Events - December 2018

Friday, December 21, 2018 — 1:30 PM EST

Joseph Haraldson, PhD candidate
David R. Cheriton School of Computer Science

We consider the problem of computing the nearest matrix polynomial with a non-trivial Smith Normal Form (SNF). This is a non-convex optimization problem where we find a nearby matrix polynomial with prescribed eigenvalues and associated multiplicity structure in the invariant factors.

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, December 17, 2018 — 10:00 AM EST

Jade Marcoux-Ouellet, Master’s 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

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

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

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. 

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 — 9:00 AM EST

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

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. 

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.

Monday, December 10, 2018 — 10:21 AM EST

Panos K. Chrysanthis
Department of Computer Science, University of Pittsburgh

Wednesday, December 5, 2018 — 2:00 PM EST

Li Liu, PhD candidate
David R. Cheriton School of Computer Science

Following my previous seminar talk on embezzlement of entanglement, this talk introduces a more general version of the problem — self-embezzlement. Instead of embezzling a pair of entangled state from a catalyst, self-embezzlement aims to create two copies of the catalyst state using only local operators. 

Wednesday, December 5, 2018 — 1:30 PM EST

Di Wang, Postdoctoral fellow
Georgia Institute of Technology

Tuesday, December 4, 2018 — 10:00 AM EST

Ahmed Alquraan, Master’s candidate
David R. Cheriton School of Computer Science

We present a comprehensive study of 136 system failures attributed to network-partitioning faults from 25 widely used distributed systems. We found that the majority of the failures led to catastrophic effects, such as data loss, reappearance of deleted data, broken locks, and system crashes. 

Tuesday, December 4, 2018 — 9:30 AM EST

Jeff Avery, PhD candidate
David R. Cheriton School of Computer Science

Monday, December 3, 2018 — 11:30 AM EST

Zeming Liu, Master’s candidate
David R. Cheriton School of Computer Science

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