The Montreal AI Symposium aims at gathering experts and professionals interested in fundamental advances and applications of artificial intelligence, with an emphasis on machine learning, deep learning and related approaches.
The Symposium welcomes both academic and industrial participants; it seeks to build strong connections between researchers within the Greater Montreal area.
We will feature a day-long event, filled with keynote addresses, contributed talks and posters, and time for networking and socializing. Information about the last year event can be found here.
The Symposium date and location will be announced shortly.
Daycare will be offered for free during the symposium. However, registration will be mandatory.
Code of conduct
This symposium aims at facilitating discussions and the exchange of ideas. We ask all participants to be respectful of others and to be aware of their own behaviour. Registration for the symposium will require signing the code of conduct available here.
Call for Contributions
We invite you to submit a contribution to the third Montreal AI symposium. We encourage submission of abstracts from both academic and industrial researchers, which can describe a technical or practical contribution, an open problem, an application or a position statement. Previously published material is acceptable. Do not include any confidential material.
Topics of interest include but are not limited to:
- Fundamental research in deep learning, reinforcement learning, kernel machines, Bayesian modelling, ensemble methods, optimization for machine learning;
- Implementation issues, parallelization, software platforms, hardware;
- Applications, including vision, audio, speech, natural language processing, robotics, healthcare, bioinformatics.
Senior Program Chair:
- Negar Rostamzadeh, Element AI
- Laurent Charlin, MILA, Université de Montréal/ HEC
- Adriana Romero, Facebook AI Research/ McGill
- Fernando Diaz, Microsoft Research
- Émélie Brunet, MILA, Université de Montréal
Diversity and Inclusion Chairs:
- Laurent Dinh, Google Brain
- Hana Nagel, Element AI