Topological data analysis looks at data from a rather unique angle. Good news: it may provide additional information to traditional machine learning, hence benefiting downstream applications. Bad news: Let K be the social network over topologists and machine learners, then betti0(K)=2. Why this means they didn’t talk to each other …
This talk gives an introduction to a recently established link between the geometry of numbers and mixed integer linear optimization. The main focus is to provide a review of families of lattice-free polyhedra and their use in the context of deriving and explaining cutting planes for mixed integer programs. This …
We provide a high level overview of the information theoretic study of two-way networks. We start by introducing the capacity / capacity region of a channel / network, respectively. While we know the capacity of one-way point-to-point channels where there is one source and one destination, we do not know …
The problem of low rank estimation naturally arises in a number of functional or relational data analysis settings, for example when dealing with spatio-temporal data or link prediction with attributes. We consider a unified framework for these problems and devise a novel penalty function to exploit the low rank structure …
A fundamental task in wireless communication is channel estimation: Compute the channel parameters of a medium between a transmitter and a receiver. In this talk we will treat the case of delay-Doppler channels — thus a signal, while transmitted, undergoes time-frequency shifts. We will introduce the incidence and cross methods …
Modern wireless technology enables the vision of future large scale systems such as the SmartGrid, a network of ubiquitous and heterogeneous devices wirelessly connected to the Internet, and wireless health monitoring and health modifying sensor networks over communities and not just individuals. All of these applications necessitate methods that simultaneously …
As computer vision algorithms have become more and more sophisticated in the task of object detection, semantic learning remains a harder goal to achieve. Let us assume that a good object detection/feature extraction algorithm is given, how does one build on that information to gain context about the semantic label …
Independent Component Analysis (ICA) models are very popular semi- parametric models in which we observe independent copies of a random vec- tor X = AS, where A is a non-singular matrix and S has independent compo- nents. We propose a new way of estimating the unmixing matrix W = A^{-1} …
Complex networks and information seeks to understand mathematically how fundamental approaches to information exchange influence overall network and system performance and behavior. From this understanding we wish to develop strategies to assess and influence the predictability and performance of heterogeneous types of networks and information systems that must provide reliable …