Reduced-order modeling is often utilized in obtaining an approximate solution to a complex high-fidelity system. An essential step in constructing a reduced-order system is to project the original high-fidelity system onto ...

After a defense of the claim that cognitive structure cannot exist apart from actions (a claim which I refer to as "No-semantically-empty-structure"), I introduce PAGI World, a simulation environment rich enough in possible ...

Specifically, the proposed model consists of three parts: the first part is a Poisson spatial autoregressive regression model for count data (i.e., small positive integers); the second part characterizes virtual connections ...

We call this the two-step neural network algorithm, which is capable of training and predicting on multiple machines. The first step of this algorithm is an unsupervised autoencoder trained to capture the normal behavior ...

Neutron detectors are useful for a number of applications, including the identification of nuclear weapons, radiation dosimetry, and nuclear reactor monitoring, among others. Microstructured solid-state neutron detectors ...

As the amount of information stored as text grows, being able to efficiently organize and sort the available information becomes crucial. Supervised learning methods provide a solution for some of these tasks, however they ...

This thesis presents a series of orthogonal memory system design techniques that leverage the characteristics of various applications to optimize memory fault tolerance in highly scaled memory technologies. This thesis ...

Automatic activity detections and forecasts can allow a controller to prompt for meals and anticipate exercise. To this end, an automatic activity detection framework using a smartwatch and smartphone has been developed. ...