Results 71 to 80 of about 44,296 (265)
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
Semi-supervised Classification Based Mixed Sampling for Imbalanced Data
Open Physics, 2019 In practical application, there are a large amount of imbalanced data containing only a small number of labeled data. In order to improve the classification performance of this kind of problem, this paper proposes a semi-supervised learning algorithm ...
Zhao Jianhua, Liu Ning
doaj +1 more source
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Graph regularized low-rank representation for semi-supervised learning
Journal of Algorithms & Computational Technology, 2021 Low-rank representation (LRR) has attracted wide attention of researchers in recent years due to its excellent performance in the exploration of high-dimensional subspace structures.
Cong-Zhe You +3 more
doaj +1 more source
Semi-supervised Learning for WLAN Positioning [PDF]
, 2011 Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a "radio map" is constructed by modeling how the signal strength measurements vary according to the location. However, collecting a sufficient amount of location-tagged training data is a rather tedious and time consuming task, especially in indoor ...
Teemu Pulkkinen +2 more
openaire +1 more source
A discriminative model for semi-supervised learning [PDF]
Journal of the ACM, 2010 Supervised learning—that is, learning from labeled examples—is an area of Machine Learning that has reached substantial maturity. It has generated general-purpose and practically successful algorithms and the foundations are quite well understood and captured by theoretical frameworks such as the PAC-learning model and the Statistical ...
Maria-Florina Balcan, Avrim Blum
openaire +1 more source
Advanced Functional Materials, EarlyView.Sea cucumber mutable collagenous tissue (MCT) is a remarkable collagen‐based material which can rapidly undergo large changes in stiffness through transiently bound effector proteins. Here, we investigate the hierarchical structure and mechanical response of MCT from Cucumaria frondosa across length scales with a wide range of methods, also exploring ...
Nathalie R. H. Singh +7 more
wiley +1 more source
Semi-HFL: semi-supervised federated learning for heterogeneous devices
Complex & Intelligent Systems, 2022 In the vanilla federated learning (FL) framework, the central server distributes a globally unified model to each client and uses labeled samples for training.
Zhengyi Zhong +5 more
doaj +1 more source
Semi-Supervised Learning with Heterophily
CoRR, 2014 We derive a family of linear inference algorithms that generalize existing graph-based label propagation algorithms by allowing them to propagate generalized assumptions about "attraction" or "compatibility" between classes of neighboring nodes (in particular those that involve heterophily between nodes where "opposites attract").
openaire +2 more sources
Semi-Supervised Learning on Riemannian Manifolds [PDF]
Machine Learning, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mikhail Belkin, Partha Niyogi
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