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REGISTRATION

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WELCOME

DEEP LEARNING THEORY & APPLICATION

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Ziming Zhang

Ziming Zhang - Research Scientist - Mitsubishi Electric Research Laboratories

BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning

DEEP LEARNING MODELS & FRAMEWORKS

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Nikhil Thorat

Nikhil Thorat - Software Engineer - Google Brain

Deeplearn.js: A Hardware Accelerated Machine Intelligence Library for the Web

Daniel Smilkov

Daniel Smilkov - Software Engineer - Google Brain

Deeplearn.js: A Hardware Accelerated Machine Intelligence Library for the Web

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William Moses

William Moses - PhD student - MIT CSAIL

Tensor Comprehensions

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Fabio Buso

Fabio Buso - Head of Engineering - Logical Clocks

Hyperscale Deep Learning for the Masses

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COFFEE

DEEP CONVOLUTIONAL NEURAL NETWORKS

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Michael Sollami

Michael Sollami - Lead Data Scientist - Salesforce

Computational Photography with Deep Learning

COMPUTER VISION

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Sergul Aydore

Sergul Aydore - ML Scientist - Amazon

Neural Networks for Forecasting Demand

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LUNCH

NATURAL LANGUAGE UNDERSTANDING

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Anoop Deoras

Anoop Deoras - Lead Researcher - Netflix

Latent Models (Shallow and Deep) for Recommender Systems

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Bjarke Felbo

Bjarke Felbo - Research Assistant - MIT

Transferring Knowledge From Emojis

SPEECH RECOGNITION

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David Harwath

David Harwath - Research Scientist - MIT CSAIL

Jointly Learning to Hear and See

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Kelly Davis

Kelly Davis - Machine Learning Researcher - Mozilla

Deep Speech: Free(ing) Speech with Deep Learning

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COFFEE

GENERATIVE ADVERSARIAL NETWORKS

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Miriam Cha

Miriam Cha - PhD Candidate - Harvard University

Adversarial Learning for Text-to-Image Synthesis

DEEP LEARNING & ROBOTICS

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Sudeep Pillai

Sudeep Pillai - Machine Learning Research Scientist - Toyota Research Institute

Self-Supervision in Mobile Robots in the Deep Learning Era

DEEP LEARNING & SOCIETAL IMPACTS

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PANEL: Is the Biggest Challenge Facing AI an Ethical One?

Simon Mueller

Simon Mueller - Co-founder and Vice President - The Future Society

MODERATOR

Cansu Canca

Cansu Canca - Founder/Director - AI Ethics Lab

PANELLIST

Gabriele Fariello

Gabriele Fariello - Instructor in ML & AI / CIO - Harvard University / University of Rhode Island

PANELIST

Kathy Pham

Kathy Pham - Fellow - Harvard Berkman Klein Center

PANELLIST

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Conversation & Drinks

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DOORS OPEN

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WELCOME

STARTUP SESSION

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Bill Aronson

Bill Aronson - CEO - Artificial Intelligence Research Group

The Matrix – Programmable Matter

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Neil Yager

Neil Yager - Chief Scientist - Phrasee

Using Deep Learning to Generate and Assess Natural Language

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Charles Ahmadzadeh

Charles Ahmadzadeh - Co-Founder & Engineering - Bunch.ai

What Can We Learn from Slack Data about Human Collaboration Using NLP and Research in Psychology?

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Yibiao Zhao

Yibiao Zhao - Co-Founder and CEO - iSee

Engineering Common Sense

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COFFEE

APPLICATIONS OF DEEP LEARNING IN INDUSTRY

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Jeshua Bratman

Jeshua Bratman - Staff Software Engineer - Twitter Cortex

Deep User-History Aggregates With Application to Twitter Timelines Ranking

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Chris Lott

Chris Lott - Senior Director of Engineering - Qualcomm Technologies

The Path to a Personalized, On-Device Virtual Assistant

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PANEL: How Can You Redefine Your Industry With the Application of Deep Learning?

Aditya Kaul

Aditya Kaul - Research Director - Tractica

MODERATOR

Tom Wilde

Tom Wilde - CEO - indico

PANELLIST

David Nydam

David Nydam - CEO - Business Intelligence Advisors (BIA)

PANELLIST

Sumedh Mehta

Sumedh Mehta - Chief Information Officer - Putnam Investments

PANELLIST

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LUNCH

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Greg Amis

Greg Amis - Principal Software Engineer - TripAdvisor

Improving TripAdvisor Photo Selection With Deep Learning

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Miguel Campo

Miguel Campo - SVP of Data Science & Analytics - Twentieth Century Fox Film Corp

Geometric Deep Learning in Multigraphs for Movie Recommender Systems

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Nitin Sharma

Nitin Sharma - Distinguished Scientist - PayPal

Deep Learning Architectures for Large-Scale Online Payments Fraud Detection

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Narine Kokhlikyan

Narine Kokhlikyan - Machine Learning Engineer - Slice Technologies

Using Deep Learning to Detect Anomalies in Time Series Data

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END OF SUMMIT

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Day 1

Distributed Tensorflow: Scaling Model Training to Multiple GPUs - WORKSHOP

Presentation and Real-Life Use-cases

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Day 1

The ROI of Deep Learning Application - Is it Worth it? - PANEL DISCUSSION

Panel Discussion with Leading Experts & Practitioners

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Day 2

From Academia to Industry - FIRESIDE CHAT

Fireside Chat and Q&A

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Day 2

The Future of Deep Learning in the Workplace - OPEN TABLE DISCUSSION

Open Round Table Discussion with Leading Experts

*Please note the agenda is subject to change

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