Conference Schedule

8:55-9:00

Introduction & Morning Announcements

9:00-9:40

Large-scale Machine Learning: Deep, Distributed and Multi-Dimensional

Anima Anandkumar
9:40-10:10

The Role of AI and Machine Learning in Creativity

Doug Eck
10:10-10:30

Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

Franziska Bell
10:30-10:55

Tensor Decomposition: A Mathematical Tool for Data Analysis

Tamara G. Kolda
10:55-11:10

Coffee Break

11:10-11:35

Deep Reinforcement Learning with Shallow Trees

Matineh Shaker
11:35-12:00

Can Machine Learning Save the Whales?

Ted Willke
12:00-12:20

Counter Intuitive Machine Learning for the Industrial Internet of Things

Dr. June Andrews
12:20-12:40

Lessons Learnt from building ML Products for enterprise SaaS

LN Renganarayana & Madhura Dudhgaonkar
12:40-2:00

Lunch

2:00-2:30

ML to Cure the World

Xavier Amatriain
2:30-2:55

Personalized User Recommendations at Tinder: The TinVec Approach

Dr. Steve Liu
2:55-3:20

Natural Language Understanding @ Facebook Scale

Rushin Shah
3:20-3:45

Getting Value Out of Chat Data

Daniel Shank
3:45-4:10

Coffee Break

4:10-4:35

I Build The Black Box: Grappling with Product and Policy

Josh Wills
4:35-5:00

Classifying Multi-Variate Time Series at Scale

Ashfaq Munshi
5:00-5:25

Machine Learning Systems at Scale

Jonas Schneider
5:25-5:45

Representation Learning @ Red Hat

Michael Alcorn
5:45-6:00

Closing Announcements, Giveaways & Event Conclusion

The following sponsors made this event possible