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Research in Data Science

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Cover of 'Research in Data Science'

Table of Contents

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    Book Overview
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    Chapter 1 Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
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    Chapter 2 The Hubness Phenomenon in High-Dimensional Spaces
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    Chapter 3 Heuristic Framework for Multiscale Testing of the Multi-Manifold Hypothesis
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    Chapter 4 Interdisciplinary Approaches to Automated Obstructive Sleep Apnea Diagnosis Through High-Dimensional Multiple Scaled Data Analysis
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    Chapter 5 The ℓ ∞ -Cophenetic Metric for Phylogenetic Trees As an Interleaving Distance
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    Chapter 6 Inference of a Dyadic Measure and Its Simplicial Geometry from Binary Feature Data and Application to Data Quality
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    Chapter 7 A Non-local Measure for Mesh Saliency via Feature Space Reduction
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    Chapter 8 Feature Design for Protein Interface Hotspots Using KFC2 and Rosetta
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    Chapter 9 Geometry-Based Classification for Automated Schizophrenia Diagnosis
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    Chapter 10 Compressed Anomaly Detection with Multiple Mixed Observations
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    Chapter 11 Analysis of Simulated Crowd Flow Exit Data: Visualization, Panic Detection and Exit Time Convergence, Attribution, and Estimation
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    Chapter 12 A Data Driven Modeling of Ornaments
Attention for Chapter 2: The Hubness Phenomenon in High-Dimensional Spaces
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Chapter title
The Hubness Phenomenon in High-Dimensional Spaces
Chapter number 2
Book title
Research in Data Science
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-030-11566-1_2
Book ISBNs
978-3-03-011565-4, 978-3-03-011566-1
Authors

Priya Mani, Marilyn Vazquez, Jessica Ruth Metcalf-Burton, Carlotta Domeniconi, Hillary Fairbanks, Gülce Bal, Elizabeth Beer, Sibel Tari, Mani, Priya, Vazquez, Marilyn, Metcalf-Burton, Jessica Ruth, Domeniconi, Carlotta, Fairbanks, Hillary, Bal, Gülce, Beer, Elizabeth, Tari, Sibel

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