10th Conference on Bayesian Nonparametrics
Abstract
Statement of Work: Bayesian nonparametric methods of statistics have recently flourished and found applications in various fields. The 10th Conference on Bayesian Nonparametrics, to be held in Raleigh, June 22--26, 2015, will bring researchers together to exchange ideas on theory, methodology and applications of Bayesian nonparametrics. Objective: This proposal seeks funding to pay registration fee and provide accommodation for some invited speakers many of whom are young researchers. It is customary in Bayesian nonparametrics meeting to provide such hospitality to invited speakers. Organizing this conference is key to maintaining the current leadership of American institutions in this field. The conference will also provide American researchers opportunity to exchange ideas with leading researchers from elsewhere in the world such as Europe, Asia and Latin America. In addition, the conference will provide opportunities for young researchers to disseminate widely the results of their work, not only through contributed talks and posters, but also by facilitating the publication of peer-reviewed papers and a proposed special issue of a leading statistics journal. The extensive poster session and some slots for contributed talks are especially reserved for young researchers. Approach: The conference will host 3 plenary lectures, 28 invited talks, 54 contributed talks and two large poster sessions where about 100 people can present their work. The main purpose of the conference is to increase interactions between various researchers working on Bayesian nonparametric methods in different parts of the world. Ample recess time and social events will allow such interaction to flourish. The scientific committee has carefully drafted a strong program covering ever aspects of Bayesian nonparametrics and selecting speakers to address diversity. The local organizers will provide the state-of-the-art facilities during the conference and offer local and travel support to some invited speakers and young researchers. Overall Merit and ONR Mission/Relevance: Defense applications often deal with complex data sets in various forms such as images, texts, video streams, trees, records and so on. Discovering hidden patterns and relationships from large, complex, and noisy datasets in various applications such as threat identification, anomalies detection, document classification, network discovery, satellite imaging, risk assessment and building highly interpretable and accurate prediction models are challenging problems directly relevant in applications in defense. In three dimensional object detection, the goal is to detect objects such as cars, buildings, and human faces from background noise. The main challenge is large data variation in visual appearance, caused by object sizes and shapes, object position and orientation, image background and surrounding nvironments. So it is crucial to identify important features and enhance true signals. Another example is the identification of important risk factors for a certain disease such as the recent Ebola outbreak and protect troops the population they are protecting from getting exposed to these deadly diseases. Bayesian nonparametric methods and related machine learning techniques provide important directions towards these goals. Recent advances on computing and innovative algorithms such as integrated nested Laplace approximation, expectation propagation, variational methods and Markov chain and sequential Monte Carlo methods have made it possible to address the most complex problems through Bayesian nonparametric techniques. The issue has become particularly important in the age of the internet, social network and mobile computing. Bayesian nonparametric methods are well-suited for automated analyses of streaming data because they have the flexibility to adapt to complex data and do not require extensive tuning and model checking.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2016
- Source ID
- N000141512427
Entities
People
- Subhashis Ghosal
Organizations
- North Carolina State University
- Office of Naval Research
- United States Navy