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September 24, 2018

Impact of Social Learning on Privacy-Preserving Data Collection

The explosive growth in data collection is accelerating the use of machine learning in many IoT applications and shaping our networked life. In particular, personal data is often collected based on “informed consent," where users decide whether to report data or not based upon who is collecting the data. We developed a Bayesian game theoretic framework to study the impact of social learning on users’ data reporting strategies and devise the payment mechanism for the data collector. Our findings reveal that both the data collector and the users benefit from social learning under some mild conditions.

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October 10, 2018

Notre Dame Radio Society Meeting

Join us for the Notre Dame Radio Society meeting on Wednesday, November 10, from 5:30 - 6:30 pm, in 258 Fitzpatrick Hall. Membership in the Notre Dame Radio Society is open to all Notre Dame Students, Faculty, Staff, and Alumni. Please email ND1U@nd.edu for more information.

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October 24, 2018

Context-Based Wireless Link Prediction for Drone Communications

Drone communications inherently carries a challenge of needing to communicate in three dimensions at any point in time. Fortunately, UAVs have a number of sensors such as Inertial Measurement Units (IMUs), 4K cameras, and Light Detection and Ranging (LiDAR) that could potential infer environmental context to improve drone-to-drone and drone-to-ground wireless links. In this talk, we leverage cellular crowdsourcing, sensed geographical features, and environmental contexts to enable robust wireless links for efficient coordination among drone swarms.

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