CSCE 478/878 (Fall 2001) Oral Presentation Schedule
Note: If your oral presentation is from an on-line source (e.g. PowerPoint),
bring your presentation slides on a floppy. It
takes too much time for each group to log off and the next one to log on, so
there will be one login at the start of class, and everyone presenting that day
will simply copy their presentation on to the hard drive from the floppy.
Of course, if you are using transparencies, you have nothing to worry about.
You are expected to attend as many talks as possible, especially those during
regular class periods. This will affect the subjective portion of your grade.
You should consider your presentation's scheduled time slot final unless you
have a conflict that you absolutely cannot change. This is to prevent
constant modifications of the presentation schedule, which require alterations
to everyone else's schedules and potential problems with room and equipment
reservations.
Each talk will be 15 minutes, plus 5 minutes for
questions. I expect that it will take 5 minutes to transition from one group
to the next. Hence a total of 25 minutes is allotted per talk. However, this
is only an approximation! Don't assume that your talk will start exactly at
the time implied by the given schedule.
- Monday, December 10, 3:30-5:30pm, Ferguson 112
-
Sangsuree Vasupongayya
Ensembles of ANNs
-
Qingping Tao
Experiments with a DNF Learning Algorithm
-
Cory Lueninghoener
Parallelization of a DNF Learning Algorithm and an Ensemble Pruner
-
Cory Strope
Parallelization of an On-Line Algorithm to Learn Multiple-Instance Concepts
-
Robert Glaubius & Sarah Osentoski
Training an ANN to Recognize Visual Artistic Styles
- Wednesday, December 12, 9:00am-12:30pm, Ferguson 114
-
Jeremy Glasser & Jason Brozek
Predicting the Outcomes of Sporting Events
-
Kye Halsted
Machine Learning in a Query-by-Example Information Retrieval System
-
Brad Trenkle
Learning to Diagram English Sentences
-
Harikrishna Koppisetti
Solving the Travelling Salesman Problem using Kohonen Networks
-
Tibor Moldovan
Learning in Constraint Satisfaction Systems
-
Octav Chipara
Virtual Blue Jays Eat Virtual Moths
-
Yap, Eng-Hooi
Machine Learning Applications in Finance
- Wednesday, December 12, 3:30-5:30pm, Ferguson 112
-
Benjamin Kutsch
An Introduction to Support Vector Machines
-
Jiang Li
Remote Sensing Image Classification using Support Vector Machines
-
Olga Lamonova
Learning in Multi-Agent Systems
-
Christopher Hammack
Learning to Classify Web Pages
-
Erik Mumm
Reinforcement Learning to Control a Rapelling Robot
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Last modified 16 August 2011; please report problems to
sscott AT cse.