{"id":508112,"date":"2018-10-24T18:05:11","date_gmt":"2018-10-25T01:05:11","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=508112"},"modified":"2020-07-07T10:10:09","modified_gmt":"2020-07-07T17:10:09","slug":"neurips-2018","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/neurips-2018\/","title":{"rendered":"Microsoft @ NeurIPS 2018"},"content":{"rendered":"

Venue:<\/strong> Palais des Congr\u00e8s de Montr\u00e9al (opens in new tab)<\/span><\/a>
\n1H5 Place Jean-Paul-Riopelle
\nMontr\u00e9al, Qu\u00e9bec H2Z 1H5
\nCanada<\/p>\n

Website:<\/strong> NeurIPS 2018 (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft is excited to be a Diamond sponsor of the thirty-second annual conference on Neural Information Processing Systems (NIPS). Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops at NIPS. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities with Microsoft.<\/p>\n","protected":false},"featured_media":508535,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"msr_startdate":"2018-12-02","msr_enddate":"2018-12-08","msr_location":"Montreal, Quebec, Canada","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"https:\/\/nips.cc\/Register\/view-registration","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"footnotes":""},"research-area":[13556],"msr-region":[197900],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-508112","msr-event","type-msr-event","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-region-north-america","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"Venue:<\/strong> Palais des Congr\u00e8s de Montr\u00e9al<\/a>\r\n1H5 Place Jean-Paul-Riopelle\r\nMontr\u00e9al, Qu\u00e9bec H2Z 1H5\r\nCanada\r\n\r\nWebsite:<\/strong> NeurIPS 2018<\/a>","tab-content":[{"id":0,"name":"About","content":"Microsoft is excited to be a Diamond sponsor of the 32nd annual conference on Neural Information Processing Systems<\/a>. Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities<\/a> with Microsoft.\r\n

Program Chair<\/h2>\r\nHanna Wallach<\/a>\r\n
\r\n

Tutorial Chair<\/h2>\r\n<\/div>\r\n
\r\n\r\nJenn Wortman Vaughan<\/a>\r\n\r\n<\/div>\r\n

Workshop Organizers<\/h2>\r\nPrateek Jain<\/a> | 2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a>\r\n\r\nAbhishek Gupta | AI for social good<\/a>\r\n\r\nEvelyne Viegas<\/a> | CiML 2018 - Machine Learning competitions \"in the wild\": Playing in the real world or in real time<\/a>\r\n\r\nRich Caruana<\/a> | Critiquing and Correcting Trends in Machine Learning<\/a>\r\n\r\nTristan Naumann<\/a> | Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare<\/a>\r\n\r\nSiddhartha Sen<\/a> | MLSys: Workshop on Systems for ML and Open Source Software<\/a>\r\n\r\nOlya Ohrimenko<\/a> | Privacy Preserving Machine Learning<\/a>\r\n\r\nMarc-Alexandre C\u00f4t\u00e9<\/a>, Wendy Tay<\/a>, Adam Trischler<\/a>, Hal Daum\u00e9 III<\/a>, Nate Kushman<\/a>, Alessandro Sordoni<\/a> | Wordplay: Reinforcement and Language Learning in Text-based Games<\/a>\r\n

Volunteer Workflow Team<\/h2>\r\nChinmay Singh<\/a>"},{"id":1,"name":"Posters","content":"
\r\n\r\n

Tuesday, December 4, 2018<\/h2>\r\n\r\n
\r\n\r\n

Adversarial Multiple Source Domain Adaptation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #107<\/h3>\r\nHan Zhao, Shanghang Zhang, Guanhang Wu, Jose M. F. Moura, Joao P. Costeira, Geoffrey Gordon<\/a>\r\n

FRAGE: Frequency-Agnostic Word Representation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #153<\/h3>\r\nChengyue Gong, Di He<\/a>, Xu Tan<\/a>, Tao Qin<\/a>, Liwei Wang, Tie-Yan Liu<\/a>\r\n

Frequency-Domain Dynamic Pruning for Convolutional Neural Networks<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #67<\/h3>\r\nZhenhua Liu, Jizheng Xu, Xiulian Peng<\/a>, Ruiqin Xiong\r\n

Heterogeneous Bitwidth Binarization in Convolutional Neural Networks<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #69<\/h3>\r\nJosh Fromm, Shwetak Patel, Matthai Philipose<\/a>\r\n

Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\r\nDon Dennis, Chirag Pabbaraju<\/strong>, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a>\r\n

Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #73<\/h3>\r\nMinjia Zhang<\/a>, Xiaodong Liu<\/a>, Wenhan Wang<\/strong>, Jianfeng Gao<\/a>, Yuxiong He<\/a>\r\n

On the Dimensionality of Word Embedding<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #110<\/h3>\r\nZi Yin, Yuanyuan Shen<\/strong>\r\n

The Lingering of Gradients: How to Reuse Gradients Over Time<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #2<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Towards Text Generation with Adversarially Learned Neural Outlines<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #14<\/h3>\r\nSandeep Subramanian, Sai Rajeswar Mudumba, Adam Trischler<\/a>, Alessandro Sordoni<\/a>, Aaron Courville, Chris Pal\r\n

A Dual Framework for Low-rank Tensor Completion<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #146<\/h3>\r\nMadhav Nimishakavi, Bamdev Mishra<\/a>, Pratik Kumar Jawanpuria<\/strong><\/a>\r\n

Bounded-Loss Private Prediction Markets<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #28<\/h3>\r\nRafael Frongillo, Bo Waggoner<\/strong>\r\n

Contamination Attacks in Multi-Party Machine Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #158<\/h3>\r\nJamie Hayes, Olya Ohrimenko<\/a>\r\n

Dialog-based Interactive Image Retrieval<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #55<\/h3>\r\nXiaoxiao Guo, Hui Wu, Yu Cheng<\/strong>, Steven Rennie, Rogerio Schmidt Feris\r\n

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #93<\/h3>\r\nDaya Guo, Duyu Tang<\/a>, Nan Duan<\/a>, Ming Zhou<\/a>, Jian Yin\r\n

Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #94<\/h3>\r\nYizhe Zhang<\/a>, Michel Galley<\/a>, Jianfeng Gao<\/a>, Zhe Gan<\/strong>, Xiujun Li<\/a>, Chris Brockett<\/a>, Bill Dolan<\/a>\r\n

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #85<\/h3>\r\nTianyu He, Tao Qin<\/a>, Tie-Yan Liu<\/a>, Yingce Xia<\/strong>, Xu Tan<\/a>, Di He<\/a>, Zhibo Chen\r\n

Local Differential Privacy for Evolving Data<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\r\nMatthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/strong>\r\n

Precision and Recall for Time Series<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #116<\/h3>\r\nNesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich\r\n

Supervising Unsupervised Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #164<\/h3>\r\nVikas Garg, Adam Kalai<\/a>\r\n

Turbo Learning for Captionbot and Drawingbot<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #54<\/h3>\r\nQiuyuan Huang<\/a>, Pengchuan Zhang<\/a>, Oliver Wu, Lei Zhang<\/a>\r\n\r\n
\r\n\r\n

Wednesday, December 5, 2018<\/h2>\r\n\r\n
\r\n\r\n

Adversarial Text Generation via Feature-Mover's Distance<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #129<\/h3>\r\nLiqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan<\/strong>, Haichao Zhang, Yizhe Zhang<\/a>, Lawrence Carin\r\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #159<\/h3>\r\nSampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/strong>, Zhiwei Steven Wu\r\n

Constructing Unrestricted Adversarial Examples with Generative Models<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #149<\/h3>\r\nYang Song, Rui Shu, Nate Kushman<\/a>, Stefano Ermon\r\n

Global Non-convex Optimization with Discretized Diffusions<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #18<\/h3>\r\nMurat A. Erdogdu, Lester Mackey<\/a>, Ohad Shamir\r\n

Inexact trust-region algorithms on Riemannian manifolds<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #15<\/h3>\r\nHiroyuki Kasai, Bamdev Mishra<\/strong>\r\n

Is Q-Learning Provably Efficient?<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\r\nChi Jin, Zeyuan Allen-Zhu<\/a>, Sebastien Bubeck<\/a>, Michael Jordon\r\n

M-Walk: Learning to Walk over Graphs with Monte Carlo Tree Search<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 | AB #164<\/h3>\r\nYelong Shen<\/strong>, Jianshu Chen, Po-Sen Huang, Yuqing Guo<\/strong>, Jianfeng Gao<\/a>\r\n

On Oracle-Efficient PAC RL with Rich Observations<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #111<\/h3>\r\nChristoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a>\r\n

On the Local Hessian in Back-propagation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #43<\/h3>\r\nHuishuai Zhang<\/a>, Wei Chen<\/a>, Tie-Yan Liu<\/a>\r\n

Recurrent Transformer Networks for Semantic Correspondence<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #119<\/h3>\r\nSeungryong Kim, Stephen Lin<\/strong>, SANG RYUL JEON, Dongbo Min, Kwanghoon Sohn\r\n

Universal Growth in Production Economies<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\r\nSimina Branzei, Ruta Mehta, Noam Nisan<\/strong>\r\n

Weakly Supervised Dense Event Captioning in Videos<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #125<\/h3>\r\nXuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang<\/a>, Wenwu Zhu, Junzhou Huang\r\n

Natasha 2: Faster Non-Convex Optimization Than SGD<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #50<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Coupled Variational Bayes via Optimization Embedding<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #11<\/h3>\r\nBo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao<\/a>, Le Song\r\n

Dual Policy Iteration<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #124<\/h3>\r\nWen Sun, Geoffrey Gordon<\/a>, Wen Sun, J. Andrew Bagnell\r\n

Probabilistic Matrix Factorization for Automated Machine Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\r\nNicolo Fusi<\/a>, Rishit Sheth<\/a>, Melih Elibol<\/strong>\r\n

NEON2: Finding Local Minima via First-Order Oracles<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #45<\/h3>\r\nZeyuan Allen-Zhu<\/a>, Yuanzhi Li\r\n

Teaching Inverse Reinforcement Learners via Features and Demonstrations<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #167<\/h3>\r\nLuis Haug, Sebastian Tschiatschek<\/a>, Adish Singla\r\n\r\n
\r\n\r\n

Thursday, December 6, 2018<\/h2>\r\n\r\n
\r\n\r\n

Contextual bandits with surrogate losses: Margin bounds and efficient algorithms<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\r\nDylan Foster, Akshay Krishnamurthy<\/a>\r\n

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network<\/a>\r\n10:45 AM - 12:45 PM | Room 210&230 AB #89<\/h3>\r\nAditya Kusupati<\/strong>, Manish Singh,\u00a0Kush Bhatia, Ashish Kumar, \u00a0 Prateek Jain<\/a>, Manik Varma<\/a>\r\n

Gaussian Process Prior Variational Autoencoders<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #63<\/h3>\r\nNicolo Fusi<\/a>, Luca Saglietti<\/strong>, Francesco Paolo Casale<\/a>, Adrian Dalca, Jennifer Listgarten\r\n

Learning to Teach with Dynamic Loss Functions<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #155<\/h3>\r\nTao Qin<\/a>, Tie-Yan Liu<\/a>, Fei Tian<\/a>, Yingce Xia<\/strong>, Lijun Wu, Yingce Xia, Lai Jian-Huang\r\n

Byzantine Stochastic Gradient Descent<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #164<\/h3>\r\nDan Alistarh, Zeyuan Allen-Zhu<\/a>, Jerry Li\r\n

Towards Deep Conversational Recommendations<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #118<\/h3>\r\nRaymond Li, Samira Ebrahimi Kahou<\/a>, Hannes Schulz<\/a>,Vincent Michalski, Laurent Charlin, Chris Pal\r\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\r\nKevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Yin Tat Lee, Laurent Massoulie\r\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #63<\/h3>\r\nRaghav Somani<\/strong>, Chirag Gupta, Prateek Jain<\/a>, Praneeth Netrapalli<\/a>\r\n

Community Exploration: From Offline Optimization to Online Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\r\nXiaowei Chen, Weiran Huang, Wei Chen<\/a>, John C.S. Lui\r\n

Constrained Graph Variational Autoencoders for Molecule Design<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #103<\/h3>\r\nQi Liu, Miltos Allamanis<\/a>, Marc Brockschmidt<\/a>, Alexander Gaunt<\/a>\r\n

How To Make the Gradients Small Stochastically<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #74<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Learning Beam Search Policies via Imitation Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB#104<\/h3>\r\nRenato Negrinho, Matthew Gormley, Geoffrey Gordon<\/a>\r\n

Learning SMaLL Predictors<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #98<\/h3>\r\nVikas K. Garg, Ofer Dekel<\/a>, Lin Xiao<\/a>\r\n

Neural Architecture Optimization<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #123<\/h3>\r\nRenqian Luo, Fei Tian<\/a>, Tao Qin<\/a>, Enhon Chen, Tie-Yan Liu<\/a>\r\n

Random Feature Stein Discrepancies<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #78<\/h3>\r\nJonathan Huggins, Lester Mackey<\/a>\r\n\r\n
"},{"id":2,"name":"Spotlight Sessions","content":"

Local Differential Privacy for Evolving Data\r\nTuesday, December 4, 2018 | 3:35 PM\u20133:40 PM | Room 517CD<\/h3>\r\nMatthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/a><\/strong>\r\n

Bounded-Loss Private Prediction Markets\r\nTuesday, December 4, 2018 | 4:05 PM\u20134:10 PM | Room 517CD<\/h3>\r\nRafael Frongillo, Bo Waggoner<\/a><\/strong>\r\n

Precision and Recall for Time Series\r\nTuesday, December 4, 2018 | 4:50 PM\u20134:55 PM | Room 220CD<\/h3>\r\nNesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich\r\n

Supervising Unsupervised Learning\r\nTuesday, December 4, 2018 | 4:55 PM\u20135:00 PM | Room 517CD<\/h3>\r\nVikas Garg, Adam Kalai<\/a><\/strong>\r\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem\r\nWednesday, December 5, 2018 | 9:45 AM\u20139:50 AM | Room 220CD<\/h3>\r\nSampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/a><\/strong>, Zhiwei Steven Wu\r\n

Recurrent Transformer Networks for Semantic Correspondence\r\nWednesday, December 5, 2018 | 10:20 AM\u201310:25 AM | Room 220E<\/h3>\r\nSeungryong Kim, Stephen Lin<\/a><\/strong>, Sang Ryul Jeon, Dongbo Min, Kwanghoon Sohn\r\n

On Oracle-Efficient PAC RL with Rich Observations\r\nWednesday, December 5, 2018 | 10:25 AM\u201310:30 AM | Room 220CD<\/h3>\r\nChristoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/strong>\r\n

Natasha 2: Faster Non-Convex Optimization Than SGD\r\nWednesday, December 5, 2018 | 4:40 PM\u20134:45 PM | Room 517CD<\/h3>\r\nZeyuan Allen-Zhu<\/a><\/strong>\r\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds\r\nThursday, December 6, 2018 | 4:55 PM\u20135:00 PM | Room 220CD<\/h3>\r\nRaghav Somani,<\/strong> Chirag Gupta,<\/strong> Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/strong>"},{"id":3,"name":"Oral Presentations","content":"

On the Dimensionality of Word Embedding\r\nThursday, December 6, 2018 | 10:05AM \u2013 10:20AM | Room 220E<\/h3>\r\nZi Yin, Yuanyuan Shen<\/strong>\r\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>\r\nThursday, December 6, 2018 | 3:50 PM\u20134:05 PM | Room 517CD<\/h3>\r\nKevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Laurent Massouli\u00e9, Yin Tat Lee"},{"id":4,"name":"Workshops","content":"

2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a>\r\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nInvited speaker: Manik Varma<\/a>\r\n

MLSys: Workshop on Systems for ML and Open Source Software<\/a>\r\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nAccepted paper: Matteo Interlandi,\u00a0Sergiy Matusevych,\u00a0Saeed Amizadeh, Shauheen Zahirazami, Markus Weimer<\/strong> | Machine Learning at Microsoft with ML.NET\r\n\r\nAccepted paper:\u00a0Gyeong-In Yu,\u00a0Saeed Amizadeh<\/b>,\u00a0Byung-Gon Chun, Markus Weimer, Matteo Interlandi<\/b> | Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach\r\n\r\nAccepted paper: Yaoqing Yang, Matteo Interlandi<\/b>, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer<\/b> | Coded Elastic Computing\r\n

2nd Conversational AI: \u201cToday's Practice and Tomorrow's Potential\u201d<\/a>\r\nFriday, December 7, 2018 | 9:00 AM-5:30 PM<\/h3>\r\nAccepted paper: Elnaz Nouri<\/a>, Ehsan Hosseini-Asl | Toward Scalable Neural Dialogue State Tracking Model\r\n

Workshop on Security in Machine Learning<\/a>\r\nFriday, December 7, 2018 | 11:00 AM-1:30 PM<\/h3>\r\nKeynote: danah boyd<\/a>\r\n

Interpretability and Robustness in Audio, Speech, and Language<\/a>\r\nSaturday, December 8, 2018 | 9:00 AM-9:30 AM<\/h3>\r\nInvited Speaker 1: Rich Caruana<\/a>\r\n

Relational Representation Learning<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\n10:15 AM spotlight talk: Saeed Amizadeh |<\/strong> A Neural Framework for Learning DAG to DAG Translation\r\n<\/strong>\r\n

Privacy Preserving Machine Learning<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nPoster: Bolin Ding, Janardhan Kulkarni and Sergey Yekhanin<\/strong> | A Distributed Algorithm For Differentially Private Heavy Hitters <\/a>\r\n\r\nPoster: Joshua Allen, <\/strong>Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olya Ohrimenko and Sergey Yekhanin<\/strong> | An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors <\/a>\r\n

Second Workshop on Machine Learning for Creativity and Design<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nPoster: Khyatti Gupta, Sonam Damani, Kedhar Nath Narahari | <\/strong>Using AI to Design Stone Jewelry\r\n

Wordplay: Reinforcement and Language Learning in Text-based Games<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nInvited speaker: Katja Hofmann<\/strong>\r\n

Machine Learning Open Source Software 2018: Sustainable communities<\/a>\r\nSaturday, December 8, 2018 | 8:30 AM-5:35 PM<\/h3>\r\n11:00AM poster: Mayank Meghwankshi<\/strong>, Pratik Jawanpuria<\/strong>, Anoop Kunchukuttan<\/strong>, Hiroyuki Kasai, Bamdev Michra<\/strong>, McTorch | a manifold optimization library for deep learning\r\n\r\n11:00AM poster: Markus Weimer<\/a> | Machine Learning at Microsoft with ML.NET"},{"id":5,"name":"Demonstrations","content":"

Booth Demos<\/h2>\r\nCome by our booth (#203) to see demos of our latest research. See schedule below:\r\n
<\/div>\r\n

Sunday, December 2<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:00 AM\u201310:30 AM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:30 PM\u20131:15 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:15 PM\u20132:00 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
4:00 PM\u20134:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
6:30 PM\u20137:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Monday, December 3<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:30 AM\u201311:00 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:00 PM\u20131:45 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:45 PM\u20132:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
4:30 PM\u20135:00 PM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
6:30 PM\u20137:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
7:30 PM\u20138:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Tuesday, December 4<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:40 AM\u201310:05 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Wednesday, December 5<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:20 AM\u20139:45 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nTextWorld<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Thursday, December 6<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:20 AM\u20139:45 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Friday, December 7<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:30 AM\u201311:00 AM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:00 PM\u201312:45 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:00 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:00 PM\u20133:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Conference Demo Sessions<\/h2>\r\n

ML on Resource Constrained Edge Devices \u2013 GesturePod!<\/a>\r\nSunday, December 2, 2018 | 2:00 PM\u20136:30 PM | Room 510ABCD<\/h3>\r\nShishir G. Patil, Don Kurian Dennis, Harsha Vardhan Simhadri, Prateek Jain<\/a>\r\n<\/strong>\r\n

Ruuh: A Deep Learning Based Conversational Social Agent<\/a>\r\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D3<\/h3>\r\nManoj Chinnakotla, Kedhar Narahari, Nitya Raviprakash, Umang Gupta, Ankush Chatterjee, Sneha Magapu, Sonam Damani, Abhishek Mathur, Puneet Agrawal, Meghana Joshi, Khyatti Gupta<\/strong>\r\n

TextWorld: A Learning Environment for Text-based Games<\/a>\r\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D10<\/h3>\r\nEric Yuan<\/a>, Wendy Tay<\/a>, Marc-Alexandre C\u00f4t\u00e9<\/a>\r\n

Multi-Word Imputation and Sentence Expansion<\/a>\r\nWednesday, December 5, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D7<\/h3>\r\nDouglas Orr, Osman Ramadan, <\/strong>Dmitry Stratiychuk, B\u0142a\u017cej Czapp<\/strong>"},{"id":6,"name":"Analytics","content":"[row]\r\n[card title=\" NeurIPS Conference Analytics\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/academic\/articles\/neurips-conference-analytics\/\" ]\r\nMicrosoft Academic | November 23, 2018\r\n

<\/h3>\r\nThe Microsoft Academic Graph makes it possible to gain analytic insights about any of the entities within it: publications, authors, institutions, topics, journals, and conferences.[\/card]\r\n[\/row]"}],"msr_startdate":"2018-12-02","msr_enddate":"2018-12-08","msr_event_time":"","msr_location":"Montreal, Quebec, Canada","msr_event_link":"https:\/\/nips.cc\/Register\/view-registration","msr_event_recording_link":"","msr_startdate_formatted":"December 2, 2018","msr_register_text":"Watch now","msr_cta_link":"https:\/\/nips.cc\/Register\/view-registration","msr_cta_text":"Watch now","msr_cta_bi_name":"Event Register","featured_image_thumbnail":"\"Bonsecours","event_excerpt":"Microsoft is excited to be a Diamond sponsor of the thirty-second annual conference on Neural Information Processing Systems (NIPS). Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops at NIPS. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities with Microsoft.","msr_research_lab":[199562,199565,199571,212740,199560],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[416408],"related-opportunities":[],"related-publications":[506933,633429,543570,543717,392960],"related-videos":[],"related-posts":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-event"}],"version-history":[{"count":10,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112\/revisions"}],"predecessor-version":[{"id":672624,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112\/revisions\/672624"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/508535"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=508112"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=508112"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=508112"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=508112"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=508112"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=508112"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=508112"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=508112"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=508112"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}