Dynamics and geometry from high dimensional dataMar 14 - 16, 2017Carnegie Mellon University |
ABSTRACTThis workshop focuses on extracting structure from high-dimensional data sets. In particular, it will address how to reliably uncover the laws that govern the dynamics being investigated and how to discover and describe the geometry present in sets of data. The workshop will bring together researchers from a variety of fields, including statistical machine learning, applied analysis, dynamical systems, probability and stochastic processes, and computational mathematics for exchange of ideas. GOALSThe aim of the workshop is to bring together researchers from a wide spectrum of disciplines studying geometry of data sets and data-driven ways to discover and the rules that govern dynamic of physical, chamical or biological processes observed. The goal is to foster exchanges between applied scientists studying the phenomena and theoretical scientists who develop models and study their properties. REGISTRATION REQUESTEDInvited participants can RSVP and provide the additional requested information about their stay, including the title and abstract of proposed talks, here. Applications for participation can be made through the Online Application. Applicants who are also interested in making a poster presentation can specify their preference to do so in the “comments section” of their application. Due to space limitations, these requests are subject to approval by the organizers. ORGANIZERS |
CONFIRMED PARTICIPANTSFUNDINGA limited amount of travel and local lodging is available for researchers in the early stages of their career who want to attend the full program, especially for graduate students and post-doctoral fellows. INFORMATION FOR PARTICIPANTSMathematical SciencesDepartment of Mathematical Sciences, Wean Hall 6113, 5000 Forbes Avenue, Carnegie Mellon University, Carnegie Mellon University Pittsburgh, PA Email: slepcev@math.cmu.edu CONFERENCE POSTERACKNOWLEDGMENTFunding provided by the NSF through the KI-net Grant. |