The following is the schedule of upcoming department seminars. Seminars will be added to the schedule throughout the year. All seminars are free of charge and are open to all members, affiliates, and colleagues of the university community. Seminars are typically held on Tuesday or Thursday at 1:00 pm. If you would like additional information or if you might be interested in presenting a seminar, please contact Steph Durocher or the Department of Computer Science.
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Dr. Yang Wang
When: May 22, 2012 @ 1:00pm
Where: EITC E2-304, University of ManitobaSpeaker: Yang Wang, University of Illinois at Urbana-Champaign
Title: Discriminative Latent Variable Models for Visual Recognition
Abstract:
Discriminative latent variable models, in particular those involving structured latent variables, are emerging as a class of powerful tools for solving many computer vision problems that involve complex structures. In this talk, I will give an overview of several of our recent work in adapting these models for solving various problems in visual recognition, including part-based models for human action recognition, latent pose for still image action recognition, group activity recognition and image annotation. I will also mention applications in other areas(e.g. NLP) that can be addressed by these models. -
Dr. M. Tamer Özsu
When: May 29, 2012 @ 1:00pm
Where: EITC E2-304, University of ManitobaSpeaker: M. Tamer Özsu, University of Waterloo
Title: RDF Data Management Using Graph Algorithms
Abstract:
Resource Description Framework (RDF) has been proposed for modeling Web objects as part of developing the "semantic web". It has also gained attention as a way to accomplish web data integration. As the volume of RDF data has increased, interesting data management issues have arisen. In this talk I will discuss some of our recent work in this area, focusing on two results: answering SPARQL queries over RDF graphs, and processing aggregate SPARQL queries. The first problem focuses on evaluating SPARQL queries with wildcards over an RDF graph that sees frequent updates. We propose an approach that maps both the RDF data and the SPARQL query into graphs and converts the query evaluation problem to one of subgraph matching. In order to speed up query processing, we propose an indexing mechanism and pruning rules to reduce the search space. The second problem addresses the processing of aggregation queries over large RDF data sets. We propose a processing approach that partitions aggregate queries into smaller parts (called star queries), processes these efficiently, and joins the results of star queries to obtain more general results. We develop indexes to assist in executing star queries and to facilitate joining their results.
Bio:
M. Tamer Özsu is Professor of Computer Science at the David R. Cheriton School of Computer Science of the University of Waterloo. His research is in data management focusing on large-scale data distribution and management of non-traditional data. He is a Fellow of the Association for Computing Machinery (ACM), and of the Institute of Electrical and Electronics Engineers (IEEE), and a member of Sigma Xi.