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Linear Dimensionality Reduction: What Is Better?

Data
This research paper focuses on dimensionality reduction, which is a major subproblem in any data processing operation. Dimensionality reduction based on principal components is the most used methodology. Our paper examines three heuristics, namely Kaiser’
Mohit Baliyan, Evgeny M. Mirkes
doaj   +1 more source

The principal independent components of images [PDF]

, 2010
This paper proposes a new approach for the encoding of images by only a few important components. Classically, this is done by the Principal Component Analysis (PCA).
Arlt, Björn, Brause, Rüdiger W.
core  

Nutritional and Behavioral Intervention for Long‐Term Childhood Acute Leukemia Survivors With Metabolic Syndrome

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Metabolic syndrome (MetS) is a common complication in survivors of childhood acute lymphoblastic and myeloid leukemia (AL), and a major risk factor for premature cardiovascular disease, type‐2‐diabetes, and metabolic dysfunction‐associated steatotic liver disease (MASLD).
Visentin Sandrine, Béliard Sophie, Renard Cécile, Caussy Cyrielle, Hamidou Zeinab, Romano David, Gacem Mélanie, Petit Arnaud, Saultier Paul, Borentain Patrick, Michel Gérard   +10 more
wiley   +1 more source

Estimating Common Principal Components in High Dimensions

, 2013
We consider the problem of minimizing an objective function that depends on an orthonormal matrix. This situation is encountered when looking for common principal components, for example, and the Flury method is a popular approach.
Browne, Ryan P., McNicholas, Paul D.
core   +1 more source

Robust functional principal components: A projection-pursuit approach [PDF]

, 2011
In many situations, data are recorded over a period of time and may be regarded as realizations of a stochastic process. In this paper, robust estimators for the principal components are considered by adapting the projection pursuit approach to the ...
Bali, Juan Lucas, Boente, Graciela, Tyler, David E., Wang, Jane-Ling   +3 more
core   +2 more sources

Parameterized principal component analysis [PDF]

Pattern Recognition, 2018
When modeling multivariate data, one might have an extra parameter of contextual information that could be used to treat some observations as more similar to others. For example, images of faces can vary by age, and one would expect the face of a 40 year old to be more similar to the face of a 30 year old than to a baby face.
Ajay Gupta, Adrian Barbu
openaire   +2 more sources

Survival for Children Diagnosed With Wilms Tumour (2012–2022) Registered in the UK and Ireland Improving Population Outcomes for Renal Tumours of Childhood (IMPORT) Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga, Angela Lopez‐Cortes, Reem Al‐Saadi, Suzanne Tugnait, Kristina Dzhuma, Catriona Duncan, Gordan Vujanic, Tanzina Chowdhury, Claudia Allemani, Michel P. Coleman, Kathy Pritchard‐Jones, the Children's Cancer and Leukaemia Group (CCLG) Renal Tumour Special Interest Group, Hugh Bishop, Anthony McCarthy, Pamela Kearns, Helen Rees, Amos Burke, Meriel Jenney, Jane Pears, Hamish Wallace, Milind Ronghe, Tanzina Chowdhury, Susan Picton, Emma Ross, Lisa Howell, Bernadette Brennan, Gail Halliday, Richard Grundy, Shaun Wilson, Sucheta Vaidya, Daniel Yeomanson, Jessica Bate, Vesna Pavasovic, Jessica Bate, Sabine Irtan, Jesper Brok, Minou Oostveen, Kristina Dzhuma, Mark Weeks, Richard Williams, Mark Powis, Max Pachl, Bruce Okoye, Naima Smeulders, Gordan Vujanic, Oystein Olsen, Tom Watson, Susan Shelmerdine, Dan Saunders, Angela Lopez-Cortes, Taryn Treger, Tom Jackson, Suzanne Tugnait, Lisa Howell, Tanzina Chowdhury, Sam Behjati, Angela Polanco   +56 more
wiley   +1 more source

Simple Principal Components

Journal of the Royal Statistical Society Series C: Applied Statistics, 2000
SUMMARY We introduce an algorithm for producing simple approximate principal components directly from a variance–covariance matrix. At the heart of the algorithm is a series of ‘simplicity preserving’ linear transformations. Each transformation seeks a direction within a two-dimensional subspace that has maximum variance.
openaire   +1 more source

Principal Component Projection Without Principal Component Analysis

, 2016
We show how to efficiently project a vector onto the top principal components of a matrix, without explicitly computing these components. Specifically, we introduce an iterative algorithm that provably computes the projection using few calls to any black-box routine for ridge regression.
Frostig, Roy, Musco, Cameron, Musco, Christopher, Sidford, Aaron   +3 more
openaire   +2 more sources

The MedSupport Multilevel Intervention to Enhance Support for Pediatric Medication Adherence: Development and Feasibility Testing

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction We developed MedSupport, a multilevel medication adherence intervention designed to address root barriers to medication adherence. This study sought to explore the feasibility and acceptability of the MedSupport intervention strategies to support a future full‐scale randomized controlled trial.
Elizabeth G. Bouchard, Hital Patel, Paula C. Vincent, Justine Kahn, Kira Bona, Thai Hoa Tran, Elisa M. Rodriguez, Kristopher Attwood, Kara M. Kelly   +8 more
wiley   +1 more source