Seminar

Hamed Haddadi, Senior Lecturer and Deputy Director of Research
Dyson School of Design Engineering
Academic Fellow, Data Science Institute, Imperial College London

Finn Lidbetter, Master’s candidate
David R. Cheriton School of Computer Science

The fundamental problem of additive number theory is to determine whether there exists an integer m such that every nonnegative integer (resp., every sufficiently large nonnegative integer) is the sum of at most m elements of S. If so, we call S an additive basis of order m (resp., an asymptotic additive basis of order m). If such an m exists, we also want to find the smallest such m.

Vern Paxson
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
Chief Scientist, Corelight, Inc.
Lead, Networking and Security Group, International Computer Science Institute

Pavel Valov, PhD candidate
David R. Cheriton School of Computer Science

Pavel Valov, PhD candidate
David R. Cheriton School of Computer Science

Daniel Recoskie, PhD candidate
David R. Cheriton School of Computer Science

The wavelet transform has seen success when incorporated into neural network architectures, such as in wavelet scattering networks. More recently, it has been shown that the dual-tree complex wavelet transform can provide better representations than the standard transform. 

Anil Pacaci, PhD candidate
David R. Cheriton School of Computer Science

Torben Bach Pedersen, Professor of Computer Science
Aalborg University

Data collected from new sources such as sensors and smart devices is large, fast, and often complex. There is a universal wish to perform multidimensional OLAP-style analytics on such data, i.e., to turn it into “Big Multidimensional Data.” Supporting this is a multi-stage journey, requiring new tools and systems, and forming a new, extended data cycle with models as a key concept. We will look at three specifics steps in this data cycle.

Carolyn Lamb, PhD candidate
David R. Cheriton School of Computer Science

We describe three versions of TwitSong, a system that generates poetry based on the news. TwitSong is designed to make aesthetic decisions about potential lines of poetry and, in the third version, to edit its own work. We describe how the system was developed, how it performs in user studies, and why this type of computer-generated poetry still has a long way to go.

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.