AI & Fundamentals
Human-Centered Artificial Intelligence: Trusted, Reliable and Safe - Ben Shneiderman, Emeritus Distinguished University Professor, University of Maryland; Founding Director of the Human-Computer Interaction Laboratory
Human-Centered Artificial Intelligence: Trusted, Reliable and Safe - Ben Shneiderman, Emeritus Distinguished University Professor, University of Maryland; Founding Director of the Human-Computer Interaction Laboratory
Abstract: Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) model clar...
AI & Ethics
CANCELLED--The End of Privacy - Michal Kosinski, Associate Professor, Stanford University
CANCELLED--The End of Privacy - Michal Kosinski, Associate Professor, Stanford University
This seminar has been CANCELLED in response to COVID-19. Abstract: A growing proportion of human activities―such as social interactions, entertainment, shopping, and gathering information―are now mediated by digital ...
General Event
EVENT POSTPONED--Emerging Technologies: BC's AI Showcase
EVENT POSTPONED--Emerging Technologies: BC's AI Showcase
NOTE: Event Postponed due to COVID-19. New date TBD. Please contact organizers for any questions or concerns. UBC's Centre for Artificial Intelligence Decision-making and Action (CAIDA) invites you to the conference "Emerging T...
AI & Fundamentals
Halting Time is Predictable for Large Models: A Universality Property and Average-case Analysis - Courtney Paquette, Research Scientist, Google Research
Halting Time is Predictable for Large Models: A Universality Property and Average-case Analysis - Courtney Paquette, Research Scientist, Google Research
Please register for this event here. Abstract: Average-case analysis computes the complexity of an algorithm averaged over all possible inputs. Compared to worst-case analysis, it is more representative of the typical behavior...
AI & Fundamentals
Rethinking the Objective for Policy Optimization in Reinforcement Learning - Martha White, Associate Professor, University of Alberta
Rethinking the Objective for Policy Optimization in Reinforcement Learning - Martha White, Associate Professor, University of Alberta
Please register for this event here Abstract: The goal in reinforcement learning is to obtain a policy that maximizes long-term reward. Policy optimization in reinforcement learning involves directly estimating a paramet...
AI & Fundamentals
Beyond Linearization in Neural Networks - Jason Lee, Assistant Professor, Princeton University
Beyond Linearization in Neural Networks - Jason Lee, Assistant Professor, Princeton University
Please register for this event here Abstract: Deep Learning has had phenomenal empirical successes in many domains including computer vision, natural language processing, and speech recognition. To consolidate and boost the em...
AI & Applications
Active learning and A-Optimal Experimental Design - Eldad Haber, Professor, UBC
Active learning and A-Optimal Experimental Design - Eldad Haber, Professor, UBC
Please register for this event here. Abstract: In this work we discuss the problem of active learning. We present an approach that is based on A-optimal experimental design of ill-posed problems and show how one can optimally ...
AI & Fundamentals
Inconsistency of a Recurrent Language Model: A Question I Forgot to Ask in 2014 - Kyunghyun Cho, Associate Professor, New York University
Inconsistency of a Recurrent Language Model: A Question I Forgot to Ask in 2014 - Kyunghyun Cho, Associate Professor, New York University
Please register for this event here Abstract: In this talk, I will go back to the basic of neural sequence modeling and ask the glaringly obvious question I forgot to ask in 2014; "is density estimation a good strategy for seq...
AI & Fundamentals
Playing with Visual AI - Helge Rhodin, Assistant Professor, UBC
Playing with Visual AI - Helge Rhodin, Assistant Professor, UBC
Please register for this event here. Abstract: I will be talking about my past and ongoing work on human and animal capture: telepresence (virtual reality), injury prevention in sports (alpine skiing and soccer), b...
AI & Fundamentals
Meta-Learning - A Roadmap for Few-Shot Transfer Learning - Hugo Larochelle, Research Scientist, Google Brain
Meta-Learning - A Roadmap for Few-Shot Transfer Learning - Hugo Larochelle, Research Scientist, Google Brain
Please register for this event here. Abstract: A lot of the recent progress on many AI tasks were enabled in part by the availability of large quantities of labeled data for deep learning. Yet, humans are able to learn ne...