Upcoming Colloquia Events

Designing Matching Algorithms and Collaborative Project Experiences in Computer Science

Duke Computer Science Colloquium
Speaker Name
Brandon Fain
Location
LSRC D106
Date and Time
-
In the first part of the talk, we will consider the design of two-sided matching algorithms for problems like residency matching and school choice. In the second half of the talk, we will step back and consider how the approach of the first half reflects a larger goal of engaging students in the process of becoming computer scientists through active and collaborative learning.

Foundations of Intelligent Systems with (Deep) Function Approximators

Duke Computer Science Colloquium
Speaker Name
Simon Du
Location
LSRC D106
Date and Time
-
In this talk, I will discuss my work on understanding, designing, and applying function approximators. First, I will focus on understanding deep neural networks. In the second part of the talk, I will focus on applying function approximators to decision-making, aka reinforcement learning, problems.

Where Natural Language Processing Meets Societal Needs

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Kathleen McKeown
Location
LSRC D106
Date and Time
-

The large amount of language available online today makes it possible to think about how to learn from this language to help address needs faced by society. In this talk, I will describe research in our group on summarization and social media analysis that addresses several different challenges. We have developed approaches that can be used to help people live and work in today’s global world, approaches to help determine where problems lie following a disaster, and approaches to identify when the social media posts of gang-involved youth in Chicago express either aggression or loss.

Digital Forensics: From Photoshop to Deep Fakes

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Hany Farid
Location
LSRC D106
Date and Time
-

The past few years have seen a startling and troubling rise in the fake-news phenomena in which everyone from individuals to state-sponsored entities can produce and distribute mis-information. The implications of fake news range from a mis-informed public to an existential threat to democracy, and horrific violence. At the same time, recent and rapid advances in machine learning are making it easier than ever to create sophisticated and compelling fake images and videos, making the fake-news phenomena even more powerful and dangerous.

Putting Ethical AI to the Vote

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Ariel Procaccia
Location
LSRC D106
Date and Time
-

I will present the 'virtual democracy' framework for the design of ethical AI. In a nutshell, the framework consists of three steps: first, collect preferences from voters on example dilemmas; second, learn models of their preferences, which generalize to any (previously unseen) dilemma; and third, at runtime, predict the voters' preferences on the current dilemma, and aggregate these virtual 'votes' using a voting rule to reach a decision.