Events

Speaker: Delbert Dueck

While many clustering methods assume clusters are described by parameters or points in a vector space, an alternative approach is to identify a set of training cases as 'exemplars' and then assign every other training case to an exemplar.

Speaker: Wei Li

The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work demonstrates that the well-known Davis-Putnam procedure combined with a dynamic decomposition and caching technique is an effective method for exact inference in Bayesian networks with high density and width.

Speaker: David Poole (University of British Columbia)

This tutorial gives an overview of rich representations for probabilistic reasoning. The first third of the tutorial gives the basics of logic, knowledge representation and probability.

Speaker: Mattt Enns

For my Masters thesis I researched the effects of word sense disambiguation on lexical chains. A lexical chain is a sequence of words in a document that are semantically related (i.e., related in meaning).

Speaker: David Tausky

In this talk, I will describe our prototype pen-based system for entering and manipulating mathematical expressions, currently called MathBrush.

Speaker: Shaheen Fatima

Sequential and simultaneous auctions are two important mechanisms for buying and selling multiple objects. These two mechanisms yield different outcomes (i.e., different surpluses, different revenues, and also different profits to the winning bidders). Given this, we compare the outcomes for the sequential and simultaneous mechanisms for the following scenario.

Speaker: Fei Song (University of Guelph)

Text categorization is the process of assigning predefined categories to textual documents. As the exponential growth of web pages and online documents continues, there is an increasing need for systems that automatically classify text into proper categories.

Speaker: David Hirtle

One explanation as to why the Semantic Web has not quite caught on yet is that the barrier to entry is too high. This talk describes TRANSLATOR, a free tool available as a Java Web Start application designed to allow anyone, even non-experts, to write facts and rules in formal representation for use on the Semantic Web.

Speaker: Feng Jiao

We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data.

Speaker: Jiye Li

Clickstream data collected across multiple websites (user-centric data) captures users' browsing behaviors, interests and preferences more than clickstream data collected from individual websites (site-centric data). For example, we would expect that we could better model and predict the intentions of users who we know not only searched on google but also visited certain shopping websites, than if we know only one of these pieces of information. Current research on clickstream data analysis is mostly centered around site-centric data.