Results 241 to 250 of about 429,197 (329)

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang   +5 more
wiley   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi   +5 more
wiley   +1 more source

Peritoneal mesothelioma and asbestos exposure: a population-based case-control study in Italy, 2000-2021. [PDF]

open access: yesOccup Environ Med
Consonni D   +33 more
europepmc   +1 more source

Distributed Formation Control for Heterogeneous Robot Systems Based on Competitive Mechanism

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents an adaptive formation control method for a heterogeneous robot swarm, utilising a multilevel formation task tree to model various types of formation tasks and a single‐state distributed k‐winner‐take‐all (S‐DKWTA) algorithm to address the MRTA problem.
Zhenghui Cui, Xiaoyi Gu, Ning Tan
wiley   +1 more source

Design and Validation of Zeroing Neural Network With Active Noise Rejection Capability for Time‐Varying Problems Solving

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Recently, the zeroing neural network (ZNN) has demonstrated remarkable effectiveness in tackling time‐varying problems, delivering robust performance across both noise‐free and noisy environments. However, existing ZNN models are limited in their ability to actively suppress noise, which constrains their robustness and precision in solving ...
Yilin Shang   +3 more
wiley   +1 more source

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