Results 51 to 60 of about 1,666 (170)

Robust Partial Multi‐Label Learning Under Dual Noise via Joint Subspace Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Partial Multi‐label Learning (PML) deals with the ambiguity where each instance is annotated with a set of candidate labels, and only a subset of which is valid. While existing PML methods focus primarily on label disambiguation, they often rely on the assumption of a clean feature space.
Yuanjian Zhang, Zhanbo Fang, Tianna Zhao, Duoqian Miao, Witold Pedrycz   +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, Yuanyi Ren, Guojie Song, Liang Wang, Bo Zheng   +4 more
wiley   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Signal Extraction and Clustering of Partial Discharge in Motor Insulation Using Temporal Correlation‐Based Clustering

High Voltage, EarlyView.
ABSTRACT As one of the important links in energy transition and global energy interconnection, electric vehicles (EVs) are becoming increasingly major research topics in the field of energy. Partial discharge (PD) identification under repetitive impulsive voltages plays a pivotal role in evaluating the health of electric vehicle (EV) motor insulation ...
Li Wang, Jia‐Wei Zhang, Haikun Shang, Yu Zhao, Yufei Wang, Chen Song, Jianwei Zhang, Fouad Belhora   +7 more
wiley   +1 more source

The difference matrices of the classes of a Sharma-Kaushik partition [PDF]

, 2004
summary:Sharma-Kaushik partitions have been used to define distances between vectors with $n$-coordinates. In this paper, “difference matrices” for the partitioning classes have been introduced and investigated.
Sookoo, Norris, Sharma, Bhu Dev
core  

Determinants and the volumes of parallelotopes and zonotopes

, 2010
The Minkowski sum of edges corresponding to the column vectors of a matrix A with real entries is the same as the image of a unit cube under the linear transformation defined by A with respect to the standard bases.
Gover, Eugene, Krikorian, Nishan
core   +1 more source

AlignPCA‐2D: PCA‐reduced Euclidean vector alignment for 2D classification in cryo‐EM

Acta Crystallographica Section D, EarlyView.
We introduce AlignPCA‐2D, a PCA‐space Euclidean alignment method for rapid and interpretable 2D classification of cryo‐EM particle images. The approach preserves essential structural variability while greatly reducing computational cost, offering a lightweight alternative to existing large‐scale cryo‐EM classification pipelines.Cryogenic electron ...
E. Ramírez-Aportela, O. L. Zarrabeitia, Y. C. Fonseca, T. Ceska, S. Subramaniam, J. M. Carazo, C. O. S. Sorzano   +6 more
wiley   +1 more source

Cyclotomy, Hadamard arrays and supplementary difference sets

, 1972
A 4n x 4n Hadamard array, H, is a square matrix of order 4n with elements ± A, ± B, ± C, ± D each repeated n times in each row and column. Assuming the indeterminates A, B, C, D commute, the row vectors of H must be orthogonal.
Jennifer Seberry (19583125), David C Hunt (20284437)   +1 more
core  

V1-inspired features induce a weighted margin in SVMs

, 2012
Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad visual classification tasks. A central question in the vision, learning and neuroscience communities regards
Lucey, Simon, Bristow, Hilton, Hilton Bristow, Simon Lucey   +3 more
core   +1 more source

Bayesian inference for dynamic Q matrices and attribute trajectories in hidden Markov diagnostic classification models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley   +1 more source