Current undergraduate students

Speaker: Daniel Saunders (Queens University)

There has been much debate about the nature of the processes involved in biological motion perception. In contrast to previous views, Jastorff et al. (2007) provided evidence that biological motion is understood via a mechanism that is specialized, but also relatively plastic, alterable over the course of hours rather than years.

Speaker: Omar Zia Khan

There has been little work in explaining recommendations generated by Markov Decision Processes (MDPs). We analyze the difficulty of explaining policies computed automatically and identify a set of templates that can be used to generate explanations automatically at run-time.

Speaker: Babak Alipanahi

There has been much recent attention to the problem of learning an appropriate distance metric, using class labels or other side information. Some proposed algorithms are iterative and computationally expensive.

Speaker: Sandip Sen, University of Tulsa

We believe that intelligent information agents will represent their users interest in electronic marketplaces and other forums to trade, exchange, share, identify, and locate goods and services.

Speaker: Enrico Gerding, University of Southampton

Scoring rules are originally used to reward probabilistic estimates such as weather forecasts, where the score or utility that an agent receives depends on the materialized outcome of the prediction. Strictly proper scoring rule are a class of scoring rule which are designed such that they incentivize utility-maximizing agents to reveal the entire probability distribution truthfully.

Speaker: Pascal Poupart, Allan Caine, Farheen Omar and Adam Hartfield

Walkers are becoming an increasingly popular mobility aid among older adults. While they are designed to improve balance, the fact that many walkers have wheels, it is not clear whether stability is enhanced or jeopardized.

Speaker: Kevin Regan, University of Toronto

Traditional methods for finding optimal policies in stochastic, multi-step decision environments require a precise model of both the environment dynamics and the rewards associated with taking actions and the effects of those actions.

Speaker: Kate Larson

Since its introduction in the mid-nineties, Dung's theory of abstract argumentation has been influential in AI as it serves as a convenient model for reasoning about general characteristics of argument.

Speaker: Reid Kerr

Traders in electronic marketplaces may behave dishonestly, cheating other agents. A multitude of trust and reputation systems have been proposed to try to cope with the problem of cheating.

Speaker: Igor Kiselev

Classical dynamic approaches to online learning and optimization address the issue of statistical fluctuations of the incoming data by means of continual retraining their models, which is computationally intractable for real-world problems of practical interest and is inappropriate in time-critical scenarios.