The 2016 Machine Learning Conference in SF is scheduled for November 11th, 2016 at Hotel Nikko. Located at the heart of picturesque San Francisco, this venue boasts a large meeting space with natural light, views of the bay, and with several screens–you won’t miss a single slide of your favorite ML presentations.

Conference Schedule

8:00-8:55

Breakfast & Registration

8:55-9:00

Opening Announcements

Courtney Burton & Nick Vasiloglou
9:00-9:45

Machine Learning with TensorFlow

Rajat Monga, Engineering Director, TensorFlow, Google
9:45-10:10

Neural Turing Machines: Perils and Promise

Daniel Shank, Data Scientist, Talla
10:10-10:35

Using Deep Reinforcement Learning for Dialogue Systems

Harm van Seijen, Research Scientist, Maluuba
10:35-10:40

MLconf Industry Impact Student Research Award Recipient Announced

Courtney Burton & Nick Vasiloglou
10:40-10:55

Coffee Break

10:55-11:20

Being Smart with Art

Guy Lebanon, Director, Machine Learning and Data Science, Netflix
11:20-11:40

Before the Model: How Machine Learning Products Start, with Examples from Airbnb

Elena Grewal, Data Science Manager, Airbnb
11:40-12:00

Amazon Search: The Joy of Ranking Products

Daria Sorokina, Applied Scientist, A9.com (Amazon)
12:00-12:20

Personalized Content Blending In The Pinterest Homefeed

Stephanie deWet, Software Engineer, Pinterest
12:20-12:35

A General Framework for Communication-Efficient Distributed Optimization

Virginia Smith, Researcher, UC Berkeley
12:35-2:00

Lunch / Interpreting Black-Box Models with Applications to Healthcare

Brian Lucena
2:00-2:40

Personalization and Scalable Deep Learning with MXNET

Alex Smola, Machine Learning Director, Amazon
2:40-3:05

Smart Reply: Learning a Model of Conversation from Data

Anjuli Kannan, Software Engineer, Google
3:05-3:30

A Friendly Introduction To Causality

Alex Dimakis, Associate Professor, Dept. of Electrical and Computer Engineering, University of Texas at Austin
3:30-3:55

Using Bayesian Optimization to Tune Machine Learning Models

Scott Clark, CO-Founder & CEO, Sigopt
3:55-4:15

Coffee Break
4:15-4:40

Several People Are Tuning: Data and Machine Learning at Slack

Josh Wills, Head of Data Engineering, Slack
4:40-5:05

Why Machine Learning Algorithms Fall Short (And What You Can Do About It)

Jean-François Puget, Distinguished Engineer, Machine Learning and Optimization, IBM
5:05-5:25

Building a Machine Learning Platform at Quora

Nikhil Garg, Engineering Manager, Quora
5:25-5:50

Review Analysis: an Approach to Leveraging User-Generated Content in the Context of Retail

Jennifer Prendki, Principal Data Scientist, @WalmartLabs
5:50-6:00

Announcements

The following sponsors made this event possible