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Wednesday, December 12, 2018 — 12:15 PM EST

Zeynep Korkmaz, PhD seminar
David R. Cheriton School of Computer Science

Analysis on graphs have powerful impact on solving many social and scientific problems, and applications often perform expensive traversals on large scale graphs. Caching approaches on top of persistent storage are among the classical solutions to handle high request throughput. However, graph processing applications have poor access locality, and caching algorithms do not improve disk I/O sufficiently.

Wednesday, December 12, 2018 — 1:30 PM EST

Thomas Lidbetter, Master candidate
David R. Cheriton School of Computer Science

In this talk we consider two mostly disjoint topics in formal language theory that both involve the study and use of regular languages. The first topic lies in the intersection of automata theory and additive number theory. 

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. 

Friday, December 14, 2018 — 8:30 AM EST

Dhinakaran Vinayagamurthy, PhD candidate
David R. Cheriton School of Computer Science

Friday, December 14, 2018 — 3:00 PM EST

Nabiha Asghar, PhD candidate
David R. Cheriton School of Computer Science

Monday, December 17, 2018 — 10:00 AM EST

Jade Marcoux-Ouellet, Master’s candidate
David R. Cheriton School of Computer Science

Wednesday, December 19, 2018 — 12:30 PM EST

Ali Abbassi, Master’s candidate
David R. Cheriton School of Computer Science

We present a variety of translation options for converting Alloy to SMT-LIB via Alloy’s Kodkod interface. Our translations, which are implemented in a library that we call Astra, are based on converting the set and relational operations of Alloy into their equivalent in typed first order logic (TFOL). 

Monday, January 14, 2019 — 10:30 AM EST

Verena Kantere
School of Electrical Engineering and Computer Science, University of Ottawa

Big Data analytics in science and industry are performed on a range of heterogeneous data stores, both traditional and modern, and on a diversity of query engines. Workflows are difficult to design and implement since they span a variety of systems. To reduce development time and processing costs, some automation is needed.

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