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Past Events

Oct 19 2017

Growing Graceful Trees

Information
Thursday, October 19, 2017
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Edinah Gnang - Johns Hopkins University
In this talk we will describe and motivate the graceful labeling conjecture. We will discuss enumerative aspects of the conjecture and describe how it serves as a wonderful test case
Oct 18 2017

Fifty Shades of Gray Codes

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Wednesday, October 18, 2017
12:10 PM - 1:00 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Danny Scheinerman - Rutgers University
We will describe the classical Gray code and some of its nice properties. We can generalize Gray codes as walks generally through a collection of objects where each step the
Oct 18 2017

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem

Information
Wednesday, October 18, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Steven Wu - University of Pennsylvania
Bandit learning models the common setting when the decisions of an algorithm feed back into its training data, and it cannot observe counter-factuals. These settings include criminal recidivism prediction (would
Oct 16 2017

Approximate Affine Invariance and Distance to Polynomials

Information
Monday, October 16, 2017
2:00 PM - 3:00 PM
Type: Seminars | Rutgers Discrete Mathematics Seminar
Presenter(s): Swastik Kopparty - Rutgers University
Let F be a finite field, and let V be the set of functions from F to F computed by a univariate polynomial of degree at most d. It is
Oct 12 2017

Wittgenstein versus Gödel

Information
Thursday, October 12, 2017
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Art DuPre - Rutgers University

Because of a "Notorius" paragraph in Wittgenstein's 'Remarks on the Foundations of Mathematics' and the controversy it caused among mathematicians, logicians and philosophers, Hao Wang, among others, lay this controversy

Oct 11 2017

What do the largest subgraphs of K_n (or the random graph!) with a particular matching number look like?

Information
Wednesday, October 11, 2017
12:10 PM - 1:00 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Abigail Raz - Rutgers University
There are many statements across math of the form "a structure with property X must have one of the following forms". We will see a few of these statements focusing
Oct 11 2017

Practical Data-Dependent Metric Compression with Provable Guarantees

Information
Wednesday, October 11, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Ilya Razenshteyn - Columbia University
How well can one compress a dataset of points from a high-dimensional space while preserving pairwise distances? Indyk and Wagner have recently obtained almost optimal bounds for this problem, but
Oct 09 2017

A Reverse Minkowski Theorem

Information
Monday, October 9, 2017
2:00 PM - 3:00 PM
Type: Seminars | Rutgers Discrete Mathematics Seminar
Presenter(s): Noah Stephens-Davidowitz - Princeton University
A classical problem in the geometry of numbers asks us to estimate how many lattice points lie in some ball around the origin. Minkowski's celebrated theorem gives us a tight
Oct 05 2017

Three Lovely Problems from OEIS

Information
Thursday, October 5, 2017
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Neil Sloane - OEIS Foundation
I'll discuss problems from geometry, number theory, and the theory of computing. Poonen and Rubinstein counted the intersection points in a regular n-gon with all diagonals drawn. But what if
Oct 04 2017

Topological Graph Theory

Information
Wednesday, October 4, 2017
12:10 PM - 1:00 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Corrine Yap - Rutgers University
What happens when we take the graphs we know and love and stick them on the torus? What about the Möbius strip? Or the Klein bottle? We'll talk about how
Oct 04 2017

A Computer Scientist Thinks about the Brain

Information
Wednesday, October 4, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Christos Papadimitriou - University of California, Berkeley
When key problems in science are revisited from the computational viewpoint, occasionally unexpected progress results. There is a reason for this: implicit algorithmic processes are present in the great objects
Sep 28 2017

CNF-DNF and All That

Information
Thursday, September 28, 2017
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Doron Zeilberger - Rutgers University
The acronyms CNF and DNF feature prominently in Norbert Blum's brave attempt at proving the most important open problem of our time (with the possible exception of the much more
Sep 27 2017

Entropy

Information
Wednesday, September 27, 2017
12:10 PM - 1:00 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Cole Franks - Rutgers University
Shannon's entropy shows up in many places in mathematics, information theory, and computer science. After an overview of the basic concepts, I will discuss some non-obvious applications of the entropy
Sep 27 2017

On the Quantitative Hardness of CVP

Information
Wednesday, September 27, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Noah Stephens-Davidowitz - Princeton University
For odd integers p >= 1 (and p = infty), we show that the Closest Vector Problem in the ell_p norm (CVP_p) over rank n lattices cannot be solved in
Sep 20 2017

Machine Learning in a Setting of Ordinal Distance Information

Information
Wednesday, September 20, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Matthäus Kleindessner - University of Tübingen
In a typical machine learning scenario we are given numerical dissimilarity values between objects (or feature representations of objects, from which such dissimilarity values can readily be computed). In the
Sep 20 2017

Number of Maximal Independent Sets

Information
Wednesday, September 20, 2017
12:10 PM - 1:00 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Jinyoung Park - Rutgers University
For a given graph G, a subset A of V(G) is independent if no two vertices in A are adjacent. Some time ago, Erdos and Moser asked: what’s the maximum
Sep 14 2017

Sporadic Apéry-like Numbers Modulo Primes

Information
Thursday, September 14, 2017
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Amita Malik - Rutgers University

At the ICM in 1978, R. Apéry's proof of the irrationality of ζ(3) was presented. In this proof, he introduced a sequence of integers, now known as Apéry numbers. Apéry-like

Sep 13 2017

Efficient PAC Learning from the Crowd

Information
Wednesday, September 13, 2017
11:00 AM - 12:00 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Pranjal Awasthi - Rutgers University
In recent years crowdsourcing has become the method of choice for gathering labeled training data for learning algorithms. Standard approaches to crowdsourcing view the process of acquiring labeled data separately
Aug 29 2017

MPE 2013+ Workshop on Chesapeake Fisheries: From Oysters to Economics

Information
Tuesday, August 29, 2017 - Thursday, August 31, 2017
9:30 AM - 10:30 AM
Type: Workshops
Organizer(s): Asamoah Nkwanta | Fred Roberts | Scott Knoche | Margaret (Midge) Cozzens | Abdul-Aziz Yakubu | Richard Lacouture
As part of a series of multidisciplinary workshops under the theme Mathematics of Planet Earth 2013 the workshop on Chesapeake Fisheries will explore issues of the Chesapeake Bay fisheries at both an ecological and economic point of view The oyster population will serve as one motivating example for the workshop
Aug 22 2017

DIMACS Workshop on Distributed Optimization, Information Processing, and Learning

Information
Tuesday, August 22, 2017 - Thursday, August 24, 2017
- 1:30 PM
Type: Workshops
Organizer(s): Alekh Agarwal | Alejandro Ribeiro | Waheed Bajwa

There is an increasing confluence of three major trends in information processing an umbrella term that subsumes signal processing machine learning and statistics The first one of these trends is big data which refers to our ability to continuously collect massive quantities of data across a wide range of modalities