Dynamic L1-norm Tucker tensor decomposition
Tucker decomposition is a standard method for processing multi-way (tensor)
measurements and finds many applications in machine learning and data mining, among …
measurements and finds many applications in machine learning and data mining, among …
AI Computation of L1-Norm-Error Principal Components With Applications to Training Dataset Curation and Detection of Change
K Varma - 2024 - search.proquest.com
The aim of this dissertation is to achieve a thorough understanding and develop an
algorithmic framework for a crucial aspect of autonomous and artificial intelligence (AI) …
algorithmic framework for a crucial aspect of autonomous and artificial intelligence (AI) …
Autonomous plankton classification from reconstructed holographic imagery by l1-pca-assisted convolutional neural networks
Studying and monitoring plankton distribution is vital for global climate and environment
protection as they are the most elementary part of oceanic eco-systems. However, the …
protection as they are the most elementary part of oceanic eco-systems. However, the …
[BOOK][B] Dynamic Algorithms and Asymptotic Theory for Lp-norm Data Analysis
M Dhanaraj - 2022 - search.proquest.com
The focus of this dissertation is the development of outlier-resistant stochastic algorithms for
Principal Component Analysis (PCA) and the derivation of novel asymptotic theory for Lp …
Principal Component Analysis (PCA) and the derivation of novel asymptotic theory for Lp …
Unsupervised training dataset curation for deep-neural-net RF signal classification
We consider the problem of unsupervised (blind) evaluation and assessment of the quality
of data used for deep neural network (DNN) RF signal classification. When neural networks …
of data used for deep neural network (DNN) RF signal classification. When neural networks …
[BOOK][B] Theory and Algorithms for Reliable Multimodal Data Analysis, Machine Learning, and Signal Processing
DG Chachlakis - 2021 - search.proquest.com
Modern engineering systems collect large volumes of data measurements across diverse
sensing modalities. These measurements can naturally be arranged in higher-order arrays …
sensing modalities. These measurements can naturally be arranged in higher-order arrays …
Connected Multi-Domain Autonomy and Artificial Intelligence: Autonomous Localization, Networking, and Data Conformity Evaluation
K Tountas - 2020 - search.proquest.com
The objective of this dissertation is the development of a solid theoretical and algorithmic
framework for three of the most important aspects of autonomous/artificial-intelligence (AI) …
framework for three of the most important aspects of autonomous/artificial-intelligence (AI) …