We will discuss a line of recent work on methods for statistical inference in high dimensions. In many real-world applications, samples are not collected cleanly and may be observed subject to systematic corruptions such as missing data and additive noise. We describe how Lasso-based linear regression may be corrected to …
Matt’s talk: Title: Sequential Testing in High Dimensions Sequential methods make use of information as it becomes available, creating an interactive connection between a sampling procedure and information gathered by that procedure. In this talk we explore sequential methods applied to sparse recovery problems, motivated by applications in both communications …
*** Hongbo’s talk: Title: Using a New Nonconvex Singular Value Regularizer in Multivariate Linear Regression. We introduce the weighted singlar value penalization, which uses a nonconvex nonseparable regularizer. We show that in spite of the nonconvexity, one optimization problem with this regularizer is efficiently solvable. Applied to Multivariate Linear Regression, …
***Bryan: Both cognitive constraints and limited amounts of data restrict the complexity of inferential models. Sparse coding is an elegant way to address these restrictions, extracting correlated subparts from data in a way that can be efficient, predictive, and adaptive. We present a sparse coding method for use on binary …
*** Pari’s talk: Title: Group Symmetry and Covariance Regularization Statistical models that possess symmetry arise in diverse settings such as random fields associated to geophysical phenomena, exchangeable processes in Bayesian statistics, and cyclostationary processes in engineering. We formalize the notion of a symmetric model via group invariance. We propose projection …
Transcriptional regulatory networks are networks of genes and transcription factor proteins that determine the context-specific expression pattern of a gene, where a context could represent a time point, a spatial location or a combination of these. Although these networks are a key to accurate information processing and function in living …
*** William’s talk: Title: Secretary Problems with Convex Cost We consider online resource allocation problems where given a set of requests our goal is to select a subset that maximizes a value minus cost type of objective function. Requests are presented online in random order, and each request possesses an …
*** Atul’s talk: Title: The Least-Squares Invertible Constant-Q Spectrogram (LSICQS) and Its Application to Phase Vocoding Building on the idea of a constant-Q transform popularized by Judith Brown in the 1990’s, we will develop a constant-Q spectrogram representation which is invertible in a least-squares sense. We will see that the …
Although the network clustering literature has focused on undirected networks, many networks are directed. For example, communication networks contain asymmetric relationships, representing the flow of information from one person to another. This talk will (1) demonstrate that co-clustering, instead of clustering, is more natural for many directed graphs, (2) propose …
*** Philip Poon Title: Symmetry and spatiotemporal chaos with strong scale separation I will discuss the effect of a continuous symmetry on pattern formation in one spatial dimension. In particular, I will present a study of the Nikolaevskiy equation, a sixth-order PDE, which is a paradigmatic model for pattern dynamics …