Future students

The Vector Institute drives excellence and leadership in Canada’s knowledge, creation and use of artificial intelligence to foster economic growth and improve the lives of Canadians. The institute is dedicated to the transformative field of artificial intelligence, excelling in machine and deep learning research.

When an election is held we often employ a peculiar kind of logic. As we mull over the candidates we may have a top choice, but if we think our preferred candidate isn’t going to win we might vote for our second choice. Or maybe we cast a ballot for our second choice because we want to make sure that a frontrunner who doesn’t represent our view loses.

We live in a world increasingly dependent on the Internet for information retrieval, social interaction and general leisure. A growing number of Internet users with cognitive or visual impairments need assistive technology to make information accessible to them, but visually complex web pages can be difficult to navigate for assistive technology.

When you look at a scenic mountain photo typically everything in the distance is in sharp focus. But this scene might be even more captivating if something striking were in the foreground, perhaps a field of wild flowers in peak bloom. The problem is if the flowers are close to the lens relative to the mountains it’s impossible for all elements in the photo to be in perfect focus — if the flowers are sharp, the distant mountains will be blurry and vice versa.

Professor Robin Cohen has received a Lifetime Achievement Award from the Canadian Artificial Intelligence Association. She is the first female recipient of the Association’s highest honour, an award that is conferred to individuals who have distinguished themselves through outstanding research excellence in artificial intelligence during the course of their academic career.

Speaker: Rejean Lau (University of Alberta)

Sentiment classification is a form of the text categorization problem where user sentiment is categorized as either positive or negative sentiment. It is generally accepted that sentiment analysis is a more challenging classification problem then topic categorization and here the bag of words approach does not perform as well. Using the IMDB sentiment dataset from Cornell University, we improve on their results by using a stacked classifier and web-mined features.