Seminar

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.

Philipp Kindermann, Postdoctoral Fellow
David R. Cheriton School of Computer Science

The visual complexity of a graph drawing is defined as the number of geometric objects needed to represent all its edges. In particular, one object may represent multiple edges, e.g., one needs only one line segment to draw two collinear incident edges. 

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

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. 

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.