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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A Cross-language Study on Automatic Speech Disfluency Detection
We investigate two systems for automatic disfluency detection on English and Mandarin conversational speech data. The first system combines various lexical and prosodic features in a Conditional Random Field model for…