Learning the structure of graphical models from data is a fundamental task in many scientific domains. I will describe analysis and applications of learning graphical models. We analyze the theoretical properties of a well-known structure learning algorithm known as the Chow-Liu algorithm (1968). The Chow-Liu algorithm learns the maximum-likelihood (ML) …
In wireless communications and networks, the average delay packets experience is an important quality of service criterion. Therefore, it is imperative to design advanced transmission schemes to jointly address the goals of reliability, high rates and low delay. I will first talk about the delay-optimal rate allocation in a multiple …
This week, we’ll hear belated summaries from three graduate students about their internships over the summer. Each presenter will speak for about 15 minutes. John Brady — NASA Langley Research Center. John worked on testing and modifying a communications protocol for use in the Climate Absolute Radiance and Refractivity Observatory …
The Discrete Fourier Transform (DFT) is one of the most important operators in computational mathematics.The DFT operator acts on the n-dimenional Hilbert Space of complex valued functions on the group of integers modulo-n. It becames very useful in the last century due to the Cooley–Tukey algorithm that computes this transform …
Given the proliferation of wireless communication devices, the need for increased power and bandwidth efficiencyin emerging technologies is getting ever more pronounced. Two echnological trends offer new opportunities for addressing these challenges: mm-wave systems (60-100GHz) that afford large bandwidths, and multi-antenna (MIMO) transceivers that exploit the spatial dimension. In particular, …
Phase retrieval is the recovery of signals from Fourier transform magnitude with wide applications in crystallography, microscopy, optics, and astronomy. Although a unique solution almost always exists for two or higher dimensional signals, there is no known algorithm with guaranteed recovery. An iterative algorithm for recovering nonnegative real signals, based …
For functions acquired through point evaluations, is there an optimal way to estimate a quantity of interest or even to approximate the functions in full? We give an affirmative answer to this question under the novel assumption that the functions belong to a model set defined by approximation capabilities. In …
Pregnancy loss is a primary limit on human reproduction and a key driver of population dynamics. It is also very difficult to study. 85% of pregnancy loss happens prior to clinical interaction. We use information from over a million users of a fertility tracking application to construct estimates of pregnancy …
Entity matching (EM) finds data instances that refer to the same real-world entity. In 2015, we started the Magellan project at UW-Madison to build EM systems. Most current EM systems are stand-alone monoliths. In contrast, Magellan borrows ideas from the field of data science (DS), to build a novel kind …
Given a data set $\mathcal{X}=\{x_1, \dots, x_n\}$ and a weighted graph structure $\Gamma= (\mathcal{X},W)$ on $\mathcal{X}$, graph based methods for learning use analytical notions like graph Laplacians, graph cuts, and Sobolev semi-norms to formulate optimization problems whose solutions serve as sensible approaches to machine learning tasks. When the data set …