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Events for February 28, 2018

  • CS Colloquium: Yinzhi Cao (Lehigh University) – Testing and Repairing Machine Learning Systems in Adversarial Environment

    Wed, Feb 28, 2018 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Yinzhi Cao, Lehigh University

    Talk Title: Testing and Repairing Machine Learning Systems in Adversarial Environment

    Series: Computer Science Colloquium

    Abstract: Machine learning (ML) systems are increasingly deployed in safety- and security-critical domains such as self-driving cars and malware detection, where the system correctness for corner case inputs are crucial. Existing testing of ML system correctness depends heavily on manually labeled data and therefore often fails to expose erroneous behaviors for rare inputs.

    In this talk, I will present the first framework to test and repair ML systems, especially in an adversarial environment. In the first part, I will introduce DeepXplore, a whitebox testing framework of real-world deep learning (DL) systems. Our evaluation shows that DeepXplore can successfully find thousands of erroneous corner case behaviors, e.g., self-driving cars crashing into guard rails and malware masquerading as benign software. In the second part, I will introduce machine unlearning, a general, efficient approach to repair an ML system exhibiting erroneous behaviors. Our evaluation, on four diverse learning systems and real-world workloads, shows that machine unlearning is general, effective, fast, and easy to use.

    This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in RTH 115, seats will be first come first serve.

    Biography: Yinzhi Cao is an assistant professor at Lehigh University. He earned his Ph.D. in Computer Science at Northwestern University and worked at Columbia University as a postdoc. Before that, he obtained his B.E. degree in Electronics Engineering at Tsinghua University in China. His research mainly focuses on the security and privacy of the Web, smartphones, and machine learning. He has published many papers at various security and system conferences, such as IEEE S&P (Oakland), NDSS, CCS, and SOSP. His JShield system has been adopted by Huawei, the world's largest telecommunication company. His past work was widely featured by over 30 media outlets, such as NSF Science Now (Episode 38), CCTV News, IEEE Spectrum, Yahoo! News and ScienceDaily. He received two best paper awards at SOSP'17 and IEEE CNS'15 respectively.

    Host: Muhammad Naveed

    Location: Ronald Tutor Hall of Engineering (RTH) - 115

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

  • Computer Science General Faculty Meeting

    Wed, Feb 28, 2018 @ 12:00 PM - 02:00 PM

    Thomas Lord Department of Computer Science

    Receptions & Special Events

    Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.

    Location: Ronald Tutor Hall of Engineering (RTH) - 526

    Audiences: Invited Faculty Only

    Contact: Assistant to CS chair

  • Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering

    Wed, Feb 28, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars

    Speaker: Magnus Egerstedt, Georgia Institute of Technology

    Talk Title: Long-range autonomy and constraint-based coordination of multi-robot systems

    Abstract: By now, we have a fairly good understanding of how to design coordinated control strategies for making teams of mobile robots achieve geometric objectives in a distributed manner, such as assembling shapes or covering areas. But, the mapping from high-level tasks to geometric objectives is not particularly well understood. In this talk, we investigate this topic in the context of long-range autonomy, i.e., we consider teams of robots, deployed in an environment over a sustained period of time, that can be recruited to perform a number of different tasks in a distributed, safe, and provably correct manner. This development will involve the composition of multiple barrier certificates for encoding the tasks and safety constraints, as well as a detour into ecology as a way of understanding how persistent environmental monitoring, as a special instantiation of the long-range autonomy concept, can be achieved by studying animals with low-energy life-styles, such as the three-toed sloth.

    Biography: Magnus Egerstedt is the Executive Director for the Institute for Robotics and Intelligent Machines at the Georgia Institute of Technology and a Professor and the Julian T. Hightower Chair in Systems and Controls in the School of Electrical and Computer Engineering. He received the M.S. degree in Engineering Physics and the Ph.D. degree in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden, the B.A. degree in Philosophy from Stockholm University, and was a Postdoctoral Scholar at Harvard University. Dr. Egerstedt is a Fellow of the IEEE and a recipient of a number of research and teaching awards, including the Ragazzini Award from the American Automatic Control Council.

    Host: Mihailo Jovanovic, mihailo@usc.edu

    More Information: egerstedt.jpg (JPEG Image, 623 × 779 pixels).pdf

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Gerrielyn Ramos

  • CAIS Seminar: Dr. Henry Kautz (University of Rochester) – Mining Social Media to Improve Public Health

    Wed, Feb 28, 2018 @ 04:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Dr. Henry Kautz, University of Rochester

    Talk Title: Mining Social Media to Improve Public Health

    Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series

    Abstract: People posting to social media on smartphones can be viewed as an organic sensor network for public health data, picking up information about the spread of disease, lifestyle factors that influence health, and pinpointing sources of disease. We show how a faint but actionable signal can be detected in vast amounts of social media data using statistical natural language and social network models. We present case studies of predicting influenza transmission and per-city rates, discovering patterns of alcohol consumption in different neighborhoods, and tracking down the sources of foodborne illness.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Dr. Henry Kautz is the Robin & Tim Wentworth Director of the Goergen Institute for Data Science and Professor in the Department of Computer Science at the University of Rochester. He has served as department head at AT&T Bell Labs in Murray Hill, NJ, and as a full professor at the University of Washington, Seattle. In 2010 he was elected President of the Association for Advancement of Artificial Intelligence, and in 2016 was elected Chair of the AAAS Section on Information, Computing, and Communication. His research in artificial intelligence, pervasive computing, and healthcare applications has led him to be honored as a Fellow of the American Association for the Advancement of Science, Fellow of the Association for Computing Machinery, and Fellow of the AAAI.

    Host: Milind Tambe

    Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101

    Audiences: Everyone Is Invited

    Contact: Computer Science Department