitter