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Wednesday, August 1, 2018 1:30 pm - 1:30 pm EDT (GMT -04:00)

Master’s Thesis Presentation / Seminar • Algorithms and Complexity — Minimum Shared-Power Edge Cut

Kshitij Jain, Master’s candidate
David R. Cheriton School of Computer Science

We introduce a problem called the Minimum Shared-Power Edge Cut (MSPEC). The input to the problem is an undirected edge-weighted graph with distinguished vertices s and t, and the goal is to find an s-t cut by assigning "powers'' at the vertices and removing an edge if the sum of the powers at its endpoints is at least its weight. The objective is to minimize the sum of the assigned powers.

Wednesday, August 1, 2018 2:00 pm - 2:00 pm EDT (GMT -04:00)

Seminar • Networks and Distributed Systems — Cache Modeling and Optimization using Miniature Simulations

Irfan Ahmad, Founder and CEO
CachePhysics

​Caches in modern distributed and storage systems must be manually tuned and sized in response to changing application’s workload. A balance must be achieved between cost, performance and revenue loss from cache sizing mis-matches. However, caches are inherently nonlinear systems making this exercise equivalent to solving a maze in the dark.

Friday, August 3, 2018 11:00 am - 11:00 am EDT (GMT -04:00)

Master’s Thesis Presentation • Data Systems — Refresh Strategies for Continuous Active Learning

Nimesh Ghelani, Master’s candidate
David R. Cheriton School of Computer Science

High recall information retrieval is crucial to tasks such as electronic discovery and systematic review. Continuous Active Learning (CAL) is a technique where a human assessor works in loop with a machine learning model; the model presents a set of documents likely to be relevant and the assessor provides relevance feedback. 

Tuesday, August 7, 2018 10:30 am - 10:30 am EDT (GMT -04:00)

Seminar • Software Engineering — A rerun of "The Prehistory and History of RE (+SE) as Seen by Me"

Daniel M. Berry
David R. Cheriton School of Computer Science

Dan Berry weaves the twin peaks of (1) his life in computing, programming, programming languages, software engineering, electronic publishing, and requirements engineering with (2) the almost concurrent development of programming languages, software engineering, and requirements engineering.

Thursday, August 9, 2018 10:00 am - 10:00 am EDT (GMT -04:00)

Master’s Thesis Presentation • Artificial Intelligence — Disentangled Representation Learning for Stylistic Variation in Neural Language Models

Vineet John, Master’s candidate
David R. Cheriton School of Computer Science

This thesis tackles the problem of disentangling the latent style and content variables in a language modelling context. This involves splitting the latent representations of documents by learning which features of a document are discriminative of its style and content, and encoding these features separately using neural network models.