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02/26/2023
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups
Distributed (or Federated) learning enables users to train machine learn...
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06/22/2022
FLaaS: Enabling Practical Federated Learning on Mobile Environments
Federated Learning (FL) has recently emerged as a popular solution to di...
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01/29/2022
BatteryLab: A Collaborative Platform for Power Monitoring
Advances in cloud computing have simplified the way that both software d...
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10/28/2021
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
Since the inception of Recommender Systems (RS), the accuracy of the rec...
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04/29/2021
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
We propose and implement a Privacy-preserving Federated Learning (PPFL) ...
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11/18/2020
FLaaS: Federated Learning as a Service
Federated Learning (FL) is emerging as a promising technology to build m...
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04/12/2020
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments
We present DarkneTZ, a framework that uses an edge device's Trusted Exec...
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03/14/2020
Decentralized Policy-Based Private Analytics
We are increasingly surrounded by applications, connected devices, servi...
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10/20/2019
BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
Recent advances in cloud computing have simplified the way that both sof...
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07/13/2019
Towards Characterizing and Limiting Information Exposure in DNN Layers
Pre-trained Deep Neural Network (DNN) models are increasingly used in sm...
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08/30/2018
Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing
Remembering our day-to-day social interactions is challenging even if yo...
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07/06/2018
Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being
Not all smartphone owners use their device in the same way. In this work...
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02/09/2018
Deep Private-Feature Extraction
We present and evaluate Deep Private-Feature Extractor (DPFE), a deep mo...
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12/19/2017
Continual Prediction of Notification Attendance with Classical and Deep Network Approaches
We investigate to what extent mobile use patterns can predict -- at the ...
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10/04/2017