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Efficient Parallel Learning of Linear Dynamical Systems on SMPs

Efficient Parallel Learning of Linear Dynamical Systems on SMPs

This video was recorded at Carnegie Mellon Machine Learning Lunch seminar. The Machine Learning lunch is a weekly seminar which has the goal of bringing together the different people at CMU working on related fields to discuss their work. In the past a broad range of topics has been discussed: reinforcement learning, machine learning in general, statistical AI, statistical learning theory, robot learning, text learning, etc. The talks have always been enjoyable and have ranged from quite informal to formal conference style talks. It is also a great forum to practice conference talks, bounce around new ideas and for guests from other universities and industry to speak. Currently the talks are sponsored by MLD - the Machine Learning Department of the School of Computer Science. The goal of MLD is slightly broader than that of these talks - it brings together the many departments working on similar topics at CMU. The series has been going on for quite a few years. In earlier days it was called the Reinforcement Learning Lunch because of the emphasis on reinforcement learning. As the topics broadened, the name was changed to the Machine Learning Lunch. Organizing committee: Amr Ahmed, Polo Chau, Steve Hanneke, Sue Ann Hong, Nathan Ratliff This lecture series is being kindly sponsored by Yahoo! Academic Relations

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