Machine learning is accelerating the translation of biological and biomedical data to advance the detection, diagnosis, treatment, and prevention of diseases. However, the unprecedented scale and complexity of large-scale biomedical data have presented critical computational bottlenecks requiring new concepts and enabling tools.
We establish first a theoretical foundation for the use of Gromov-Hausdorff (GH) distance for point set registration with homeomorphic deformation maps perturbed by Gaussian noise. We then present a probabilistic, deformable registration framework. At the core of the framework is a highly efficient iterative algorithm with guaranteed convergence to a local minimum of the GH-based objective function. The framework has two other key components – a multi-scale stochastic shape descriptor and a data compression scheme.
The second annual Triangle Machine Learning Day is hosted by SAMSI at Duke University's Penn Pavilion. This event brings together researchers and applied scientists in different areas of machine learning, including industrial applications, academic theory, and everything in between, for a day of technical talks and posters.
CS Department, please join us for this special opportunity to come together in fellowship and welcome our newest faculty, graduate students, undergraduate students, postdocs, and staff.
- Meeting: 4:30pm
- Dinner: 5:15pm - Families, please join us for dinner @ 5:15 pm.
Entertainment will be provided for children, and free parking is available at the Washington Duke Inn. Please register by September 11, 2019 and contact Pam Spencer with any questions. We hope to see you there!
InDuke TechConnect brings students and employers together for networking and education. Each year, employers connect with Engineering and Computer Science students in an open, dynamic networking environment. Students come prepared with resumes to meet industry and tech representatives to learn about employment opportunities available, the characteristics employers seek as well as a realistic and insightful view of the job market and career paths for students interested in engineering and technical careers.
As software moves off the desktop and into data centers, and cell phones use server requests as the other half of apps, the observation tools for large-scale distributed transaction systems are not keeping up with the complexity of the environment. Exploring a simpler environment can help expose some of the problems that confront today’s tool users and tool builders. There is a lot to be learned from careful observation of a program and its complete surrounding context, even one as trivial as “Hello, World!”.
Video games, Virtual Reality (VR), Augmented Reality (AR), and Smart appliances (e.g., smart TVs and drones) all all for a new way for users to interact and control them. Motivated by this observation, we have developed a series of novel motion tracking technologies using acoustic signals. A unique feature of our approach is that it can achieve mm-level tracking accuracy on smartphones without special hardware. We further develop a few interesting applications on top of our motion tracking technology such as a follow-me drone and acoustic imaging on mobile phones.
Hosted at Duke University and bringing together researchers, students and industry labs for a day of technical talks and posters in the broad areas of privacy, security, cryptography, and blockchains, the first-ever Triangle Area Privacy and Security Day (TAPS) is modeled after similar events occurring in Boston, DC and New York. The program will feature technical talks and a poster session.
The ADT 2019 conference focus is on algorithmic decision theory broadly defined, seeking to bring together researchers and practitioners coming from diverse areas of Computer Science, Economics and Operations Research in order to improve the theory and practice of modern decision support.