Biblio
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2017. Control with minimal cost-per-symbol encoding and quasi-optimality of event-based encoders. IEEE Trans. on Automat. Contr.. 62:2286–2301.
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2017. A Simplex Architecture for Hybrid Systems using Barrier Certificates. International Conference on Computer Safety, Reliability and Security (SAFECOMP 2017). :117–131.
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2017. Modeling Genetic Circuit Behavior in Transiently Transfected Mammalian Cells. Gordon Research Conference in Stochastic Physics.
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2016. Modeling Genetic Circuit Behavior in Transiently Transfected Mammalian Cells. Q-Bio Summer Conference.
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2018. Probabilistic Model Checking of Partially Controlled Multi-agent Systems. Under review by AAAI 2018.
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2017. Convoy: Physical Context Verification for Vehicle Platoon Admission. 18th International Workshop on Mobile Computing Systems and Applications (HotMobile).
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2017. PitchIn: Eavesdropping via Intelligible Speech Reconstruction using Non-Acoustic Sensor Fusion. 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).
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2017. SenseTribute: Smart Home Occupant Identification via Fusion Across On-Object Sensing Devices. 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys).
to appear
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2017. Trust but Verify: Auditing Secure Internet of Things Devices. {Proceedings of the The 15th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2017)}.
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2016. Deploying Fourier coefficients to unravel soybean canopy diversity. Frontiers in plant science. 7
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2011. Structural similarity and distance in learning. 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Allerton Park {&} Retreat Center, Monticello, IL, USA, 28-30 September, 2011. :744–751.
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2012. Local Supervised Learning through Space Partitioning. Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States.. :91–99.
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2013. Online local linear classification. 5th {IEEE} International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, {CAMSAP} 2013, St. Martin, France, December 15-18, 2013. :173–176.
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2013. Locally-Linear Learning Machines (L3M). Asian Conference on Machine Learning, {ACML} 2013, Canberra, ACT, Australia, November 13-15, 2013. 29:451–466.
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2014. Model Selection by Linear Programming. Computer Vision - {ECCV} 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part {II}. 8690:647–662.
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2014. An LP for Sequential Learning Under Budgets. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, {AISTATS} 2014, Reykjavik, Iceland, April 22-25, 2014. 33:987–995.
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2015. Sensor Selection by Linear Programming. CoRR. abs/1509.02954
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2015. Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction. Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada. :2152–2160.
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Submitted. An LP for Sequential Learning Under Budgets. {AISTATS}. 33:987–995.
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2016. Modeling Concurrency and Reconfiguration in Vehicular Systems: A $π$-calculus Approach. IEEE International Conference on Automation Science and Engineering.
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2016. Toward Modeling Concurrency and Reconfiguration in Vehicular Systems. 9th Interaction and Concurrency Experience.
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2017. Compiling CPS Model Repositories through Student Competitions. 2nd Workshop on Monitoring and Testing of Cyber-Physical Systems.
This talk describes how the Cyber-Physical Systems Virtual Organization (CPS-VO) is hosting competitions for the purpose of improving CPS verication tools. We describe the 2016 Challenge, which focused on quadrotor control and codesign of payload, and the 2017 Challenge which focuses on populating a ground vehicle simulator with realistic obstacles. In addition, the interfaces by which participants compete are described, in order to articulate the means by which models can be decoupled from the system for the purposes of evaluation by external tools.
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2016. Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs. CoRR. abs/1601.06105
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2015. Learning Efficient Anomaly Detectors from K-NN Graphs. Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, {AISTATS} 2015, San Diego, California, USA, May 9-12, 2015. 38