We have three special colloquium times this coming week.  The
information for them is copied below from
http://eecs.oregonstate.edu/graduate/colloquium/, which includes the
next few colloquiums as well.  Hope to see you there!

Monday
February 14
9:00 - 9:50 AM 
Owen 102

Heather Richter 
Ph.D. Candidate
College of Computing
Georgia Institute of Technology


Designing and Evaluating Meeting Capture and Access Services 

Many work practices consist of repeated discussions among groups of
people. For example, software developers talk to customers to generate
requirements, brainstorm and sketch design alternatives and make
decisions, and perform code walkthroughs and reviews. A large amount of
the rich, unstructured information that is generated during these
discussions often does not get recorded as formal knowledge. Yet this
information is later useful for providing additional context, details,
and decisions surrounding a project. 

In this talk, I will present several prototypes that demonstrate the
application of ubiquitous computing to automatically capture, integrate
and store multimedia records of different work discussions. We capture
knowledge acquisition sessions with Tagger, and have evaluated the use
of captured sessions in creating a requirements document. With the
TeamSpace system, we have achieved authentic, long-term use of capture
and access in general meetings. I will discuss what we have learned
about the motivations and potential benefits for using recorded meeting
information. I will also discuss the behavioral patterns we observed and
the implications for supporting users with meeting capture and access
systems.


Biography

Heather Richter is a Ph.D. candidate in the College of Computing at the
Georgia Institute of Technology. She is a member of the Ubicomp Research
Group and GVU Center, where she investigates the use of meeting capture
and access systems. Her research interests include Human-Computer
Interaction, Software Engineering, and Ubiquitous Computing. She
received her B.S. in computer science from Michigan State University in
1995.
 
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Wednesday
February 16
9:00 - 9:50 AM 
Owen 102
 
Xiaoli Fern 
Ph.D. candidate
Computer Engineering
Purdue University


Unsupervised Pattern Discovery for Scientific Applications 

Vast amounts of scientific data are collected everyday. Tools for
automatically extracting interesting patterns from the data with limited
or no human supervision are critical toward understanding and gaining
knowledge from the data. In this talk, I will present my research on two
unsupervised pattern discovery problems within the context of Earth
Science applications. 

The first problem, clustering multi-spectral land cover data, poses
fundamental challenges to existing unsupervised learning techniques due
to the high dimensionality of the data. I will present a method based on
random projection and cluster ensemble techniques to tackle the issues
caused by high dimensionality. Results on land cover data and other
benchmarks will be presented to show that this approach significantly
improves the clustering performance on high dimensional data over
existing approaches.

In the second problem, correlation pattern analysis of
vegetation-precipitation data, I will build on the classical statistical
method of Canonical Correlation Analysis (CCA) and introduce a novel
approach to learning mixtures of CCA models. This approach not only
addresses the linearity limitation of the traditional CCA method, but
also is capable of finding correlation patterns that are only locally
valid in the data. I will demonstrate the efficacy of the proposed
approach with both synthetic and real-world data.


Biography

Xiaoli Fern is a Ph.D. candidate in Computer Engineering at Purdue
University. She received her B.S. and M.S. degrees from Shanghai Jiao
Tong University in 2000 and 1997 respectively. Her primary research
interests are in machine learning and data mining. She is particularly
interested in developing practical algorithms for automatically
discovering useful patterns from scientific data.
 
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Thursday
February 17
9:00 - 9:50 AM 
Owen 102

Bruce Childers 
Assistant Professor
Computer Science
University of Pittsburgh


Continuous Compilation for Aggressive and Adaptive Code Transformation 

Over the past several decades, the compiler research community has
developed a number of sophisticated and powerful algorithms for a
variety of code improvements. Although there are still promising
directions for particular code optimizations, programming languages, and
machine architectures, research on optimizations is nearing the point of
diminishing returns and other approaches are needed to achieve further
performance improvements. Our research aims to address this challenge by
investigating and developing an innovative framework and system for
continuously and adaptively applying code improvements. Our system, the
Continuous Compiler (CoCo), determines "optimization plans" at
compile-time that describe the best way in which to apply both static
and dynamic code transformations. The plans consider program and machine
context, interaction among optimizations, and performance profit.
Through such planning, CoCo can tailor and adapt its decisions to more
synergistically apply a whole suite of code transformations. This talk
will describe the Continuous Compilation approach and present initial
results. These results include novel analytic models that can accurately
predict the performance benefit (profit) of applying an optimization
without actually doing it or running the resulting program code. Using
the analytic models, we have developed several planners that can guide a
static optimizer. Initial results are very encouraging and show that
optimizations can be effectively directed by planning. The talk will
conclude with a brief discussion of CoCo's run-time system, including
its dynamic code translator, instrumentation optimizer, and source-level
debugger for dynamically translated code.


Biography

Bruce Childers is an Assistant Professor in the Department of Computer
Science at the University of Pittsburgh. Dr. Childers received a BS
degree (Computer Science, 1991) from the College of William and Mary,
and a PhD degree (Computer Science, 2000) from the University of
Virginia. His research interests are compilers and software development
tools, computer architecture, and embedded systems. Current projects
include continuous compilation to synergistically apply both static and
dynamic code optimizations, debugging for dynamically translated code,
power-aware real-time systems, and demand-driven software testing.
 

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