Schedule 2021

You must register to attend using Eventbrite. Welcoming coffee and poster session/social will happen on gather.town. You will receive the Zoom and gather.town links at the email that you used to register on Eventbrite – check your email!

TimeTitleSpeakerPlatform
08:30-09:00Welcome social eventOrganizersgather.town
09:00Opening remarksCourtney PaquetteIn-person/Zoom
09:00-10:00Keynote talk 1: Vision and Language: Progress and Challenges
Aishwarya Agrawal

Assistant Professor in the Department of Computer Science and Operations Research at University of Montreal. 		In-person/Zoom
10:00-10:45Poster spotlights:
1) Aggregating From Multiple Target-Shifted Sources (Changjian Shui)
2) Deep Reinforcement Learning at the Edge of the Statistical Precipice (Rishabh Agarwal)
3) Typing assumptions improve identification in causal discovery (Philippe Brouillard)
4) On the Limits of Algorithmic Counting and Out-of-Distribution Generalization (Martin Weiss)		In-person/Zoom
10:45-11:00Break
11:00-11:45Keynote talk 2: Practical Directions for Responsible AI Development

Tegan Maharaj

Assistant Professor in the Faculty of Information at the University of Toronto.		In-person/Zoom
11:45-12:30Poster spotlights:
1) Improving Fairness in Heterogeneous Federated Learning (Shaoxiang Qin)
2) Mixture-based Feature Space Learning for Few-shot Image Classification (Arman Afrasiyabi)
3) Sequential Pipeline Optimization: Bandits-driven Exploration using a Collaborative Filtering Representation (Maxime Heuillet)
4) Task-Assisted GAN for resolution enhancement, quality improvement and modality translation in fluorescence microscopy (Catherine Bouchard)		In-person/Zoom
12:30-14:00Lunch break
14:00-14:45Keynote talk 3: Deep Reinforcement Learning – Challenges and Opportunities

Pablo Samuel Castro

Staff research Software Developer in Google Research (Brain team) in Montreal		In-person/Zoom
14:45-15:30Poster spotlights:
1) Q-Layer: Latent Space Constraints for Robust Convolutional Neural Network (Sirui Song)
2) CARL: Conditional value-at-risk Adversarial Reinforcement Learning (Mathieu Godbout)
3) Parallel Gaussian Process-Based Bayesian Optimization for Multiple Cortical Array Neuroprosthetic Control (Julien Rimok)
4) SESNO: Sample Efficient Social Navigation from Observation (Bobak H Baghi)		In-person/Zoom
15:30-15:45Break
15:45-16:45Poster session (see list of accepted submissions here)gather.town
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