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Privacy Adversarial Network: Representation Learning for Mobile Data Privacy
The remarkable success of machine learning has fostered a growing number...
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Better accuracy with quantified privacy: representations learned via reconstructive adversarial network
The remarkable success of machine learning, especially deep learning, ha...
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POLYPATH: Supporting Multiple Tradeoffs for Interaction Latency
Modern mobile systems use a single input-to-display path to serve all ap...
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Glider: A GPU Library Driver for Improved System Security
Legacy device drivers implement both device resource management and isol...
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Rio: A System Solution for Sharing I/O between Mobile Systems
Mobile systems are equipped with a diverse collection of I/O devices, in...
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Making I/O Virtualization Easy with Device Files
Personal computers have diverse and fast-evolving I/O devices, making th...
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Transparent Programming of Heterogeneous Smartphones for Sensing
Sensing on smartphones is known to be power-hungry. It has been shown th...
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Seamless Flow Migration on Smartphones without Network Support
This paper addresses the following question: Is it possible to migrate T...
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Sesame: Self-Constructive System Energy Modeling for Battery-Powered Mobile Systems
System energy models are important for energy optimization and managemen...
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Chameleon: A Color-Adaptive Web Browser for Mobile OLED Displays
Displays based on organic light-emitting diode (OLED) technology are app...
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