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Showing posts with label NIPS. Show all posts
Showing posts with label NIPS. Show all posts

Thursday, 23 February 2012

Announcing Google-hosted workshop videos from NIPS 2011

Posted on 08:00 by Unknown
Posted by John Blitzer and Douglas Eck, Google Research

At the 25th Neural Information Processing Systems (NIPS) conference in Granada, Spain last December, we engaged in dialogue with a diverse population of neuroscientists, cognitive scientists, statistical learning theorists, and machine learning researchers. More than twenty Googlers participated in an intensive single-track program of talks, nightly poster sessions and a workshop weekend in the Spanish Sierra Nevada mountains. Check out the NIPS 2011 blog post for full information on Google at NIPS.

In conjunction with our technical involvement and gold sponsorship of NIPS, we recorded the five workshops that Googlers helped to organize on various topics from big learning to music. We’re now pleased to provide access to these rich workshop experiences to the wider technical community.

Watch videos of Googler-led workshops on the YouTube Tech Talks Channel:
  • Big Learning: Algorithms, Systems, and Tools for Learning at Scale by Joseph Gonzalez, Sameer Singh, Graham Taylor, James Bergstra, Alice Zheng, Misha Bilenko, Yucheng Low, Yoshua Bengio, Michael Franklin, Carlos Guestrin, Andrew McCallum, Alexander Smola, Michael Jordan, Sugato Basu (Googler)
  • Domain Adaptation Workshop: Theory and Application by John Blitzer, Corinna Cortes, Afshin Rostamizadeh (all Googlers)
  • Learning Semantics by Antoine Bordes, Jason Weston (Googler), Ronan Collobert, Leon Bottou
  • Sparse Representation and Low-rank Approximation by Ameet Talwalkar, Lester Mackey, Mehryar Mohri (Googler), Michael Mahoney, Francis Bach, Mike Davies, Remi Gribonval, Guillaume Obozinski
  • International Workshop on Music and Machine Learning: Learning from Musical Structure by Rafael Ramirez, Darrell Conklin, Douglas Eck (Googler), Ryan Rifkin (Googler)


To highlight a few workshops: The Domain Adaptation workshop organized by Google, which fused theoretical and practical domain adaptation, featured invited talks from Shai Ben-David and Googler Mehryar Mohri from the theory side and Dan Roth from the applications side. This was just next door to Googlers Doug Eck and Ryan Rifkin's workshop on Machine Learning and Music, with musical demonstrations loud enough for the next-door neighbors to ask them to “turn it down a bit, please.” In addition to the Googler-run workshops, the Integrating Language and Vision workshop showcased invited talks by Google postdoctoral fellow Percy Liang on the pragmatics of visual scene description and Josh Tenenbaum on physical models as a cognitive plausible mechanism for bridging language and vision. Finally, Google consultant Andrew Ng was one of the organizers of the Deep Learning and Unsupervised Feature Learning, which offered an extended tutorial, several inspiring talks, and two panel discussions (one with Googler Samy Bengio as panelist) exploring the question of “How deep is deep?”

As the workshop weekend drew to a close, an airline strike in Spain left NIPS attendees scrambling to get home for the holidays. We hope the skies look clear for 2012 when NIPS lands in Google’s neck of the woods, Lake Tahoe!
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Posted in conferences, Natural Language Processing, NIPS | No comments

Thursday, 27 January 2011

Google at NIPS 2010

Posted on 07:30 by Unknown
Posted by Slav Petrov, Doug Aberdeen, and Lisa McCracken, Google Research

The machine learning community met in Vancouver in December for the 24th Neural Information Processing Systems Conference (NIPS). As always, the single-track program of the main conference featured a number of outstanding talks, followed by interesting late night poster sessions. A record number of workshops covered a wide variety of topics, while allocating sufficient time for skiing in Whistler - after all, many of the most interesting research conversations happen while riding the lift in-between ski runs. This year’s conference also featured a symposium dedicated to Sam Roweis, providing a retrospective on Sam’s life and work. Sam, a fellow Googler and professor at NYU, was at the heart of the NIPS community and is terribly missed.

As always, Google was involved in various ways with NIPS. Here at Google, we take a data-driven approach when solving problems. Therefore, Machine Learning is in one way or another at the core of most of the things that we do. It is therefore unsurprising that many Googlers helped shape the program of the conference or were in the audience. This year, three Googlers served as area chairs and even more were reviewers. Googlers also co-authored the following papers:
  • Label Embedding Trees for Large Multi-Class Tasks by Samy Bengio and Jason Weston
  • Learning Bounds for Importance Weighting by Corinna Cortes, Yishay Mansour, and Mehryar Mohri
  • Online Learning in the Manifold of Low-Rank Matrices by Uri Shalit, Daphna Weinshall, and Gal Chechik
  • Deterministic Single–Pass Algorithm for LDA by Issei Sato, Kenichi Kurihara, and Hiroshi Nakagawa
  • Distributed Dual Averaging In Networks by John Duchi, Alekh Agarwal, and Martin Wainwright

Additionally, Googlers co-organized three well attended workshops:
  • Coarse–to–Fine Learning and Inference by Ben Taskar, David Weiss, Benjamin Sapp, and Slav Petrov
  • Low–rank Methods for Large–scale Machine Learning by Arthur Gretton, Michael Mahoney, Mehryar Mohri, and Ameet Talwalkar
  • Learning on Cores, Clusters, and Clouds by John Duchi, Ofer Dekel, John Langford, Lawrence Cayton, and Alekh Agarwal

Finally, Yoram Singer gave a great talk on Learning Structural Sparsity at the Sam Roweis symposium and Googlers presented the following talks during the workshops:
  • Online Learning in the Manifold of Low–Rank Matrices by Uri Shalit, Daphna Weinshall, and Gal Chechik
  • Distributed MAP Inference for Undirected Graphical Models by Sameer Singh, Amar Subramanya, Fernando Pereira, and Andrew McCallum
  • MapReduce/Bigtable for Distributed Optimization by Keith Hall, Scott Gilpin and Gideon Mann
  • Self-Pruning Prediction Trees by Sally Goldman
  • Web Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings by Jason Weston, Samy Bengio, and Nicolas Usunier
  • Coarse–to–fine Decoding for Parsing and Machine Translation by Slav Petrov

Overall, it was a very successful conference and it was good to be back in Vancouver one last time. This coming year NIPS 2011 will be in Granada, Spain. Hasta luego!
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Posted in conference, NIPS, Publications | No comments
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