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Series: Research Horizons Seminar

Many
data sets in image analysis and signal processing are in a
high-dimensional space
but exhibit a low-dimensional structure. We are interested in building
efficient representations of these data for the purpose of compression
and inference. In the setting where a data set in $R^D$ consists of
samples from a probability measure concentrated
on or near an unknown $d$-dimensional manifold with
$d$ much smaller than $D$, we consider
two sets of problems: low-dimensional geometric approximations to the
manifold and regression of a function on the manifold. In the first
case, we construct multiscale low-dimensional empirical approximations
to the manifold and give finite-sample performance
guarantees. In the second case, we exploit these empirical geometric
approximations of the manifold and construct multiscale approximations
to the function. We prove finite-sample guarantees showing that we
attain the same learning rates as if the function
was defined on a Euclidean domain of dimension $d$. In both cases our
approximations can adapt to the regularity of the manifold or the
function even when this varies at different scales or locations.

Series: Dissertation Defense

The first part, consists on a result in the area of commutators. The classic result by Coifman, Rochber and Weiss, stablishes a relation between a BMO function, and the commutator of such a function with the Hilbert transform. The result obtained for this thesis, is in the two parameters setting (with obvious generalizations to more than two parameters) in the case where the BMO function is matrix valued. The second part of the thesis corresponds to domination of operators by using a special class called sparse operators. These operators are positive and highly localized, and therefore, allows for a very efficient way of proving weighted and unweighted estimates. Three main results in this area will be presented: The first one, is a sparse version of the celebrated $T1$ theorem of David and Journé: under some conditions on the action of a Calderón-Zygmund operator $T$ over the indicator function of a cube, we have sparse control.. The second result, is an application of the sparse techniques to dominate a discrete oscillatory version of the Hilbert transform with a quadratic phase, for which the notion of sparse operator has to be extended to functions on the integers. The last resuilt, proves that the Bochner-Riesz multipliers satisfy a range of sparse bounds, we work with the ’single scale’ version of the Bochner-Riesz Conjecture directly, and use the ‘optimal’ unweighted estimates to derive the sparse bounds.

Series: Geometry Topology Seminar

For oriented manifolds of dimension at least 4 that are simply connected at infinity, it is known that end summing (the noncompact analogue of boundary summing) is a uniquely defined operation. Calcut and Haggerty showed that more complicated fundamental group behavior at infinity can lead to nonuniqueness. We will examine how and when uniqueness fails. There are examples in various categories (homotopy, TOP, PL and DIFF) of nonuniqueness that cannot be detected in a weaker category. In contrast, we will present a group-theoretic condition that guarantees uniqueness. As an application, the monoid of smooth manifolds homeomorphic to R^4 acts on the set of smoothings of any noncompact 4-manifold. (This work is joint with Jack Calcut.)

Monday, March 26, 2018 - 13:55 ,
Location: Skiles 005 ,
Mark Iwen ,
Michigan State University ,
iwenmark@msu.edu ,
Organizer: Wenjing Liao

We propose a general phase retrieval approach that uses correlation-based measurements with compactly supported measurement masks. The algorithm admits deterministic measurement constructions together with a robust, fast recovery algorithm that consists of solving a system of linear equations in a lifted space, followed by finding an eigenvector (e.g., via an inverse
power iteration). Theoretical reconstruction error guarantees are presented. Numerical experiments demonstrate robustness and computational efficiency that outperforms competing approaches on large
problems. Finally, we show that this approach also trivially extends to phase retrieval problems based on windowed Fourier measurements.

Series: Geometry Topology Seminar

Friday, March 16, 2018 - 15:05 ,
Location: Skiles 271 ,
Longmei Shu ,
GT Math ,
Organizer: Jiaqi Yang

Isospectral reductions decrease the dimension of the adjacency matrix
while keeping all the eigenvalues. This is achieved by using rational
functions in the entries of the reduced matrix. I will show how it's
done through an example. I will also discuss about the eigenvectors and
generalized eigenvectors before and after reductions.

Series: Math Physics Seminar

Consider a relativistic electron interacting with a nucleus of nuclear charge Z and coupled to its self-generated electromagnetic field. The resulting system of equations describing the time evolution of this electron and its corresponding vector potential are known as the Maxwell-Dirac-Coulomb (MDC) equations. We study the time local well-posedness of the MDC equations, and, under reasonable restrictions on the nuclear charge Z, we prove the existence of a unique local in time solution to these equations.

Series: Combinatorics Seminar

The (type A) Hecke algebra H_n(q) is an n!-dimensional q-analog of the symmetric group. A related trace space of certain functions on H_n(q) has dimension equal to the number of integer partitions of n. If we could evaluate all functions belonging to some basis of the trace space on all elements of some basis of H_n(q), then by linearity we could evaluate em all traces on all elements of H_n(q). Unfortunately there is no simple published formula which accomplishes this. We will consider a basis of H_n(q) which is related to structures called wiring diagrams, and a combinatorial rule for evaluating one trace basis on all elements of this wiring diagram basis. This result, the first of its kind, is joint work with Justin Lambright and Ryan Kaliszewski.

Friday, March 16, 2018 - 14:00 ,
Location: Skiles 006 ,
Jen Hom ,
Georgia Tech ,
Organizer: Jennifer Hom

In this series of talks, we will study the relationship between the Alexander module and the bordered Floer homology of the Seifert surface complement. In particular, we will show that bordered Floer categorifies Donaldson's TQFT description of the Alexander module.

Series: ACO Student Seminar

A low-diameter decomposition (LDD) of an undirected graph G is a partitioning of G into components of bounded diameter, such that only a small fraction of original edges are between the components. This decomposition has played instrumental role
in the design of low-stretch spanning tree, spanners, distributed algorithms etc.
A natural question is whether such a decomposition can be efficiently maintained/updated as G undergoes insertions/deletions of edges. We make the first step towards answering this question by designing a fully-dynamic graph algorithm that maintains an
LDD in sub-linear update time.
It is known that any undirected graph G admits a spanning tree T with nearly logarithmic average stretch, which can be computed in nearly linear-time. This tree decomposition underlies many recent progress in static algorithms for combinatorial and scientific
flows. Using our dynamic LDD algorithm, we present the first non-trivial algorithm that dynamically maintains a low-stretch spanning tree in \tilde{O}(t^2) amortized update time, while achieving (t + \sqrt{n^{1+o(1)}/t}) stretch, for every 1 \leq t \leq n.
Joint work with Sebastian Krinninger.