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Paris, Machine Learning, and the Wonders of Streaming

April 26, 2013 | By Microsoft blog editor

Eiffel Tower, ParisStanding on the banks of the Seine, I found myself marveling at the beauty of “April in Paris” (cue the 1930s song). Perhaps it was the scent of the flowers in bloom in the Jardin du Luxembourg or the warmth of the Continental spring. But, most likely, my contentment stemmed from the success of the just-completed Microsoft Research Machine Learning Summit, which took place April 22 to 24 in the “City of Light” on Le Campus de Microsoft France.

Andrew Blake, director of Microsoft Research CambridgeThe event brought together more than 230 attendees and presenters, including thought leaders from computer science, engineering, statistics, and mathematics. Through keynotes, demos, and panel discussions, we highlighted some of the key challenges in this new era of machine learning and explored the next generation of approaches, techniques, and tools that researchers and scientists need to exploit the information revolution for the benefit of society.

Judea Pearl, professor emeritus at UCLAAs exciting as the in-person event was, I was equally enthused by the reception of our streaming broadcast of key presentations and interviews, which was viewed by some 3,000 people around the globe. The live, online presentation not only made it possible for many more people to view the summit, it gave a broader group of students and researchers an opportunity to engage directly with some of the top experts in the field of machine learning, including Andrew Blake, director of Microsoft Research Cambridge, and Judea Pearl, professor emeritus at UCLA. I was pleased that many from the online audience posed questions about computer vision to Professor Blake, and difficult questions about probability and causality to Professor Pearl.

There was hardly an area of machine learning that wasn’t explored in depth at the summit—from the aforementioned topics of computer vision and causality, to insightful presentations on Bayesian statistics and the use of machine learning techniques in the realm of social media and large-scale learning.

Of course the food was outstanding (it was Paris, after all), and meals were made all the more enjoyable by the stimulating conversation of our companions and the spectacular views of Paris from the thirty-fourth floor of our hotel. But for me, the most exciting moments were the intense discussions I observed taking place during breaks and the social events, and the sense that seeds of exciting new ideas were being planted that would germinate in the months and years ahead.

Chris Bishop, Distinguished Scientist, Microsoft Research Cambridge

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