Minimax rank estimation for subspace tracking

Rank estimation is a classical model order selection problem that arises in a variety of important statistical signal and array processing systems, yet is addressed relatively infrequently in the extant literature. Here we present sample covariance asymptotics stemming from random matrix theory, and bring them to bear on the problem of optimal rank estimation in the context of the standard array observation model with additive white Gaussian noise. The most significant of these results demonstrates the existence of a phase transition threshold, below which eigenvalues and associated eigenvectors of the sample covariance fail to provide any information on population eigenvalues. We then develop a decision-theoretic rank estimation framework that leads to a simple ordered selection rule based on thresholding; in contrast to competing approaches, however, it admits asymptotic minimax optimality and is free of tuning parameters. We analyze the asymptotic performance of our rank selection procedure and conclude with a brief simulation study demonstrating its practical efficacy in the context of subspace tracking.Comment: 10 pages, 4 figures; final versio

Deep Learning For Smile Recognition

Inspired by recent successes of deep learning in computer vision, we propose a novel application of deep convolutional neural networks to facial expression recognition, in particular smile recognition. A smile recognition test accuracy of 99.45% is achieved for the Denver Intensity of Spontaneous Facial Action (DISFA) database, significantly outperforming existing approaches based on hand-crafted features with accuracies ranging from 65.55% to 79.67%. The novelty of this approach includes a comprehensive model selection of the architecture parameters, allowing to find an appropriate architecture for each expression such as smile. This is feasible because all experiments were run on a Tesla K40c GPU, allowing a speedup of factor 10 over traditional computations on a CPU.Comment: Proceedings of the 12th Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS 2016

Fresh Silo Polish, Serf!

I find the art of palindrome creation both fascinating and ridiculous. The difficulty, especially with longer ones, is trying to insure that everything makes sense. It never does, so I content myself with developing a theme of sorts and hope the other 70 or 80 per cent of the words are not too bothersome

Morphological Complexity and Conceptualization : The Human Body

In this squib, I want to argue that the morphological structure of words is, at least to some extent, motivated. As an example I have choosen the partonomic (and for the less part taxonomic) nomenclature of the human body. While important work by Brown et alii (1973), Anderson (1978) and Schladt (1997) exists on this topic, these analyses focus on the conceptualization of body-parts and their semantics, but not on their morphological representation. In the following, I want to check two predictions about the morphological complexity of lexical items denoting parts of the human body. The first assumption is that the most canonical body-parts are always expressed by mono-lexematic items. The second one consists in the assumption that body-parts of the lowest levels in the hierarchy are always morphologically complex. A set of six body-parts has been analysed in 27 languages. The set consists of two canonical (HEAD and EAR) and of one from the lowest level of the hierarchy (TOENAIL). For this I have adopted a sample from Schladt (1997) and a small one compiled by mysel

Evaluating Motivational Interviewing in the Physician Assistant Curriculum

Purpose Motivational interviewing (MI) is an evidence-based technique that enables clinicians to help patients modify health behaviors. Although MI is an essential tool for physician assistants (PAs), the extent to which it is addressed in PA curricula in the United States is unknown. This study is a comprehensive description of MI education in PA programs in the United States. Methods Data are from the 2014 Physician Assistant Education Association Annual Program Survey. Descriptive statistics were conducted on de-identified data from all 186 PA programs in the United States. Results Of the 186 PA programs surveyed, 72.58% (n = 135) reported at least one course providing MI training. Availability of courses providing training in skills essential to the MI process varied. Having a course with verbal communication training was most frequently endorsed, and having a course with training in developing discrepancy was least frequently endorsed. The most popular teaching modality was lecture (84.95%, n = 158), whereas only 41.40% (n = 77) and 58.60% (n = 109) reported role play with evaluation and standardized patient exercises with evaluation, respectively. Conclusions More than 70% of programs included at least one course in their curriculum that provided training in MI, suggesting that PA programs recognize the importance of MI. Instruction in change talk was not provided in nearly half of the programs. Role-play and standardized patient exercises with evaluation were underused methods despite their proven efficacy in MI education. As the first comprehensive benchmark of MI education for PAs, this study shows that although most programs address MI, opportunities exist to improve MI training in PA programs in the United States