Results 111 to 120 of about 1,704,441 (287)

NIPD: A Federated Learning Person Detection Benchmark Based on Real-World Non-IID Data

, 2023
Federated learning (FL), a privacy-preserving distributed machine learning, has been rapidly applied in wireless communication networks. FL enables Internet of Things (IoT) clients to obtain well-trained models while preventing privacy leakage.
Ding, Zhen, Yin, Kangning, Chen, Dongsheng, Yin, Guangqiang, Fu, Jie, Wang, Zhiguo, Dong, Zhihua, Ji, Xinhui   +7 more
core   +1 more source

Stochastic Gradient Descent in High Dimensions for Multi‐Spiked Tensor PCA

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We study the high‐dimensional dynamics of online stochastic gradient descent (SGD) for the multi‐spiked tensor model. This multi‐index model arises from the tensor principal component analysis (PCA) problem with multiple spikes, where the goal is to estimate the unknown signal vectors within the N$N$‐dimensional unit sphere through maximum ...
Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo   +2 more
wiley   +1 more source

Cross-Gradient Aggregation for Decentralized Learning from Non-IID data

, 2021
Decentralized learning enables a group of collaborative agents to learn models using a distributed dataset without the need for a central parameter server.
Esfandiari, Yasaman, Hegde, Chinmay, Tan, Sin Yong, Jiang, Zhanhong, Balu, Aditya, Herron, Ethan, Sarkar, Soumik   +6 more
core   +1 more source

Fintech Policy and the Rise of Green Technological Inventions

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Technological transformation can enhance enterprises' green invention by promoting knowledge spillovers, alleviating financial constraints, and supporting innovative business models. Within this framework, our study investigates the effect of technological infrastructure construction on green technology invention, using the ‘Fintech China ...
Tao Huang, Qurat ul Ain, Tahir Yousaf, Kaiyang Zhong   +3 more
wiley   +1 more source

2D Implementation of Kinetic‐Diffusion Monte Carlo in Eiron

Contributions to Plasma Physics, EarlyView.
ABSTRACT Particle‐based kinetic Monte Carlo simulations of neutral particles are one of the major computational bottlenecks in tokamak scrape‐off layer simulations. This computational cost comes from the need to resolve individual collision events in high‐collisional regimes.
Oskar Lappi, Emil Løvbak, Thijs Steel, Giovanni Samaey   +3 more
wiley   +1 more source

Global Convergence of Continual Learning on Non-IID Data

CoRR
Continual learning, which aims to learn multiple tasks sequentially, has gained extensive attention. However, most existing work focuses on empirical studies, and the theoretical aspect remains under-explored. Recently, a few investigations have considered the theory of continual learning only for linear regressions, establishes the results based on ...
Fei Zhu 0004, Yujing Liu, Wenzhuo Liu, Zhaoxiang Zhang 0001   +3 more
openaire   +2 more sources

Seismic Structural Reliability by Time‐Variant Fragility Functions

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT The seismic vulnerability of aging structures is often represented in the form of fragility curves that vary with time. On one hand, each of these functions is intended to apply if the earthquake hits at the time the fragility refers to. On the other hand, performance‐based earthquake engineering (PBEE) resources to classical probabilistic ...
Iunio Iervolino
wiley   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source

Federated Learning for Breast Cancer Classification: A Comparative Study of Aggregation Methods

Information
Federated Learning (FL) allows healthcare institutions to collaboratively develop machine learning models while safeguarding patient data, making it ideal for privacy-sensitive medical imaging.
Nadjat Saàdia Lachemi, Medjeded Merati, Saïd Mahmoudi   +2 more
doaj   +1 more source

Fairness amidst non‐IID graph data: A literature review

AI Magazine
AbstractThe growing importance of understanding and addressing algorithmic bias in artificial intelligence (AI) has led to a surge in research on AI fairness, which often assumes that the underlying data are independent and identically distributed (IID).
Wenbin Zhang 0002, Jeremy C. Weiss, Shuigeng Zhou, Toby Walsh   +3 more
openaire   +2 more sources