Results 91 to 100 of about 451,604 (277)
Robust and Adaptive Incremental Learning for Varying Feature Space
IEEE AccessReal-world multiple or streaming tabular datasets, such as electronic health records from various sources and internet-of-things data generated from different devices, typically exhibit varied feature spaces depending on the datasets. Batch-mode learning
Cheol Ho Kim +3 more
doaj +1 more source
Learning Automata Based Incremental Learning Method for Deep Neural Networks
IEEE Access, 2019 Deep learning methods have got fantastic performance on lots of large-scale datasets for machine learning tasks, such as visual recognition and neural language processing. Most of the progress on deep learning in recent years lied on supervised learning,
Haonan Guo +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Bioprosthetic aortic valves have revolutionized the treatment of aortic stenosis, but their durability is limited by structural valve deterioration (SVD). This review focuses on the pericardial tissue at the heart of these valves, examining how its mechanical properties and calcification drive fatigue and failure.
Gabriele Greco +7 more
wiley +1 more source
A Learning Algorithm based on High School Teaching Wisdom [PDF]
, 2010 A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate a student and to give them training on the examples for which they repeatedly fail, until, they can correctly answer all types of
Philip, Ninan Sajeeth
core
Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning
17 pages, 6 figures, 6 tables, ECCV 2024 ...
Min-Yeong Park +2 more
openaire +2 more sources
Incremental ELMVIS for Unsupervised Learning [PDF]
, 2017 An incremental version of the ELMVIS+ method is proposed in this paper. It iteratively selects a few best fitting data samples from a large pool, and adds them to the model. The method keeps high speed of ELMVIS+ while allowing for much larger possible sample pools due to lower memory requirements.
Akusok, Anton +7 more
openaire +2 more sources
Additive Manufacturing of NiTi Shape Memory Alloys for Elastocaloric Applications: A Review
Advanced Functional Materials, EarlyView.Additive manufacturing enables complex NiTi architectures that overcome key limitations in elastocaloric refrigeration, including poor heat transfer and high mechanical work input. This review surveys recent advances in LPBF‐ and DED‐fabricated NiTi shape memory alloys for elastocaloric applications, highlighting process–structure–performance ...
Ignatius Andre Setiawan +7 more
wiley +1 more source
A Practical Incremental Learning Framework For Sparse Entity Extraction [PDF]
, 2018 This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation.
Al-Olimat, Hussein S. +4 more
core +2 more sources
Advanced Functional Materials, EarlyView.We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
Unsupervised Neural Network for the Control of a Mobile Robot [PDF]
, 1993 This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes of robot parameters such as ...
Guadiano, Paolo +2 more
core +1 more source