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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Atlanta, GA | Posted: November 30, 2018
Summary Sentence:
Active Hypothesis Testing for Information Acquisition and Active Learning
Full Summary:
Active Hypothesis Testing for Information Acquisition and Active Learning
Tara JavidiTitle:
Active Hypothesis Testing for Information Acquisition and Active Learning
Abstract:
In the first part of the talk, I will discuss an overview of my research on information acquisition and active learning in the context of the mission of our newly formed UCSD Center for Machine-Integrated Computing and Security (MICS). I will report of ongoing research on characterizing rate-reliability trade-off in active hypothesis testing, and hence bringing action into information theory and Machine Learning. In the second part of the talk, I will delve deeper into the problems of information acquisition, controlled sensing, and active learning and show our solutions to significantly reduce the cost of data collection and/or data labeling while ensuring reliability and fidelity during the training or run-time. In particular, we illustrate our findings and algorithms in the context of DetecDrone: an ML-enabled drone intelligence platform developed in my lab to provide search, mapping, and monitoring on off-the-shelf low cost drones.
Bio: Tara Javidi received his BS in Electrical Engineering from Sharif University of Technology in 1996. She received her MS degrees in electrical engineering and computer science (systems) and in applied mathematics (stochastic analysis) and her Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor. She is currently a professor of electrical and computer engineering at the University of California, San Diego, where she is a founding co-director of the Center for Machine-aware Computing and Security (MICS). She is also a member of Board of Governors of the IEEE Information Theory Society (2017/18/19).
Tara Javidi’s research interests are in theory of active learning, information theory with feedback, stochastic control theory, and stochastic resource allocation in wireless communications and communication networks. Tara Javidi was a recipient of a 2018 Qualcomm Faculty Award, National Science Foundation early career award (CAREER) in 2004, Barbour Graduate Scholarship, University of Michigan, in 1999, and the Presidential and Ministerial Recognitions for Excellence in the National Entrance Exam, Iran, in 1992. Tara Javidi is a Distinguished Lecturer of the IEEE Information Theory Society (2017/18).
