Wed, 30 Nov 2016
11:30
N3.12

Partition Identities, Q-series and the Quest for Rogers-Ramanujan Involutions

Adam Keilthy
(University of Oxford)
Abstract
This talk will introduce some arguably trivial results about partition identities, and generating functions for various counts of partitions. We will discuss methods of proving q-series identities via bijections of partitions, and proving partition identities via analytic methods. We will then comment on the Rogers-Ramanujan identities, their combinatorial interpretation, and their various methods of proof.

Beauty is in the eye of the beholder, but what about symmetry? In our final feature on mathematicians let loose in the Ashmolean Museum, Oxford Mathematician Balázs Szendrői investigates the beauty of symmetry in the Museum's Islamic art works. As he explains, no matter what the tile pattern may look like, its underlying symmetry configuration belongs to a small set of possibilities. 

Fri, 25 Nov 2016

15:00 - 16:00
S0.29

Hyperbolic Dehn filling in dimension four

Stefano Riolo
(University of Pisa)
Abstract

By gluing copies of a deforming polytope, we describe some deformations of complete, finite-volume hyperbolic cone four-manifolds. Despite the fact that hyperbolic lattices are locally rigid in dimension greater than three (Garland-Raghunathan), we see a four-dimensional analogue of Thurston's hyperbolic Dehn filling: a path of cone-manifolds $M_t$ interpolating between two cusped hyperbolic four-manifolds $M_0$ and $M_1$.

This is a joint work with Bruno Martelli.

Tue, 29 Nov 2016

12:45 - 13:30
C5

Community Detection in Annotated Bipartite Networks

Roxana Pamfil
(University of Oxford)
Abstract

A successful programme of personalised discounts and recommendations relies on identifying products that customers want, based both on items bought in the past and on relevant products that the customers have not yet purchased. Using basket-level grocery shopping data, we aim to use clustering ("community detection") techniques to identify groups of shoppers with similar preferences, along with the corresponding products that they purchase, in order to design better recommendation systems.


Stochastic block models (SBMs) are an increasingly popular class of methods for community detection. In this talk, I will expand on some work done by Newman and Clauset [1] that uses a modified SBM for community detection in annotated networks. In these networks, additional information in the form of node metadata is used to improve the quality of the inferred community structure. The method can be extended to bipartite networks, which contain two types of nodes and edges only between nodes of different types. I will show some results obtained from applying this method to a bipartite network of customers and products. Finally, I will discuss some desirable extensions to this method such as incorporating edge weights and assessing the relationship between metadata and network structure in a statistically robust way.


[1] Structure and inference in annotated networks, MEJ Newman and A Clauset, Nature Communications 7, 11863 (2016).


Note: This talk will cover similar topics to my presentation in the InFoMM group meeting on Friday, November 25 but it won't be exactly the same. I will focus more on the mathematical details for my JAMS talk.
 

Wed, 23 Nov 2016

16:00 - 17:00

Quasi-convexity and Howson's Theorem

Giles Gardam
(Oxford University)
Abstract

This talk will introduce the notion of quasi-convex subgroups. As an application, we will prove that the intersection of two finitely generated subgroups of a free group is again finitely generated.
 

Thu, 09 Mar 2017

16:00 - 17:30
L4

Modelfree portfolio optimization in the long run

Christa Cuchiero
Abstract

Cover’s celebrated theorem states that the long run yield of a properly chosen “universal” portfolio is as good as the long run yield of the best retrospectively chosen constant rebalanced portfolio. We formulate an abstract principle behind such a universality phenomenon valid for general optimization problems in the long run. This allows to obtain new results on modelfree portfolio optimization, in particular in continuous time, involving larger classes of investment strategies. These modelfree results are complemented by a comparison with the log-optimal numeraire portfolio when fixing a stochastic model for the asset prices. The talk is based on joint work with Walter Schachermayer and Leonard Wong.

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