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 …
The question of how and whether to join physical layer and network coding remains actively investigated. In this talk, we present some recent information-theoretic results and an application illustrating a view of this question. We begin by considering whether there are benefits, in capacity, from integrating network and physical layer …
We will discuss two mechanisms for dealing with integer programs that contain a great deal of symmetry—orbital branching and isomorphism pruning. These methods use information encoded in the symmetry group of the integer program to guide the branching decision and prune nodes of the search tree. Orbital branching and isomorphism …
We describe a novel approach to online convex programming in dynamic settings. Many existing online learning methods are characterized via regret bounds that quantify the gap between the performance of the online algorithm relative to a comparator. In previous work, this comparator was either considered static over time, or admitted …
This presentation will review the state of the art in atom probe tomography (APT) and emphasize the successes and remaining challenges. The presentation will conclude with a look toward future developments that will enhance APT. One of the key challenges is information processing such as reconstruction of our images and …
We present a simple technique for estimating parts of the Singular Value Decomposition (SVD) of a data matrix from a small randomly compressed “sketch” of that matrix. In sensor network settings–where each column of the data matrix comes from a separate sensor–the sketch can be assembled using operations local to …
An extremely powerful tool in the field of topological data analysis (TDA) is persistent homology which seeks to quantify structure in a large data set. In particular, persistence can find homology classes for an underlying manifold even when obscured by noise. These homology classes can then give information about the …