From pondabarnes at tti-c.org Mon Jun 18 10:25:37 2007 From: pondabarnes at tti-c.org (Ponda Barnes) Date: Mon Jun 18 10:58:59 2007 Subject: [TTIC Colloquium] Guest Speaker Announcement Message-ID: <002a01c7b1bc$eccc2bc0$e8bf8780@TTIC47> Guest Speaker Presented by: Toyota Technological Institute at Chicago Speaker: K.P. Unnikrishnan Speaker's home address: https://www.egr.msu.edu/ece/Content_Management/read.php?filename=seminar0929 05.pdf Date: Tuesday, June 19, 2007 Time: 10:00 am Location: TTI-C Conference room Title: Can Data Mining help Discover the `Neural Code'? Abstract: Data Mining involves "blind" discovery of patterns in data. We describe methods to discover patterns in sequential data and demonstrate their use to analyze multi-neuronal spike trains. Discovering the structure in these spike trains can help discover the functional connectivity in the dynamical system that produced it. I conclude the talk with a discussion of the question posed in the title Bio: Dr. K.P. Unnikrishnan received the PhD degree in Physics (biophysics) from Syracuse. University, Syracuse, New York, in 1987. He is currently a staff research scientist at the General Motors R&D Center, Warren, Michigan. Before joining GM, he was a postdoctoral member of the technical staff at AT&T Bell Laboratories, Murray Hill, New Jersey. He has also been an adjunct assistant professor at the University of Michigan, Ann Arbor, a visiting associate at the California Institute of Technology (Caltech), Pasadena, and a visiting scientist at the Indian Institute of Science, Bangalore. His research interests concern neural computation in sensory systems, correlation-based algorithms for learning and adaptation, dynamical neural networks, and temporal data mining and most recently, discovering the neural code. If you have any questions or would like to meet the speaker, please contact Ponda Barnes at pondabarnes@tti-c.org. For future TTI-C talks and events, please visit http://ttic.uchicago.edu/cal/month.php -------------- next part -------------- An HTML attachment was scrubbed... URL: http://ttic.uchicago.edu/pipermail/colloquium/attachments/20070618/d9fb3bfa/attachment-0001.htm From pondabarnes at tti-c.org Mon Jun 18 10:50:46 2007 From: pondabarnes at tti-c.org (Ponda Barnes) Date: Mon Jun 18 11:24:09 2007 Subject: [TTIC Colloquium] FW: Guest Speaker Announcement Message-ID: <004201c7b1c0$7012b5a0$e8bf8780@TTIC47> DATE CORRECTION!! Guest Speaker Presented by: Toyota Technological Institute at Chicago Speaker: K.P. Unnikrishnan Speaker's home address: https://www.egr.msu.edu/ece/Content_Management/read.php?filename=seminar0929 05.pdf Date: Wednesday, June 20, 2007 Time: 10:00 am Location: TTI-C Conference room Title: Can Data Mining help Discover the `Neural Code'? Abstract: Data Mining involves "blind" discovery of patterns in data. We describe methods to discover patterns in sequential data and demonstrate their use to analyze multi-neuronal spike trains. Discovering the structure in these spike trains can help discover the functional connectivity in the dynamical system that produced it. I conclude the talk with a discussion of the question posed in the title Bio: Dr. K.P. Unnikrishnan received the PhD degree in Physics (biophysics) from Syracuse. University, Syracuse, New York, in 1987. He is currently a staff research scientist at the General Motors R&D Center, Warren, Michigan. Before joining GM, he was a postdoctoral member of the technical staff at AT&T Bell Laboratories, Murray Hill, New Jersey. He has also been an adjunct assistant professor at the University of Michigan, Ann Arbor, a visiting associate at the California Institute of Technology (Caltech), Pasadena, and a visiting scientist at the Indian Institute of Science, Bangalore. His research interests concern neural computation in sensory systems, correlation-based algorithms for learning and adaptation, dynamical neural networks, and temporal data mining and most recently, discovering the neural code. If you have any questions or would like to meet the speaker, please contact Ponda Barnes at pondabarnes@tti-c.org. For future TTI-C talks and events, please visit http://ttic.uchicago.edu/cal/month.php -------------- next part -------------- An HTML attachment was scrubbed... URL: http://ttic.uchicago.edu/pipermail/colloquium/attachments/20070618/fa7da663/attachment.htm From pondabarnes at tti-c.org Tue Jun 19 11:40:51 2007 From: pondabarnes at tti-c.org (Ponda Barnes) Date: Tue Jun 19 12:14:54 2007 Subject: [TTIC Colloquium] Guest Speaker Announcement Message-ID: <002701c7b290$9980fa70$e8bf8780@TTIC47> Guest Speaker Presented by: Toyota Technological Institute at Chicago Speaker: Alexander Morgan Speaker's home page: http://www.udri.udayton.edu/NR/exeres/14F9E30B-FF91-48A2-AB4E-C668831ADD7D.h tm Date: Wednesday, June 20, 2007 Time: 11:00 am Location: TTI-C 1427 E. 60th Street, 2nd Floor Title: Information Extraction for Ungrammatical Text: Using a Part-Category Ontology to Index Repair Technicians' Notes Abstract: It is useful to be able to index repair notes by symptom, because a number of decision-support systems rely on accurate symptom information. Early warning systems look for unusual symptoms or symptoms that occur with unusual frequency. Textual case-based reasoning systems depend on smart-search on symptoms, made much more effective with pre-computed indices. Pareto reports on most-frequent symptoms are useful for understanding problem areas. The most common sort of symptom simply indicates that a part is not functioning properly. Other symptoms involve smells, noises, handling problems, and a few other categories. The part-related symptoms are the most difficult to categorize, because there are so many types of parts. The other symptoms can be handled by a few special-purpose ontologies. This project focuses on identifying which types of parts are mentioned in a block of free text in a repair technician's note. Part mentions need to be identified in the text. Because the text is "ungrammatical," one cannot always rely on technology such as noun-phrase extractors for this. The part mentions must be matched with known categories of parts and then disambiguated. "Gas" does not always mean gasoline. It might mean the gas used in air conditioning. This talk will describe the information extraction process in general, and then on the ways that ontologies can be used. Bio: Dr. Alexander Morgan has been a research scientist at General Motors for more than 25 years. His main areas of research include the numerical solution of systems of polynomial equations and the development of practical knowledge systems. Most recently, he has been involved in projects involving data mining, text analysis, and information extraction for health care, quality, and warranty databases. He has a Ph D. in mathematics from Yale University If you have any questions or would like to meet the speaker, please contact Ponda Barnes at pondabarnes@tti-c.org For future TTI-C talks and events, please visit http://ttic.uchicago.edu/cal/month.php -------------- next part -------------- An HTML attachment was scrubbed... URL: http://ttic.uchicago.edu/pipermail/colloquium/attachments/20070619/d604a54d/attachment-0001.htm From pondabarnes at tti-c.org Wed Jun 20 08:54:59 2007 From: pondabarnes at tti-c.org (Ponda Barnes) Date: Wed Jun 20 09:29:39 2007 Subject: [TTIC Colloquium] FW: Guest Speaker Announcement Message-ID: <001601c7b342$97cd3510$e8bf8780@TTIC47> Reminder!! Guest Speaker Presented by: Toyota Technological Institute at Chicago Speaker: K.P. Unnikrishnan Speaker's home address: https://www.egr.msu.edu/ece/Content_Management/read.php?filename=seminar0929 05.pdf Date: Wednesday, June 20, 2007 Time: 10:00 am Location: TTI-C Conference room Title: Can Data Mining help Discover the `Neural Code'? Abstract: Data Mining involves "blind" discovery of patterns in data. We describe methods to discover patterns in sequential data and demonstrate their use to analyze multi-neuronal spike trains. Discovering the structure in these spike trains can help discover the functional connectivity in the dynamical system that produced it. I conclude the talk with a discussion of the question posed in the title Bio: Dr. K.P. Unnikrishnan received the PhD degree in Physics (biophysics) from Syracuse. University, Syracuse, New York, in 1987. He is currently a staff research scientist at the General Motors R&D Center, Warren, Michigan. Before joining GM, he was a postdoctoral member of the technical staff at AT&T Bell Laboratories, Murray Hill, New Jersey. He has also been an adjunct assistant professor at the University of Michigan, Ann Arbor, a visiting associate at the California Institute of Technology (Caltech), Pasadena, and a visiting scientist at the Indian Institute of Science, Bangalore. His research interests concern neural computation in sensory systems, correlation-based algorithms for learning and adaptation, dynamical neural networks, and temporal data mining and most recently, discovering the neural code. If you have any questions or would like to meet the speaker, please contact Ponda Barnes at pondabarnes@tti-c.org. For future TTI-C talks and events, please visit http://ttic.uchicago.edu/cal/month.php -------------- next part -------------- An HTML attachment was scrubbed... URL: http://ttic.uchicago.edu/pipermail/colloquium/attachments/20070620/ad6a0661/attachment.htm From pondabarnes at tti-c.org Wed Jun 20 08:55:39 2007 From: pondabarnes at tti-c.org (Ponda Barnes) Date: Wed Jun 20 09:30:12 2007 Subject: [TTIC Colloquium] FW: Guest Speaker Announcement Message-ID: <001b01c7b342$afba3ce0$e8bf8780@TTIC47> REMINDER!! Guest Speaker Presented by: Toyota Technological Institute at Chicago Speaker: Alexander Morgan Speaker's home page: http://www.udri.udayton.edu/NR/exeres/14F9E30B-FF91-48A2-AB4E-C668831ADD7D.h tm Date: Wednesday, June 20, 2007 Time: 11:00 am Location: TTI-C 1427 E. 60th Street, 2nd Floor Title: Information Extraction for Ungrammatical Text: Using a Part-Category Ontology to Index Repair Technicians' Notes Abstract: It is useful to be able to index repair notes by symptom, because a number of decision-support systems rely on accurate symptom information. Early warning systems look for unusual symptoms or symptoms that occur with unusual frequency. Textual case-based reasoning systems depend on smart-search on symptoms, made much more effective with pre-computed indices. Pareto reports on most-frequent symptoms are useful for understanding problem areas. The most common sort of symptom simply indicates that a part is not functioning properly. Other symptoms involve smells, noises, handling problems, and a few other categories. The part-related symptoms are the most difficult to categorize, because there are so many types of parts. The other symptoms can be handled by a few special-purpose ontologies. This project focuses on identifying which types of parts are mentioned in a block of free text in a repair technician's note. Part mentions need to be identified in the text. Because the text is "ungrammatical," one cannot always rely on technology such as noun-phrase extractors for this. The part mentions must be matched with known categories of parts and then disambiguated. "Gas" does not always mean gasoline. It might mean the gas used in air conditioning. This talk will describe the information extraction process in general, and then on the ways that ontologies can be used. Bio: Dr. Alexander Morgan has been a research scientist at General Motors for more than 25 years. His main areas of research include the numerical solution of systems of polynomial equations and the development of practical knowledge systems. Most recently, he has been involved in projects involving data mining, text analysis, and information extraction for health care, quality, and warranty databases. He has a Ph D. in mathematics from Yale University If you have any questions or would like to meet the speaker, please contact Ponda Barnes at pondabarnes@tti-c.org For future TTI-C talks and events, please visit http://ttic.uchicago.edu/cal/month.php -------------- next part -------------- An HTML attachment was scrubbed... URL: http://ttic.uchicago.edu/pipermail/colloquium/attachments/20070620/bc5bab76/attachment-0001.htm