Events

Filters
Export this event to calendar
iCal
RSS
RSS
Close X

Filter by:

Limit to events where the first date of the event:
Date range
Limit to events where the first date of the event:
Limit to events where the title matches:
Limit to events where the type is one or more of:
Limit to events tagged with one or more of:
Limit to events where the audience is one or more of:
Thursday, March 11, 2021 9:30 am - 9:30 am EST (GMT -05:00)

PhD Seminar • Natural Language Processing — UmlsBERT: Clinical Domain Knowledge Augmentation of Contextual Embeddings Using the Unified Medical Language System Metathesaurus

Please note: This PhD seminar will be given online.

Georgios Michalopoulos, PhD candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Ian McKillop and Helen Chen

Thursday, March 11, 2021 12:00 pm - 12:00 pm EST (GMT -05:00)

Seminar • Machine Learning — Steps Towards Making Machine Learning More Natural

Please note: This seminar will be given online.

Mengye Ren, Department of Computer Science
University of Toronto

Over the past decades, we have seen machine learning making great strides in AI applications. Yet, most of its success relies on training models offline on a massive amount of data and evaluating them in a similar test environment. By contrast, humans can learn new concepts and skills with very few examples, and can easily generalize to novel tasks.

Wednesday, March 17, 2021 11:00 am - 11:00 am EDT (GMT -04:00)

PhD Seminar • Algorithms and Complexity — Geodesic Convexity in Statistics and Sample Complexity Bounds

Please note: This PhD seminar will be given online.

Akshay Ramachandran, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Lap Chi Lau

The matrix normal model, the family of Gaussian matrix-variate distributions whose covariance matrix is the Kronecker product of two lower dimensional factors, is frequently used to model matrix-variate data. The tensor normal model generalizes this family to Kronecker products of three or more factors. 

Thursday, March 18, 2021 12:00 pm - 12:00 pm EDT (GMT -04:00)

Seminar • Cryptography, Security, and Privacy (CrySP) — Measuring and Enhancing the Security of Machine Learning

Please note: This seminar will be given online.

Florian Tramèr, Computer Science Department
Stanford University

Failures of machine learning systems can threaten both the security and privacy of their users. My research studies these failures from an adversarial perspective, by building new attacks that highlight critical vulnerabilities in the machine learning pipeline, and designing new defenses that protect users against identified threats.

Monday, March 22, 2021 12:00 pm - 12:00 pm EDT (GMT -04:00)

Seminar • Machine Learning — The Surprising Power of Little Data

Please note: This seminar will be given online.

Weihao Kong, Postdoctoral researcher
Department of Computer Science, University of Washington

In this talk, I will discuss several examples of my research that reveal a surprising ability to extract accurate information from modest amounts of data.

Tuesday, March 23, 2021 9:00 am - 9:00 am EDT (GMT -04:00)

PhD Defence • Computer Graphics | Scientific Computing — Efficient Liquid Animation: New Discretizations for Spatially Adaptive Liquid Viscosity and Reduced-Model Two-Phase Bubbles and Inviscid Liquids

Please note: This PhD defence will be given online.

Ryan Goldade, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Christopher Batty