[Links of the Day] 06/06/2017 : Secure Machine Learning, Quantum secured blockchain and Survey of Machine Learning in Hardware

• DeepSecure : a framework that enables scalable execution of the state-of-the-art Deep Learning models in a privacy-preserving setting. The authors propose a system that enables data owner and model owner to maintain segregation of information while allowing them to work together without data leak between the two parties. 
• Quantum-secured blockchain : The authors propose in this paper a quantum blockchain architecture specifically designed to solve the post-quantum computer cryptographic weakness of currently used crypto algorithms in Bitcoin and other blockchain frameworks. However, it seems that they conveniently ignore newer cryptographic solutions that are "quantum resistant".
• Survey of Neuromorphic Computing and Neural Networks in Hardware : heterogeneous hardware solutions are becoming the norm as classic CPU are not able to handle the bandwidth and processing power. Seriously, how a Intel or AMD CPU can process 1 Tb/S of bandwidth ... Anyway, as machine learning is reaching peak hype, the hardware that comes to accelerate it is getting more mainstream and diverse. This paper provides a good overview of the various technic and hardware used in the field. Moreover, it references an exhaustive collection of papers of the field.