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Chapter and Conference Paper
Discriminative Interpolation for Classification of Functional Data
The modus operandi for machine learning is to represent data as feature vectors and then proceed with training algorithms that seek to optimally partition the feature space
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Chapter and Conference Paper
Augmented Cognition Methods for Evaluating Serious Game Based Insider Cyber Threat Detection Training
DoD investments into cyber threat defense are ongoing; however, little attention is paid to training personnel to detect and prevent threats to cyber networks that come from internal sources. Supervisors need ...
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Chapter and Conference Paper
Today’s Competitive Objective: Augmenting Human Performance
Gaining competitive advantage requires acquiring or develo** a capability that allows an organization or individual to outperform its competitors. In today’s technology-driven environment, where human capabi...
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Chapter and Conference Paper
Individual Differences and the Science of Human Performance
This study comprises the third year of the Robust Automated Knowledge Capture (RAKC) project. In the previous two years, preliminary research was conducted by collaborators at the University of Notre Dame and ...
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Chapter and Conference Paper
Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamical systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding probability distribution over th...
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Chapter and Conference Paper
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding probability distribution over the ...
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Chapter and Conference Paper
Quantifying the Feasibility of Compressive Sensing in Portable Electroencephalography Systems
The EEG for use in augmented cognition produces large amounts of compressible data from multiple electrodes mounted on the scalp. This huge amount of data needs to be processed, stored and transmitted and cons...
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Chapter and Conference Paper
Leveraging Higher Order Dependencies between Features for Text Classification
Traditional machine learning methods only consider relationships between feature values within individual data instances while disregarding the dependencies that link features across instances. In this work, w...
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Chapter and Conference Paper
Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams
In a typical data stream classification task, it is assumed that the total number of classes are fixed. This assumption may not be valid in a real streaming environment, where new classes may evolve. Tradition...