Results 31 to 40 of about 9,586,369 (306)

Recent Advances in Supervised Dimension Reduction: A Survey

Machine Learning and Knowledge Extraction, 2019
Recently, we have witnessed an explosive growth in both the quantity and dimension of data generated, which aggravates the high dimensionality challenge in tasks such as predictive modeling and decision support.
Guoqing Chao, Yuan Luo, Weiping Ding
semanticscholar   +1 more source

Application of Dimension Reduction Methods for Stress Detection

International Journal of Pioneering Technology and Engineering, 2023
Effective detection of stress situations plays an important role in combating it. This is the main source of motivation for research to identify and evaluate different psychological conditions.
Erhan Bergil
doaj   +1 more source

Counting Process Based Dimension Reduction Methods for Censored Outcomes [PDF]

, 2018
We propose a class of dimension reduction methods for right censored survival data using a counting process representation of the failure process. Semiparametric estimating equations are constructed to estimate the dimension reduction subspace for the ...
Sun, Qiang, Wang, Tao, Zeng, Donglin, Zhu, Ruoqing   +3 more
core   +3 more sources

Aggregate Kernel Inverse Regression Estimation

Mathematics, 2023
Sufficient dimension reduction (SDR) is a useful tool for nonparametric regression with high-dimensional predictors. Many existing SDR methods rely on some assumptions about the distribution of predictors. Wang et al.
Wenjuan Li, Wenying Wang, Jingsi Chen, Weidong Rao   +3 more
doaj   +1 more source

Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

Journal of Statistical Software, 2019
We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data.
Angelos Markos, A. I. D'Enza, M. V. deVelden   +2 more
semanticscholar   +1 more source

Incremental dimension reduction of tensors with random index [PDF]

, 2011
We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable.
B Emruli, Blerim Emruli, D Achlioptas, DM Kane, E Velldal, Fredrik Sandin, I Fronza, J Karlgren, J Matoušek, K Lund, M Baroni, M Berry, M Sahlgren, M Wan, Magnus Sahlgren, MWM Boyd, N Goel, N Halko, P Frankl, P Kanerva, P Kanerva, PD Turney, RG Baraniuk, S Dasgupta, S Deerwester, Science Staff, SS Vempala, T Cohen, T Cohen, TG Kolda, TK Landauer, V Vasuki, W Johnson   +32 more
core   +3 more sources

Metric dimension reduction: A snapshot of the Ribe program [PDF]

International Congress of Mathematicans, 2018
The purpose of this article is to survey some of the context, achievements, challenges and mysteries of the field of metric dimension reduction, including new perspectives on major older results as well as recent advances.
A. Naor
semanticscholar   +1 more source

Scaled PCA: A New Approach to Dimension Reduction

Management Sciences, 2019
This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scaling each predictor with its predictive slope on the target ...
Dashan Huang, Fuwei Jiang, Kunpeng Li, Guoshi Tong, Guofu Zhou   +4 more
semanticscholar   +1 more source

A novel three-dimensional strapping reduction for the treatment of patellar fractures

Journal of Orthopaedic Surgery and Research, 2019
Objective This study aimed to investigate the effectiveness of a three-dimensional strapping reduction in the treatment of patellar fractures. Methods Between January 2015 and June 2017, a total of 56 patients were randomly allocated to the three ...
Wei Jiang, Yusheng Li, Ronak Naveenchandra Kotian, Bowen Lin, Xiaoming Zhang   +4 more
doaj   +1 more source

Bounds on Dimension Reduction in the Nuclear Norm [PDF]

, 2019
$ \newcommand{\schs}{\scriptstyle{\mathsf{S}}_1} $For all $n \ge 1$, we give an explicit construction of $m \times m$ matrices $A_1,\ldots,A_n$ with $m = 2^{\lfloor n/2 \rfloor}$ such that for any $d$ and $d \times d$ matrices $A'_1,\ldots,A'_n$ that ...
B Brinkman, BS Tsirelson, D Ostrev, I Abraham, J Bourgain, J Matoušek, JR Lee, K Ball, S Okubo, SJ Summers, W Slofstra   +10 more
core   +2 more sources