Microsoft @ NIPS 2017
Lieu: Long Beach, California
Venue: Long Beach Convention Center (opens in new tab)
Symposia: December 4, 2017
Demonstrations: December 5–6, 2017
Workshops: December 8–9, 2017
Website: Neural Information Processing Systems (opens in new tab)
Machine learning opportunities at Microsoft:
Click here for opportunities in China (opens in new tab)
Click here for opportunities in India (opens in new tab)
Click here for opportunities in Munich (opens in new tab)
Click here for opportunities in the UK (opens in new tab)
Click here for opportunities in the US (opens in new tab)
Paper Legend card game:
Printable version – part 1 (opens in new tab), part 2 (opens in new tab)
Cloud AI Research Challenge:
Microsoft is excited to be a Platinum sponsor of the thirty-first annual conference on Neural Information Processing Systems (NIPS) (opens in new tab). Over 80 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops at NIPS (see schedule below). Stop by our booth (#315, Exhibit Hall B) to see HoloLens and Windows Mixed Reality in action, as well as to find out about career opportunities at Microsoft and enter for your chance to win an Xbox One X (opens in new tab) gaming console. Follow @MSFTResearch (opens in new tab) for the latest information coming from the event.
NIPS organizing committee
Hanna Wallach, Program Co-chair
Jenn Wortman Vaughan, Tutorial chair
Markus Weimer, Demonstration and competition chair
Workshop organizers
Evelyne Viegas, Machine Learning Challenges as a Research Tool (opens in new tab)
Nicolo Fusi, Machine Learning in Computational Biology (opens in new tab)
Siddhartha Sen, ML Systems Workshop (opens in new tab)
Alekh Agarwal, OPT 2017: Optimization for Machine Learning (opens in new tab)
Jennifer Wortman Vaughan, Learning in the Presence of Strategic Behavior (opens in new tab)
Manik Varma, Extreme Classification: Multi-class & Multi-label Learning in Extremely Large Label Spaces (opens in new tab)
Vasilis Syrgkanis, Learning in the Presence of Strategic Behavior (opens in new tab)
Symposium organizers
Patrice Simard, Interpretable Machine Learning (opens in new tab)
Rich Caruana, Interpretable Machine Learning (opens in new tab)
Invited speaker
December 5 @ 1:50–2:40 PM | Kate Crawford, The Trouble with Bias (opens in new tab)
Careers at Microsoft information session
December 6 @ 12:30–1:20 PM | Eric Horvitz, Christopher Bishop, Jennifer Chayes, and Mir Rosenberg
Spotlight sessions
December 5 @ 3:30–3:35 PM | Clustering Billions of Reads for DNA Data Storage (opens in new tab)
Cyrus Rashtchian, Konstantin Makarychev, Luis Ceze, Karin Strauss, Sergey Yekhanin, Djordje Jevdjic, Miklos Racz, and Siena Ang
December 6 @ 11:20–11:25 AM | Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski, Yishay Mansour, Shay Moran, and Amir Yehudayoff
December 6 @ 5:15–5:20 PM | Repeated Inverse Reinforcement Learning (opens in new tab)
Kareem Amin, Nan Jiang, and Satinder Singh
Oral presentations
December 5 @ 10:55–11:00 AM | Robust Optimization for Non-Convex Objectives
Yaron Singer, Robert S Chen, Vasilis Syrgkanis, and Brendan Lucier
December 6 @ 4:20–4:35 PM | Off-policy evaluation for slate recommendation (opens in new tab)
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miro Dudik, John Langford, Damien Jose, and Imed Zitouni