{"id":452088,"date":"2017-12-29T09:11:56","date_gmt":"2017-12-29T17:11:56","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=452088"},"modified":"2025-08-06T11:57:28","modified_gmt":"2025-08-06T18:57:28","slug":"new-england-machine-learning-day-2018","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/new-england-machine-learning-day-2018\/","title":{"rendered":"New England Machine Learning Day 2018"},"content":{"rendered":"\n\n

Venue:<\/strong><\/p>\n

Microsoft Research New England<\/a>
\nHorace Mann Conference Room
\nOne Memorial Drive
\nCambridge, MA 02142<\/p>\n

Registration is now closed. We hope to see you next year!<\/strong>Opens in a new tab<\/span><\/p>\n

The seventh annual New England Machine Learning Day will take place Monday, May 7, 2018, 10 AM\u20135 PM at Microsoft Research New England, One Memorial Drive, Cambridge, MA 02142. The event will bring together local academics and researchers in machine learning, artificial intelligence, and their application. There will be a lively poster session during lunch, followed by a provocative panel.<\/p>\n

Also, consider joining a very worthwhile hackathon on June 11: New England Machine Learning for Accessibility and Neurodiversity (opens in new tab)<\/span><\/a>.<\/p>\n

Schedule<\/h2>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/strong><\/th>\nSession<\/strong><\/th>\n<\/tr>\n<\/thead>\n
\n
9:55am \u2013 10:00am<\/div>\n<\/td>\n
\n
Opening remarks<\/div>\n<\/td>\n<\/tr>\n
\n
10:00am \u2013 10:30am<\/div>\n<\/td>\n
\n
\n

Aleksander M\u0105dry (opens in new tab)<\/span><\/a>, MIT
\nTowards ML You Can Rely On<\/p>\n<\/div>\n<\/td>\n<\/tr>\n

10:35am \u2013 11:05am<\/td>\nAlexandra Meliou (opens in new tab)<\/span><\/a>,\u00a0UMass Amherst
\nFairness testing: A systems\u2019 perspective on algorithmic bias<\/td>\n<\/tr>\n
11:10am \u2013 11:40am<\/td>\nVivienne Sze (opens in new tab)<\/span><\/a>,\u00a0MIT
\nEnergy-Efficient Deep Learning for Mobile Applications<\/td>\n<\/tr>\n
11:40pm \u2013 1:20pm<\/td>\nLunch and posters<\/td>\n<\/tr>\n
1:20pm \u2013 2:15pm<\/td>\nProvocative Panel, Tina Eliassi-Rad (moderator)
\nPanelists: Carla Brodley, Northeastern, Rania Khalaf, IBM, Michael Littman, Brown, Lester Mackey, MSR, and Josh Tenenbaum, MIT<\/td>\n<\/tr>\n
2:20pm \u2013 2:50pm<\/td>\nDaniel Ritchie (opens in new tab)<\/span><\/a>, Brown
\nLearning Procedural Modeling Programs for Computer Graphics from Examples<\/td>\n<\/tr>\n
2:50pm \u2013 3:20pm<\/td>\nCoffee break<\/td>\n<\/tr>\n
3:20pm \u2013 3:50pm<\/td>\nKate Saenko (opens in new tab)<\/span><\/a>, Boston University
\nAdversarial Techniques for Visual Domain Adaptation<\/td>\n<\/tr>\n
3:55pm \u2013 4:25pm<\/td>\nByron Wallace (opens in new tab)<\/span><\/a>, Northeastern
\nTraining Neural NLP Models in Minimally Supervised Settings<\/td>\n<\/tr>\n
4:30pm \u2013 5:00pm<\/td>\nLucas Janson (opens in new tab)<\/span><\/a>, Harvard University
\nKnockoffs: using machine learning for statistically-rigorous variable selection in nonparametric models<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Organizing committee<\/h2>\n