Thursday, December 13, 2018

Thursday, December 13, 2018 — 9:00 AM EST

Haotian Zhang, PhD candidate
David R. Cheriton School of Computer Science

Thursday, December 13, 2018 — 10:00 AM EST

Murray Dunne, Master’s candidate
David R. Cheriton School of Computer Science

Distributed, life-critical systems that bridge the gap between software and hardware are becoming an integral part of our everyday lives. From autonomous cars to smart electrical grids, such cyber-physical systems will soon be omnipresent. With this comes a corresponding increase in our vulnerability to cyber-attacks. Monitoring such systems to detect malicious actions is of critical importance. 

Thursday, December 13, 2018 — 4:00 PM EST

Andreas Stöckel, PhD candidate
David R. Cheriton School of Computer Science

The artificial neurons typically employed in machine learning and computational neuroscience bear little resemblance to biological neurons. They are often derived from the “leaky integrate and fire” (LIF) model, neglect spatial extent, and assume a linear combination of input variables. It is well known that these simplifications have a profound impact on the family of functions that can be computed in a single-layer neural network. 

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