Results 51 to 60 of about 1,704,441 (287)

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

The KIF6‐RBP Complex Orchestrates mRNA Transport Required for Sperm Flagellar Assembly

Advanced Science, EarlyView.
Two homozygous deleterious KIF6 variants are identified in unrelated men with impaired sperm motility. Mouse models and multi‐omics analyses reveal that KIF6 cooperates with the RNA‐binding proteins FMRP and FXR1 to deliver mRNAs essential for sperm flagellar assembly, linking disrupted mRNA transport to reduced abundance of key structural and ...
Chunbo Xie, Sibing Yi, Xinle Lin, Shen Zhang, Weili Wang, Shimin Yuan, Lanlan Meng, Yong Li, Chen Tan, Chunjia Wei, Yanyan Yu, Yaoqiong Liang, Huan Zhang, Liang Hu, Guangxiu Lu, Wenbin He, Qianjun Zhang, Juan Du, Ge Lin, Chaofeng Tu, Yue‐Qiu Tan   +20 more
wiley   +1 more source

RRAM Variability Harvesting for CIM‐Integrated TRNG

Advanced Electronic Materials, EarlyView.
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende, Gokulnath Rajendran, Regina Dittmann, Anupam Chattopadhyay, Vikas Rana   +4 more
wiley   +1 more source

Handling Non-IID Data in Federated Learning : An Experimental Evaluation Towards Unified Metrics

, 2023
Recent research has demonstrated that Non-Identically Distributed (Non-IID) data can negatively impact the performance of global models constructed in federated learning. To address this concern, multiple approaches have been developed.
Haller, Marc,, Lenz, Christian, Lenz, Christian,, Nachtigall, Robin,, Awayshehl, Feras M.,, Awayshehl, Feras M., Alawadi, Sadi,, Haller, Marc, Alawadi, Sadi, Nachtigall, Robin   +9 more
core   +1 more source

Disorder‐Driven Ionic Mobility Edge and Localization‐Driven Dendrite Formation in Solid Electrolytes

Advanced Energy Materials, EarlyView.
Migration‐barrier disorder localizes ionic transport into a sparse percolation backbone. Current and electric‐field focusing at filament tips promote fractal dendrite growth and suppress the critical current density according to jcrit = j0 exp(−σEeff/kBT).
Dongwook Lee, Jiwon Seo
wiley   +1 more source

Privacy Protection in Prosumer Energy Management Based on Federated Learning

IEEE Access, 2021
With the booming development of prosumers, there is an urgent need for a prosumer energy management system to take full advantage of the flexibility of prosumers and take into account the interests of other parties.
Yunfeng Li, Xiaoling Li, Gangqiang Li, Zhitao Li   +3 more
doaj   +1 more source

Volatility analysis and forecasting of vegetable prices using an ARMA‐GARCH model: An application of the CF filter and seasonal adjustment method to Korean green onions

Agribusiness, EarlyView.
Abstract The vegetable market experiences significant price fluctuations due to the complex interplay of trend, cyclical, seasonal, and irregular factors. This study takes Korean green onions as an example and employs the Christiano–Fitzgerald filter and the CensusX‐13 seasonal adjustment methods to decompose its price into four components: trend ...
Yiyang Qiao, Byeong‐il Ahn
wiley   +1 more source

Aggregation Methods Based on Quality Model Assessment for Federated Learning Applications: Overview and Comparative Analysis

Mathematics, 2023
Federated learning (FL) offers the possibility of collaboration between multiple devices while maintaining data confidentiality, as required by the General Data Protection Regulation (GDPR).
Iuliana Bejenar, Lavinia Ferariu, Carlos Pascal, Constantin-Florin Caruntu   +3 more
doaj   +1 more source

Federated learning with hierarchical clustering of local updates to improve training on non-IID data [PDF]

, 2020
Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion -- as is typical ...
Fan
core   +1 more source

Fed-TDA: Federated Tabular Data Augmentation on Non-IID Data

CoRR, 2022
Non-independent and identically distributed (non-IID) data is a key challenge in federated learning (FL), which usually hampers the optimization convergence and the performance of FL. Existing data augmentation methods based on federated generative models or raw data sharing strategies for solving the non-IID problem still suffer from low performance ...
Shaoming Duan, Chuanyi Liu, Peiyi Han, Tianyu He, Yifeng Xu, Qiyuan Deng   +5 more
openaire   +2 more sources