Conferences, Lectures, & Seminars
Events for January
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NL Seminar- Mohsen Taheriyan: "A Graph-based Approach to Learn Semantic Descriptions of Data Sources"
Fri, Jan 17, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Mohsen Taheriyan, USC/ ISI
Talk Title: "A Graph-based Approach to Learn Semantic Descriptions of Data Sources"
Series: Natural Language Seminar
Abstract: Abstract: Semantic models of data sources and services provide support to automate many tasks such as source discovery, data integration, and service composition, but writing these semantic descriptions by hand is a tedious and time-consuming task. Most of the related work focuses on automatic annotation with classes or properties of source attributes or input and output parameters. However, constructing a source model that includes the relationships between the attributes in addition to their semantic types remains a largely unsolved problem. In this talk, we present a graph-based approach to hypothesize a rich semantic description of a new target source from a set of known sources that have been modeled over the same domain ontology. We exploit the domain ontology and the known source models to build a graph that represents the space of plausible source descriptions. Then, we compute the top k candidates and suggest to the user a ranked list of the semantic models for the new source. The approach takes into account user corrections to learn more accurate semantic descriptions of future data sources. Our evaluation shows that our method produces models that are twice as accurate than the models produced using a state of the art system that does not learn from prior models.
Biography: Mohsen's webpage: http://www-scf.usc.edu/~taheriya/
Host: Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - Marina Del Rey, Conf Rm- #1135
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
AI Seminar-Chris Mattmann:
Fri, Jan 24, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Chris Mattmann, Jet Propulsion Laboratory-NASA
Talk Title: "BIG DATA! 24 hour near real time processing and computation for the JPL Airborne Snow Observatory"
Series: Artificial Intelligence Seminar
Abstract: JPL's Airborne Snow Observatory is an integrated imaging spectrometer and scanning LIDAR for measuring mountain snow albedo, snow depth/snow water equivalent, and ice height (once exposed), led by PI Dr. Tom Painter. The team recently wrapped our "Snow On" campaign where over a course of 3 months, we flew the Tuolumne River Basin, Sierra Nevada, California above the O'Shaughnessy Dam of the Hetch Hetchy reservoir; focusing initial on the Tuolumne, and then moving to weekly flights over the Uncompahgre Basin, Colorado.
To meet the needs of its customers including Water Resource managers who are keenly interested in Snow melt, the ASO team had to develop and end to end 24 hour latency capability for processing spectrometer and LIDAR data from Level 0 to Level 4 ("ish") products. Fondly referring to these processing campaigns as "rodeos" the team rapidly constructed an open source data processing system at minimal cost and risk that not only met our processing demands, but taught the entire team many lessons about remote sensing of snow and dust properties, algorithm integration, the relationship between computer scientists, and snow hydrologist; flight and engineering teams, geographers, and most importantly lessons about camaraderie that will engender highly innovative and rapid data systems development, and quality science products for years to come.
Chris Mattmann is the Compute Lead for the ASO project and he will humbly tell the story of the Compute processing capability on behalf of the larger team, highlighting contributions of its key members along the way.
Biography: http://www.amazon.com/Chris-Mattmann/e/B006V44GIG
Home Page:
http://sunset.usc.edu/~mattmann/
Host: Yolanda Gil
More Info: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=91c9c7ae70c24b789a031a66963e297c1d
Webcast: TBALocation: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
WebCast Link: TBA
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=91c9c7ae70c24b789a031a66963e297c1d
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
AI Seminar- Kiri Wagstaff: "Automated data prioritization and explanation for scientific discovery of Martian minerals, exoplanets, and more"
Fri, Jan 31, 2014 @ 11:00 AM - 12:15 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kiri Wagstaff, Jet Propulsion Laboratory-NASA
Talk Title: "Automated data prioritization and explanation for scientific discovery of Martian minerals, exoplanets, and more"
Series: Artificial Intelligence Seminar
Abstract: Inundated by terabytes of data flowing from telescopes, microscopes, DNA sequencers, etc., scientists in various disciplines have a need for automated methods for prioritizing data for review. Which observations are most interesting or unusual, and why?
I will describe DEMUD (Discovery by Eigenbasis Modeling of Uninteresting Data), which iteratively prioritizes items from large data sets to provide a diverse traversal of interesting items. By modeling what the user already knows and/or has already seen, DEMUD can focus attention on the unexpected, facilitating new discoveries. Uniquely, DEMUD also provides a domain-relevant explanation for each selected item that indicates why it stands out. DEMUD's explanations offer a first step towards automated interpretation of scientific data discoveries.
We are using DEMUD in collaboration with scientists from the Mars Science Laboratory, the Mars Reconnaissance Orbiter, the Kepler exoplanet telescope, Earth orbiters, and more. It provides scalable performance, interpretable output, and new insights into very large data sets from diverse disciplines.
This is joint work with James Bedell, Nina L. Lanza, Tom G. Dietterich, Martha S. Gilmore, and David R. Thompson.
Biography: Kiri L. Wagstaff is a senior researcher in artificial intelligence and machine learning and a tactical activity planner for the Mars rover Opportunity at the Jet Propulsion Laboratory. Her research focuses on developing new machine learning and data analysis methods, particularly those that can be used for in situ analysis onboard spacecraft such as orbiters, landers, rovers, and so on. She holds a Ph.D. in Computer Science from Cornell University and an M.S. in Geological Sciences from the University of Southern California. She received a 2008 Lew Allen Award for Excellence in Research for work on the sensitivity of machine learning methods to high-radiation space environments and a 2012 NASA Exceptional Technology Achievement award for work on transient detection methods in radio astronomy data. She is passionate about keeping machine learning relevant to real-world problems and is co-editing a special issue of the Machine Learning journal on Machine Learning for Science and Society.
http://www.wkiri.com/
Host: Yolanda Gil
More Info: http://www.wkiri.com/
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=71ff3718d56e4345b89699a0433dc6d81dLocation: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=71ff3718d56e4345b89699a0433dc6d81d
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://www.wkiri.com/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
