Conference Schedule

9:00-9:45

Online Data Mining: PCA and K-Means

Edo Liberty, Yahoo
9:45-10:10

Causal Inference and Explanation to Improve Human Health

Samantha Kleinberg, Stevens Institute
10:10-10:30

Say What You Mean: Scaling Machine Learning Algorithms Directly from Source Code

Braxton McKee, Ufora
10:30-10:40

Data Science in the Newsroom

Geetu Ambwani, Huffington Post
10:40-10:55

Coffee Break

Videos Provided by Welch Labs
10:55-11:20

Predicting the Future Using Deep Adversarial Networks: Learning With No Labeled Data

Soumith Chantala, Facebook Torch
11:20-11:45

Training Recurrent Neural Networks at Scale

Erich Elsen, Baidu Research
11:45-12:10

Sharing and Growing the World's Knowledge with Machine Learning

Lei Yang, Quora
12:10-12:30

Discovery of Latent Factors in High-dimensional Data Using Tensor Methods

Furong Huang, MLconf Industry Research Award Winner, UCI
12:30-2:00

Lunch

Videos by Welch Labs, Training by Metis Data Science Boot Camp
2:00-2:40

Using EEG and Azure Machine Learning to Perform Lie Detection

Jennifer Marsman, Microsoft
2:40-3:05

Scripts that Scale with F# and mbrace.io

Mathias Brandewinder, F#/Azure, Clear Lines Consulting
3:05-3:30

Scaling Spark – Vertically

Dr. Ike Nassi, TidalScale
3:30-3:50

Coffee Break

Videos Provided by Welch Labs
3:50-4:15

Teaching K-Means New Tricks

Sergei Vassilvitskii, Google
4:15-4:40

Conversational Language Understanding

Kaheer Suleman, Maluuba
4:40-5:05

Beyond the Classifier, Inspiration from Engineering Algorithms

Yael Elmatad, Tapad
5:10-5:30

Machine Learning for Display Advertising at Scale

Damien Lefortier, Criteo
5:30-6:00

Book Giveaways and Event Conclusion

The following sponsors made this event possible