Information & computer science publications
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Using pathway covering to explore connections among metabolites
Pathway Covering is a new algorithm that takes a list of metabolites (compounds) and determines a minimum-cost set of metabolic pathways in an organism that includes (covers) all the metabolites…
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The Omics Dashboard for interactive exploration of gene-expression data
The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets.
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The Future of the Internet of Things
The IoT can become ubiquitous worldwide—if the pursuit of systemic trustworthiness can overcome the potential risks.
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Building Code for the Internet of Things
In this document, we focus on the challenges associated with composing systems, rather than building individual programs or devices.
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FHE over the Integers: Decomposed and Batched in the Post-Quantum Regime
We propose a comprehensive study of applying third generation FHE techniques to the regime of FHE-OI. We present and analyze a third generation FHE-OI based on decisional AGCD without the…
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Optimization of Bootstrapping in Circuits
We formally define the bootstrap problem, design a polynomial-time L-approximation algorithm using a novel method of rounding of a linear program, and show a matching hardness result: (L — epsilon) - inapproximability for any epsilon…
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Assessment and Content Authoring in Semantic Virtual Environments
This paper presents an approach to training in VEs that directly addresses these challenges and summarizes its application to a weapons maintenance task.
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Sub-Meter Vehicle Navigation Using Efficient Pre-Mapped Visual Landmarks
This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks.
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Probabilistic Inference Modulo Theories
We present SGDPLL(T ), an algorithm that solves probabilistic inference modulo theories, that is, inference problems over probabilistic models defined via a logic theory provided as a parameter.
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Analyzing hyperspectral images into multiple subspaces using Gaussian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low-dimensional subspaces, and that these subspaces are more easily estimated from the data than the endmembers.
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Spatial and Temporal Patterns in Preterm Birth in the United States
In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset.
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Anomaly Detection and Diagnosis for Automatic Radio Network Verification
This paper focuses on the verification problem, proposing a novel framework that uses anomaly detection and diagnosis techniques that operate within a specified spatial scope.