Videos

Name: Alberta Machine Intelligence Institute (Amii)
Address: 2nd Floor, 10065 Jasper Ave, Edmonton, Alberta, T5J 3B1, Canada

Oct 27, 2020
Tea Time Talks: Juan Fernando Hernandez Garcia, The Cascade-Correlation Learning Architecture: The Forgotten Network
Oct 27, 2020
Tea Time Talks: Robin Chauhan, TalkRL and other Projects
Oct 27, 2020
Tea Time Talks: Manan Tomar, Multi-step Greedy Reinforcement Learning Algorithms
Oct 27, 2020
Tea Time Talks: Kirby Banman, Regression nonstationarities as dynamical systems
Oct 15, 2020
AI Meetup: How AI Agents Perceive and Represent Time & Opioid Risk Prediction
Oct 12, 2020
Tea Time Talks: Banafsheh Rafiee, Classical Conditioning Testbeds for State Construction
Oct 12, 2020
Tea Time Talks: Qingfeng Lan, Predictive Representation Learning for Language Modeling
Oct 5, 2020
Tea Time Talks: Alan Chan on Problems with Fair ML
Oct 5, 2020
Tea Time Talks: Khurram Javed on Learning Causal Models Online
Sep 30, 2020
Tea Time Talks: Raksha Kumaraswamy on Stochastic Optimism & Exploration
Sep 24, 2020
Tea Time Talks 2020: Dhawal Gupta, Optimizations for TD
Sep 24, 2020
"Tea Time Talks 2020: Matthew Schlegel, A first look at hierarchical predictive coding "
Sep 22, 2020
AI Seminar: Cynthia Rudin on Simpler Models and How to Find Them
Sep 22, 2020
AI Seminar: Craig Sherstan on Representation and General Value Functions
Sep 17, 2020
AI Meetup: Explainable AI & Reinforcement Learning
Sep 17, 2020
"Tea Time Talks 2020: Martha Steenstrup, Control of Communications Networks - Tryin' to Make it RL Compared to What? "
Sep 17, 2020
Tea Time Talks 2020: Han Wang, Emergent Representations in Reinforcement Learning and their Properties
Sep 17, 2020
Tea Time Talks 2020: Yufeng Yuan, Multimodal Observation Space for Robot Learning
Sep 17, 2020
Tea Time Talks 2020: Parash Rahman, Stochastic Gradient Descent in a Changing World
Sep 8, 2020
AI Seminar: Emilie Kaufmann on Learning Good Policies with and Without Rewards
Sep 4, 2020
Tea Time Talks 2020: Shibhansh Dohare, The Interplay of Search and Gradient Descent in Semi-stationary Learning Problems
Aug 17, 2020
Tea Time Talks: Connor Stephens, How to Sample When No One’s Watching – Open Problems in Bandit Exploration
Aug 17, 2020
Tea Time Talks: Rory Dawson, Adaptive Switching for Improved Control of Robotic Prosthesis
Jul 31, 2020
AI Seminar: Yixing Luan on Translations for Word Sense Disambiguation

Videos

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Video

Tea Time Talks: Juan Fernando Hernandez Garcia, The Cascade-Correlation Learning Architecture: The Forgotten Network

Tea Time Talks: Robin Chauhan, TalkRL and other Projects

Tea Time Talks: Manan Tomar, Multi-step Greedy Reinforcement Learning Algorithms

Tea Time Talks: Kirby Banman, Regression nonstationarities as dynamical systems

AI Meetup: How AI Agents Perceive and Represent Time & Opioid Risk Prediction

Tea Time Talks: Banafsheh Rafiee, Classical Conditioning Testbeds for State Construction

Tea Time Talks: Qingfeng Lan, Predictive Representation Learning for Language Modeling

Tea Time Talks: Alan Chan on Problems with Fair ML

Tea Time Talks: Khurram Javed on Learning Causal Models Online

Tea Time Talks: Raksha Kumaraswamy on Stochastic Optimism & Exploration

Tea Time Talks 2020: Dhawal Gupta, Optimizations for TD

"Tea Time Talks 2020: Matthew Schlegel, A first look at hierarchical predictive coding "

AI Seminar: Cynthia Rudin on Simpler Models and How to Find Them

AI Seminar: Craig Sherstan on Representation and General Value Functions

AI Meetup: Explainable AI & Reinforcement Learning

"Tea Time Talks 2020: Martha Steenstrup, Control of Communications Networks - Tryin' to Make it RL Compared to What? "

Tea Time Talks 2020: Han Wang, Emergent Representations in Reinforcement Learning and their Properties

Tea Time Talks 2020: Yufeng Yuan, Multimodal Observation Space for Robot Learning

Tea Time Talks 2020: Parash Rahman, Stochastic Gradient Descent in a Changing World

AI Seminar: Emilie Kaufmann on Learning Good Policies with and Without Rewards

Tea Time Talks 2020: Shibhansh Dohare, The Interplay of Search and Gradient Descent in Semi-stationary Learning Problems

Tea Time Talks: Connor Stephens, How to Sample When No One’s Watching – Open Problems in Bandit Exploration

Tea Time Talks: Rory Dawson, Adaptive Switching for Improved Control of Robotic Prosthesis

AI Seminar: Yixing Luan on Translations for Word Sense Disambiguation

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Tea Time Talks: Juan Fernando Hernandez Garcia, The Cascade-Correlation Learning Architecture: The Forgotten Network

Tea Time Talks: Robin Chauhan, TalkRL and other Projects

Tea Time Talks: Manan Tomar, Multi-step Greedy Reinforcement Learning Algorithms

Tea Time Talks: Kirby Banman, Regression nonstationarities as dynamical systems

AI Meetup: How AI Agents Perceive and Represent Time & Opioid Risk Prediction

Tea Time Talks: Banafsheh Rafiee, Classical Conditioning Testbeds for State Construction

Tea Time Talks: Qingfeng Lan, Predictive Representation Learning for Language Modeling

Tea Time Talks: Alan Chan on Problems with Fair ML

Tea Time Talks: Khurram Javed on Learning Causal Models Online

Tea Time Talks: Raksha Kumaraswamy on Stochastic Optimism & Exploration

Tea Time Talks 2020: Dhawal Gupta, Optimizations for TD

"Tea Time Talks 2020: Matthew Schlegel, A first look at hierarchical predictive coding "

AI Seminar: Cynthia Rudin on Simpler Models and How to Find Them

AI Seminar: Craig Sherstan on Representation and General Value Functions

AI Meetup: Explainable AI & Reinforcement Learning

"Tea Time Talks 2020: Martha Steenstrup, Control of Communications Networks - Tryin' to Make it RL Compared to What? "

Tea Time Talks 2020: Han Wang, Emergent Representations in Reinforcement Learning and their Properties

Tea Time Talks 2020: Yufeng Yuan, Multimodal Observation Space for Robot Learning

Tea Time Talks 2020: Parash Rahman, Stochastic Gradient Descent in a Changing World

AI Seminar: Emilie Kaufmann on Learning Good Policies with and Without Rewards

Tea Time Talks 2020: Shibhansh Dohare, The Interplay of Search and Gradient Descent in Semi-stationary Learning Problems

Tea Time Talks: Connor Stephens, How to Sample When No One’s Watching – Open Problems in Bandit Exploration

Tea Time Talks: Rory Dawson, Adaptive Switching for Improved Control of Robotic Prosthesis

AI Seminar: Yixing Luan on Translations for Word Sense Disambiguation

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