Sparse principal component analysis

Results 131 to 140 of about 50,718 (252)

A sparse principal component analysis of Class III malocclusions. [PDF]

Angle Orthod, 2019
Kang TJ, Eo SH, Cho H, Donatelli RE, Lee SJ. +4 more
europepmc +1 more source

Synergistic Interfacial Regulation by Nano‐TiO2 and Carboxylated Cellulose Nanofibers for Multiscale Surface Stabilization of Cementitious Composites

Advanced Materials Technologies, EarlyView.
Nano‐TiO2 and carboxylated cellulose nanofibers jointly regulate hydration‐product distribution in cementitious composites. Improved microstructural continuity and refined pore structure accompany enhanced strength and surface stability without a substantial increase in overall hydration.
Kailun Chen +8 more
wiley +1 more source

Integrative sparse principal component analysis of gene expression data. [PDF]

Genet Epidemiol, 2017
Liu M, Fan X, Fang K, Zhang Q, Ma S.
europepmc +1 more source

Microwall‐Integrated Terahertz Metasurfaces for Spatially Guided Label‐Free Sensing of Micrometer‐Scale Plastic Particles

Advanced Materials Technologies, EarlyView.
A THz metasurface device integrating a metal–dielectric–metal resonator with microwall‐defined recessed regions enables spatially guided, label‐free sensing of micrometer‐scale plastic particles. The as‐fabricated devices exhibit distinct THz reflection resonances for 3.1‐µm polystyrene particles and a concentration‐dependent resonance‐frequency‐shift ...
Naoki Inomata, Yuki Sakai, Yoshiaki Kanamori +2 more
wiley +1 more source

Dense Message Passing for Sparse Principal Component Analysis.

Journal of Machine Learning Research, 2010
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of this type. MCMC procedures are too slow to be practical in a very high-dimensional setting and standard mean-field variational Bayes algorithms are ineffective.
Sharp, Kevin, Rattray, Magnus
openaire +2 more sources

Multilevel Embedding and Dropout for Improved 3D Object Detection in Autonomous Driving Systems

Advanced Robotics Research, EarlyView.
A plug‐in framework for RoI‐based 3D object detectors exploits previously untapped multi‐level information within RoI features. Its novel multi‐level embedding and dropout strategy enables the detection head to generate predictions at different feature levels.
Xiaohu Lu, Hayder Radha
wiley +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source

Localized Sparse Principal Component Analysis of Multivariate Time Series in the Frequency Domain. [PDF]

J Am Stat Assoc
Namdari J, Manatunga A, Ferrarelli F, Krafty RT. +3 more
europepmc +1 more source

Sparse principal component analysis in cancer research. [PDF]

Transl Cancer Res, 2014
Hsu YL, Huang PY, Chen DT.
europepmc +1 more source

principal component analysis
medicine