Past Seminars- Colloquium

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  • Xiaodong He
    Thu May 25, 2017
    4:00 pm
    Deep learning, which exploits multiple levels of data representations that give rise to hierarchies of concept abstraction, has been the driving force in the recent resurgence of Artifi cial Intelligence (AI). In this talk, I will summarize rapid advances in cognitive AI, particularly including comprehension, reasoning, and generation across...
  • S. Mayboroda
    Thu Apr 13, 2017
    4:00 pm
        Over the past century an effort to understand dimension and structure of the harmonic measure spanned many spectacular developments in Analysis and in Geometric Measure Theory. Uniform rectifiability emerged as a natural geometric condition, necessary and sufficient for classical estimates in harmonic analysis, boundedness of the...
  • Ramin Takloo-Bighash
    Thu Mar 16, 2017
    4:00 pm
    The talk will start with some remarks on the role that zeta functions and Tuberian theorems have played in number theory in the last 180 years starting essentially with Dirichlet's proof of his Arithmetic Progression Theorem. The remainder of the talk will be devoted to giving a survey of recent applications of Tauberian theorems to counting...
  • Jonathan Weitsman
    Thu Mar 2, 2017
    4:00 pm
    Geometric Quantization is a program of assigning to classical mechanical systems (symplectic manifolds and the associated Poisson algebras of C-infinity functions) their quantizations --- algebras of operators on Hilbert spaces.  Geometric Quantization has had many applications in Mathematics and Physics.   Nevertheless the main...
  • Greg Lawler
    Thu Feb 23, 2017
    4:00 pm
    The self-avoiding walk (SAW) is a model for polymers that assigns equal probability to all paths that do not return to places they have already been. The lattice version of this problem, while elementary to define, has proved to be notoriously difficult and is still open. It is initially more challenging to construct a...
  • Andrew Stuart
    Thu Feb 9, 2017
    4:00 pm
    A central research challenge for the mathematical sciences in the $21^{st}$ century is the development of principled methodologies for the seamless integration of (often vast) data sets with (often sophisticated) mathematical models. Such data sets are becoming routinely available in almost all areas of engineering, science and technology, whilst...
  • Bin Yu
    Fri Feb 3, 2017
    2:00 pm
    In this talk, I'd like to discuss the intertwining importance and connections of three principles of data science in the title in data-driven decisions. The ultimate importance of prediction lies in the fact that future holds the unique and possibly the only purpose of all human activities, in business, education, research, and government...