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Scherrer, Chad

Publications and source records attributed to Scherrer, Chad.

Feature Clustering for Accelerating Parallel Coordinate Descent

We demonstrate an approach for accelerating calculation of the regularization path for L1 sparse logistic regression problems. We show the benefit of feature clustering as a preconditioning step for parallel block-greedy coordinate descent algorithms.

classification↗

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems

We present a generic framework for parallel coordinate descent (CD) algorithms that has as special cases the original sequential algorithms of Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm of Bradley et al. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and Coloring-Based CD---and give performance measurements for an OpenMP implementation of these.

Scherrer, Chad↗

Indirect Estimation of Radioactivity in Containerized Cargo

Detecting illicit nuclear and radiological material in containerized cargo challenges the state of the art in detection systems. Current systems are being evaluated and new systems envisioned to address the need for the high probability of detection and extremely low false alarm rates necessary to thwart potential threats and extremely low nuisance and false alarm rates while maintaining necessary to maintain the flow of commerce impacted by the enormous volume of commodities imported in shipping containers. Maintaining flow of commerce also means that primary inspection must be rapid, requiring relatively indirect measurements of cargo from outside the containers. With increasing information content in such indirect measurements, it is natural to ask how the information might be combined to improved detection. Toward this end, we present an approach to estimating isotopic activity of naturally occurring radioactive material in cargo grouped by commodity type, combining container manifest data with radiography and gamma spectroscopy aligned to location along the container. The heart of this approach is our statistical model of gamma counts within peak regions of interest, which captures the effects of background suppression, counting noise, convolution of neighboring cargo contributions, and down-scattered photons to provide physically constrained estimates of counts due to decay of specific radioisotopes in cargo alone. Coupled to that model, we use a mechanistic model of self-attenuated radiation flux to estimate the isotopic activity within cargo, segmented by location within each container, that produces those counts. We demonstrate our approach by applying it to a set of measurements taken at the Port of Seattle in 2006. This approach to synthesizing disparate available data streams and extraction of cargo characteristics holds the potential to improve primary inspection using current detection capabilities and to enable simulation-based evaluation of new candidate detection systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

System and method for anomaly detection

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

97 MATHEMATICS AND COMPUTING↗

Hashing Strategies for the Cray XMT

Several strategies for hashing on a Cray XMT are experimentally compared. These strategies are designed to minimize memory contention. Results show good scalability and indicate under what circumstances each of the strategies should be used.

97 MATHEMATICS AND COMPUTING↗

Statistical Detection of Atypical Aircraft Flights

A computational method and software to implement the method have been developed to sift through vast quantities of digital flight data to alert human analysts to aircraft flights that are statistically atypical in ways that signify that safety may be adversely affected. On a typical day, there are tens of thousands of flights in the United States and several times that number throughout the world. Depending on the specific aircraft design, the volume of data collected by sensors and flight recorders can range from a few dozen to several thousand parameters per second during a flight. Whereas these data have long been utilized in investigating crashes, the present method is oriented toward helping to prevent crashes by enabling routine monitoring of flight operations to identify portions of flights that may be of interest with respect to safety issues.

Statler, Irving↗