Upcoming Events

Local Differential Privacy for Physical Sensor Data

Algorithms Seminar
Speaker Name
Audra McMillan
Location
North 311
Date and Time
-

Physical sensors (thermal, light, motion, etc.) are becoming ubiquitous and offer important benefits to society. However, allowing sensors into our private spaces has resulted in considerable privacy concerns. Differential privacy has been developed to help alleviate these privacy concerns. In this talk, we'll develop and define a framework for releasing physical data that preserves both utility and provides privacy. Our notion of closeness of physical data will be defined via the Earth Mover Distance and we'll discuss the implications of this choice.

From Robots to Biomolecules: Computing meets the Physical World

CS/ECE Lecture Series
Speaker Name
Lydia Kavraki
Location
D106 LSRC, Duke
Date and Time
-

Over the last decade, the development of fast and reliable motion planning algorithms has deeply influenced many domains in robotics, such as industrial automation and autonomous exploration. Motion planning has also contributed to great advances in an array of unlikely fields, including graphics animation and computational structural biology.

Learning about Agents and Mechanisms from Opaque Transactions

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Avrim Blum
Location
D106 LSRC, Duke
Date and Time
-

In this talk I will discuss the problem of trying to learn the requirements and preferences of economic agents by observing the outcomes of an allocation mechanism whose rules you also don’t initially know.   As an example, consider observing web pages where the agents are advertisers and the winners are those whose ads show up on the given page.  We know these ads are placed based on bids and other constraints given to some auction mechanism, but we do not get to see these bids and constraints.

Duke Datathon

Special Event
Location
Washington Duke Inn
Date and Time
-

Datathons are a new type of live-action competition for STEM students. They are analogous to "Hackathons" for software engineers, but instead of building apps, contestants use real-world data to develop and substantiate solutions to a socially impactful problem. If you are curious to see what a Datathon looks like, we encourage you to view this brief clip from our past Dublin Datathon!

Deep Representations, Adversarial Learning and Domain Adaptation for Some Computer Vision Problems

CS/ECE Lecture Series
Speaker Name
Rama Chellappa
Location
D106 LSRC, Duke
Date and Time
-
Recent developments in deep representation-based methods for many computer vision problems have knocked down many research themes pursued over the last four decades. In this talk, I will discuss methods based on deep representations, adversarial learning and domain adaptation for designing robust computer vision systems with applications in unconstrained face and action verification and recognition, expression recognition, subject clustering and attribute extraction.

TBD

Duke Computer Science Colloquium
Speaker Name
Aude Billard
Location
D106 LSRC, Duke
Date and Time
-

TBD

TBD

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Richard Szeliski
Location
D106 LSRC, Duke
Date and Time
-

TBD

TBD

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Polina Golland
Location
D106 LSRC, Duke
Date and Time
-

TBD

TBD

Duke Computer Science Colloquium
Speaker Name
Samir Khuller
Location
D106 LSRC, Duke
Date and Time
-

TBD

TBD

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Christopher Manning
Location
TBA, Duke (telecast from UNC)
Date and Time
-

TBD

TBD

Triangle Computer Science Distinguished Lecturer Series
Speaker Name
Jeannette Wing
Location
D106 LSRC, Duke (telecast from UNC)
Date and Time
-

TBD

TBD

Duke Computer Science Colloquium
Speaker Name
Prakash Panangaden
Location
D106 LSRC, Duke
Date and Time
-

TBD