Results 141 to 150 of about 20,082 (264)
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI 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
CAAI 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
Positive solutions for singular nonlinear beam equation
Electronic Journal of Differential Equations, 2007 In this paper, we study the existence of solutions for the singular p-Laplacian equation $$displaylines{ ig(|u''|^{p-2}u''ig)''-f(t,u)=0,quad tin (0,1) cr u(0)=u(1)=0, cr u''(0)=u''(1)=0, }$$ where $f(t,u)$ is singular at $t=0,1$ and at $u=0$.
Ruhao Song, Haishen Lu
doaj
Infinitely many weak solutions of the p-Laplacian equation with nonlinear boundary conditions. [PDF]
ScientificWorldJournal, 2014 Lu FY, Deng GQ.
europepmc +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu +4 more
wiley +1 more source
ANPGT: Towards Adaptive Node Property Extraction and Integration
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Graph transformers (GTs) with elaborate positional/structural encodings (PEs/SEs) have excelled in graph representation learning, especially in graph‐level tasks. However, their potential in large‐scale node classification remains untapped for several reasons: (i) Current PEs/SEs are insufficient in modelling large‐scale real‐world graphs ...
Qin Chen +4 more
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose fusion isomerism learning (FusionIL), a secure and domain‐agnostic framework that ...
Zhihao Hao +5 more
wiley +1 more source
Hölder regularity for parabolic fractional p-Laplacian. [PDF]
Calc Var Partial Differ EquLiao N.
europepmc +1 more source
Feedback‐Driven Medical Image Segmentation: Modelling on Boundary‐Sensitive Feature Preservation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Accurate segmentation of medical images, particularly along ambiguous lesion boundaries, plays a vital role in clinical diagnosis and treatment planning. Conventional segmentation approaches often struggle to recover fine‐grained contours due to spatial detail loss caused by convolutional downsampling and the inherent sparsity of edge features,
Jikai Yang +3 more
wiley +1 more source
Infinitely many homoclinic solutions for second order nonlinear difference equations with p-Laplacian. [PDF]
ScientificWorldJournal, 2014 Sun G, Mai A.
europepmc +1 more source