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Aug 21st 2024
News
Amii researchers investigate an AI mystery in new Nature paper: Loss of Plasticity
In a paper published in Nature, a team of Amii researchers have revealed more about a mysterious problem in machine learning — a discovery that might be a major step towards building advanced AI that can function effectively in the real world.
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Jul 20th 2021
News
The Tea Time Talks 2021: Week Three
Watch this week's videos featuring Michael Przystupa and Alex Lewandowski, as well as a panel moderated by Michael Bowling feat. Rich Sutton, Martha White, Patrick Pilarski & Rupam Mahmood!
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Jul 13th 2021
News
Amii at ICML 2021: Accepted papers & workshops
The work of Amii researchers is being featured at the 38th annual International Conference on Machine Learning (ICML), running online this year from July 18 to 24.
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Jul 7th 2021
News
The Tea Time Talks 2021: Week Two
Watch this week's videos featuring Michael Bowling, Patrick Pilarski and Rupam Mahmood! The Tea Time Talks are 20-minute talks on early-stage ideas, prospective research and technical topics.
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Jun 23rd 2021
News
The Tea Time Talks 2021: Week One
Watch this week's videos featuring Richard Sutton, Rupam Mahmood and an RLAI panel! The Tea Time Talks are 20-minute talks on early-stage ideas, prospective research and technical topics.
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Nov 30th 2020
News
Amii accepted papers, workshops & tutorials at NeurIPS 2020
Amii is proud to share the efforts and achievements of our researchers at the 34th Conference on Neural Information Processing Systems (NeurIPS), running online this year Dec 6 - 12.
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Aug 6th 2020
News
Canada’s national AI institutes come together for 16th annual CIFAR DLRL Summer School
DLRL brings together graduate students, post-docs and professionals to learn about deep learning and reinforcement learning. Learn about Amii's involvement at this year’s event.
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Dec 9th 2019
News
Five more Canada CIFAR Chairs in AI appointed
Amii and UAlberta are pleased to welcome five new Canada CIFAR Chairs in AI to our family: Rupam Mahmood, Lili Mou, Nathan Sturtevant, Csaba Szepesvári and Adam White.
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Oct 29th 2018
Research Post
Benchmarking Reinforcement Learning Algorithms on Real-World Robots
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Feb 9th 2017
Research Post
Multi-step Off-policy Learning Without Importance Sampling Ratios
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May 1st 2016
Research Post
An emphatic approach to the problem of off-policy temporal-difference learning
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Jul 6th 2015
Research Post
Emphatic Temporal-Difference Learning
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Dec 8th 2014
Research Post
Weighted importance sampling for off-policy learning with linear function approximation
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