Quantum annealing for combinatorial clustering
Sign Up to like & getrecommendations! Published in 2018 at "Quantum Information Processing"
DOI: 10.1007/s11128-017-1809-2
Abstract: Clustering is a powerful machine learning technique that groups “similar” data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between… read more here.
Keywords: quantum; search; annealing combinatorial; data points ... See more keywords
Construct boundaries and place labels for multi-class scatterplots
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Visualization"
DOI: 10.1007/s12650-021-00791-x
Abstract: Abstract Drawing boundaries and appending text labels for each class of multi-class scatterplot are two common steps to help people perceive and understand class-level spatial and semantic information hidden in the scatterplot. However, massive data… read more here.
Keywords: class; step; boundaries place; data points ... See more keywords
Computerized quantification of drugs synergism in animal studies or in clinical trials using only ten data points
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DOI: 10.1016/j.synres.2019.100049
Abstract: Abstract The median-effect equation (MEE) derived from the mass-action law (MAL) is the unified theory of dose-effect pharmacodynamics (PD) and biodynamics (BD). MEE enables the linearization of a dose-effect curve into a straight linedefined by… read more here.
Keywords: drug; animal studies; data points; effect ... See more keywords
Responsiveness of the EAT-10 to Clinical Change in Head and Neck Cancer Patients with Dysphagia
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Speech-Language Pathology"
DOI: 10.1080/17549507.2019.1596312
Abstract: Abstract Purpose: This retrospective study evaluated the external responsiveness of the Eating Assessment Tool-10 (EAT-10) to clinical changes in a single cohort (n = 105) treated with chemoradiotherapy (CRT) or radiotherapy (RT) for head-and-neck cancer. Method: Patients… read more here.
Keywords: neck cancer; eat clinical; data points; pathology ... See more keywords
Undergraduate students’ reasoning about the quality of experimental measurements of covarying secondary data
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DOI: 10.1088/1361-6404/abfd27
Abstract: We have investigated how first-year and second-year university students judge the quality of secondary experimental data consisting of measurements of covarying quantities, and to what extent they consider multiple measurements of covarying quantities as a… read more here.
Keywords: students reasoning; derived quantity; quality; data points ... See more keywords
Towards an optimal sampling of peculiar velocity surveys for Wiener Filter reconstructions
Sign Up to like & getrecommendations! Published in 2017 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stx557
Abstract: The Wiener Filter (WF) technique enables the reconstruction of density and velocity fields from observed radial peculiar velocities. This paper aims at identifying the optimal design of peculiar velocity surveys within the WF framework. The… read more here.
Keywords: wiener filter; reconstruction; data points; velocity ... See more keywords
Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection
Sign Up to like & getrecommendations! Published in 2021 at "Philosophical Transactions of the Royal Society B: Biological Sciences"
DOI: 10.1098/rstb.2020.0266
Abstract: As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and… read more here.
Keywords: detection; trend fitting; trend; data points ... See more keywords
Visual Identification and Extraction of Intrinsic Axes in High-Dimensional Data
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DOI: 10.1109/access.2019.2922997
Abstract: Interactive axis extraction for high-dimensional data visualization has been demonstrated to be powerful in high-dimensional data exploring and understanding. The extracted axes help to yield new 2-D arrangements of data points, providing new insights into… read more here.
Keywords: intrinsic axes; dimensional data; data points; high dimensional ... See more keywords
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2020.3045533
Abstract: This letter considers the problem of multi-agent distributed linear regression in the presence of system noises. In this problem, the system comprises multiple agents wherein each agent locally observes a set of data points, and… read more here.
Keywords: data points; problem; method; linear regression ... See more keywords
Adaptive Maximum Entropy Graph-Guided Fast Locality Discriminant Analysis.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3125956
Abstract: Linear discriminant analysis (LDA) aims to find a low-dimensional space in which data points in the same class are to be close to each other while keeping data points from different classes apart. To improve… read more here.
Keywords: analysis; data points; discriminant analysis; locality discriminant ... See more keywords
Community Recovery in Hypergraphs
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2019.2920637
Abstract: Community recovery is a central problem that arises in a wide variety of applications such as network clustering, motion segmentation, face clustering, and protein complex detection. The objective of the problem is to cluster data… read more here.
Keywords: community; number; data points; community recovery ... See more keywords