Results 101 to 110 of about 238,312 (311)
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
Advanced Materials Technologies, EarlyView.Hierarchical multi‐material TPMS lattices are engineered as flexible tactile sensors by combining soft and stiff elastomeric layers with a conformal conductive coating. The bilayer architecture delivers sensitivity at low pressures while maintaining a broad detectable range under large loads, enabling reliable pressure and vibration monitoring for ...
Reza Noroozi +3 more
wiley +1 more source
A Local-to-Global Metric Learning Framework From the Geometric Insight
IEEE Access, 2020 Metric plays a key role in the description of similarity between samples. An appropriate metric for data can well represent their distribution and further promote the performance of learning tasks.
Yaxin Peng +3 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
At Home Detection of Ovarian Health Biomarker in Menstruation Blood
Advanced Materials Technologies, EarlyView.A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon +3 more
wiley +1 more source
Active semi-supervised learning for biological data classification.
PLoS ONE, 2020 Due to datasets have continuously grown, efforts have been performed in the attempt to solve the problem related to the large amount of unlabeled data in disproportion to the scarcity of labeled data.
Guilherme Camargo +2 more
doaj +1 more source
, 2021 Learning based credit prediction has attracted great interest from academia and industry. Different institutions hold a certain amount of credit data with limited users to build model.
Li, Lin +5 more
core +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
Advanced Robotics Research, EarlyView.This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
Soft Sensing of Silicon Content via Bagging Local Semi-Supervised Models
Sensors, 2019 The silicon content in industrial blast furnaces is difficult to measure directly online. Traditional soft sensors do not efficiently utilize useful information hidden in process variables.
Xing He +4 more
doaj +1 more source
A semi-supervised spam mail detector
, 2006 This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge.
Pfahringer, Bernhard
core