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| Supporting Scalable Online Statistical Processing |
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Google Tech Talks
April, 28 2008
ABSTRACT
Christopher Jermaine - RESEARCH SCIENTIST
Query processing for analytic, statistical,
and exploratory database queries has been an
active area of database research and
development for nearly two decades. Many
experts now consider this problem to be
"solved", especially with regard to
performance. However, an argument can be made
that users and databases have simply reached
an uneasy truce with regard to analytic
processing. If users avoid ad-hoc,
exploratory queries that might take days to
execute, then of course the database performs
just fine.
In this talk, I will describe query
processing in a database system called DBO
that is designed from the ground up to
support interactive analytic processing. DBO
can run database queries from start to finish
and produce exact answers in a scalable
fashion. However, unlike any existing
research or production system, DBO is able to
produce statistically meaningful approximate
answers at all times throughout query
execution. These answers are continuously
updated from start to finish, even for "huge"
queries requiring arbitrary quantities of
temporary secondary storage. Thus, a user can
stop execution whenever satisfied with the
query accuracy, which may translate to
dramatic time savings during exploratory
processing.
Speaker: Christopher M. Jermaine - Research
Scientist
Chris Jermaine is an assistant professor in
the CISE Department at the University of
Florida, where he studies databases and data
management. He is the recipient of a 2008
Alfred P. Sloan Foundation Research
Fellowship, a National Science Foundation
CAREER award, and a 2007 ACM SIGMOD Best
Paper Award. He received a BA from the
Mathematics Department at UCSD, and a PhD
from the College of Computing at Georgia
Tech.
Tags : google techtalks techtalk engedu talk talks googletechtalks education |
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Affichage : 4081
Durée : 3563 s |
| Modeling Human Sentence Processing |
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Google Tech Talks
April, 17 2008
ABSTRACT
Modeling human sentence-processing can help
us both better understand how the brain
processes language, and also help improve
user interfaces. For example, our systems
could compare different (computer-generated)
sentences and produce ones that are easiest
to understand.
I will talk about my work on evaluating
theories about syntactic processing
difficulty on a large eye-tracking corpus,
and present a model of sentence processing
which uses an incremental, fully connected
parsing strategy.
Speaker: Vera Demberg
Vera Demberg is a Ph.D. student in
Computational Linguistics from the University
of Edinburgh, Scotland. Her research focus is
on building computational models of human
sentence processing.
Vera obtained a Diplom (MSc) in Computational
Linguistics from Stuttgart University, and a
MSc in Artificial Intelligence from the
University of Edinburgh. She has published
papers in a number of top venues for language
processing and psycholinguistic research,
including ACL, EACL, CogSci and Cognition.
For her PhD research, she's been awarded the
AMLaP Young Scientist Award for best platform
presentation by a junior scientist. She was a
finalist for the Google Europe Anita Borg
Memorial Scholarship in 2007.
Tags : google techtalks techtalk engedu talk talks googletechtalks education |
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Affichage : 8285
Durée : 2975 s |
| PhotoTechEDU Day 6: Digital Camera Image Processing... |
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Google Tech Talks
February 28, 2007
ABSTRACT
Photographic Technology EDU Day 6: In this
session we examine the steps that a digital
camera goes through to take raw data from an
image sensor and make a photograph out of it.
There are more steps than you might imagine,
arranged in what is usually termed a
pipeline, and is sometimes implemented on
pipelined hardware, to get to a pleasing
photographic rendering of the scene.
Credits: Speaker:Richard Lyon
Tags : google howto phototechedu day digital camera |
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Affichage : 3087
Durée : 3476 s |
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