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ACM Transactions on Knowledge Discovery from Data (TKDD), ISSN 1556-4681, 03/2009, Volume 3, Issue 1, pp. 1 - 58
As a prolific research area in data mining, subspace clustering and related problems induced a vast quantity of proposed solutions... 
Survey | clustering | high-dimensional data | High-dimensional data | Clustering | COMPUTER SCIENCE, SOFTWARE ENGINEERING | GENE | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS
Journal Article
IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, 09/2018, Volume 13, Issue 9, pp. 2151 - 2166
High-dimensional crowdsourced data collected from numerous users produces rich knowledge about our society... 
Local differential privacy | private data release | data publication | high-dimensional data | crowdsourced data | NOISE | COMPUTER SCIENCE, THEORY & METHODS | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
International Statistical Review, ISSN 0306-7734, 12/2016, Volume 84, Issue 3, pp. 371 - 389
Summary The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context... 
high‐dimensional data | aggregation | streaming data | networks | dimension reduction | computational complexity | high-dimensional data | REGRESSION | RISK | STATISTICS & PROBABILITY | NONPARAMETRIC-ESTIMATION | ESTIMATORS | TRACKING | SURVEILLANCE | SELECTION | CONFIDENCE | Analysis | Big data | Learning | Concretes | Data management | Funding | Inference | Strategy | Mathematical models | Statistical inference
Journal Article
Computational Statistics and Data Analysis, ISSN 0167-9473, 2007, Volume 52, Issue 1, pp. 502 - 519
Journal Article
IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, 03/2017, Volume 23, Issue 3, pp. 1249 - 1268
Journal Article
Ecology, ISSN 0012-9658, 05/2019, Volume 100, Issue 5, pp. e02676 - n/a
.... A range of statistical methods has been applied to construct hypervolumes but have not yet been applied in the context of ecological data sets with spatial or temporal structure, for example... 
high‐dimensional | Gaussian distribution | multivariate | Countryside Survey | niche | afforestation | high-dimensional | high | dimensional | ECOLOGY | Ecosystem | Ecology | Statistical analysis | Computer simulation | Ecosystems | Data structures | Environmental changes | Statistical methods | Afforestation | Ecosystem assessment | Case studies | Spatial data | Normal distribution | Data sets | Statistical Reports
Journal Article
The Annals of Statistics, ISSN 0090-5364, 2/2009, Volume 37, Issue 1, pp. 246 - 270
The Lasso is an attractive technique for regularization and variable selection for high-dimensional data, where the number of predictor variables $p_{n... 
Approximation | High dimensional spaces | Variable coefficients | Linear regression | Eigenvalues | Signal noise | Mathematical vectors | Estimators | Consistent estimators | Resonance lines | High-dimensional data | Shrinkage estimation | Sparsity | Lasso | REGRESSION | lasso | MODEL SELECTION | high-dimensional data | ADAPTIVE LASSO | STATISTICS & PROBABILITY | sparsity | ASYMPTOTICS | 62F07 | 62J07
Journal Article
Computational Statistics and Data Analysis, ISSN 0167-9473, 03/2014, Volume 71, pp. 52 - 78
Journal Article
Methods in Ecology and Evolution, ISSN 2041-210X, 07/2018, Volume 9, Issue 7, pp. 1772 - 1779
.... This is an especially useful approach for high‐dimensional (multivariate) data. Here, we present an r package that provides a comprehensive suite of tools for applying RRPP to linear models... 
multivariate | generalized least‐squares | high‐dimensional data | dissimilarity | generalized least-squares | high-dimensional data | REGRESSION | SHAPE | MATRICES | ECOLOGY | VARIANCE | PERMUTATION TESTS | MULTIVARIATE-ANALYSIS | Permutations | Randomization | Statistical analysis | Downstream effects | Data processing | Mathematical models | Statistical tests | Coefficients | Multivariate analysis | Variance analysis | Empirical analysis | Matrix methods
Journal Article
Science Signaling, ISSN 1945-0877, 06/2016, Volume 9, Issue 432, pp. re6 - re6
Clustering is an unsupervised learning method, which groups data points based on similarity, and is used to reveal the underlying structure of data... 
GENE-EXPRESSION DATA | HIGH-DIMENSIONAL DATA | CLINICALLY RELEVANT SUBTYPES | PHOSPHORYLATION | K-MEANS | BIOCHEMISTRY & MOLECULAR BIOLOGY | VALIDATION | PROLIFERATION | MICROARRAY DATA | DISCOVERY | SIGNALING NETWORKS | CELL BIOLOGY | Models, Theoretical | Animals | Humans | Automatic Data Processing | Databases, Factual
Journal Article
IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, 01/2020, Volume 26, Issue 1, pp. 291 - 300
With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in... 
Analytical models | High-Dimensional Space | Data analysis | Computational modeling | Data visualization | Topological Data Analysis | Inertial Confinement Fusion | Predictive models | Topology | Physics | Model Evaluation | Deep Learning | COMPUTER SCIENCE, SOFTWARE ENGINEERING | EXPLORATION
Journal Article
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, ISSN 1364-503X, 11/2009, Volume 367, Issue 1906, pp. 4237 - 4253
.... This overview article introduces the difficulties that arise with high-dimensional data in the context of the very familiar linear statistical model... 
MATHEMATICS | statistics | Cluster analysis | High-dimensional data | Regression | Sparsity | Bayesian analysis | Classification | Linear Models | Bayes Theorem | Statistics as Topic - methods | 1008 | regression | high-dimensional data | sparsity | classification | cluster analysis | 175
Journal Article