Schedule
24 October
25 October
24 October
REGISTRATION & LIGHT BREAKFAST
WELCOME
Towards Combining Statistical Relational Learning and Graph Neural Networks - HEC Montreal
AI Ethics: A Deflationary Yet Cautionary Tale - UNIVERSITE LAVAL
Few-Shot Learning: Thoughts On Where We Should Be Going - GOOGLE BRAIN
Social Inclusion in the AI Pipeline - POLYTECHNIQUE MONTREAL
Building Knowledge For AI Agents With Reinforcement Learning - DEEPMIND
AI for Humanity: How AI Could Benefit Us All- MILA
COFFEE
DEEP DIVE: Introduction to Deep Reinforcement Learning - MILA
DEEP DIVE: Neural Networks for Lawyers and Other Non-Technical Professionals - MIT
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks - MIT
Ethical Issues in NLP - UNIVERSITY OF TORONTO
DEEP DIVE: AI, Deep Learning, Optimization: How to Frame and Solve Real World Problems Effectively to Get the Most Business Benefits - ALPSANALYTICS.COM
Generalizing The Lottery Ticket Hypothesis Across Datasets and Optimizers and Beyond Supervised Image Classification - FACEBOOK AI RESEARCH
Finding Bias In Your Systems - SHOPIFY
Outlines, Explanation, and Deflecting Adversarial Examples - GOOGLE BRAIN
DEEP DIVE: How The Pharmaceutical Industry Is Leveraging Deep Learning - NOVARTIS
Agnostic Data Debiasing Through a Local Sanitizer Learnt from an Adversarial Network Approach - UNIVERSITE DU QUEBEC A MONTREAL
Learning to Act More Like Humans, and Learning with Less Data - POLYTECHNIQUE MONTREAL
LUNCH
DEEP DIVE: Lunch and Learn
PM Host Introduction
Productionizing Deep Learning Models - EXPEDIA
Fairwashing: The Risk of Rationalization - UNIVERSITÉ DE MONTRÉAL
DEEP DIVE: Algorithmic Profiling & Illegal Discrimination: A Cross-Industry Analysis - MONTREAL AI ETHICS INSTITUTE
AI for Self Driving - From Research to Production - UBER ATG
Learning Fair Rule Lists - UNIVERSITE DU QUEBEC A MONTREAL
New Optimization Perspectives on Generative Adversarial Networks - SAIT AI LAB
The Evolving Relationship Between Ethics and Safety in AI - FUTURE OF LIFE INSTITUTE
DEEP DIVE: Consumer Airfare Prediction and other Big Data AI Challenges at Hopper- HOPPER
PANEL: How Can We Overcome Challenges To Fully Leverage the Oportunities of GANs?- MILA, UNIVERSITY OF MASSACHUSETTS, SAIT AI LAB/UNIVERSITE DE MONTREAL, CONCORDIA UNIVERSITY
Adversarial Machine Learning: Ensuring Security of ML Models and Sensitive Data - VECTOR INSTITUTE
COFFEE
DEEP DIVE: Talent and Talk
Deep Learning and Cognition - UNIVERSITÉ DE MONTRÉAL
CONVERSATION & DRINKS
END OF SUMMIT
25 October