Results 81 to 90 of about 14,462,668 (184)

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

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, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +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, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

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, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source

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

The effect of nearby listings on house sale prices in Sydney: A spatio‐temporal regularization approach

Real Estate Economics, EarlyView.
Abstract We estimate the price impact of very nearby concurrently listed properties in the Sydney housing market and assess their competition effects. We apply a hedonic model with spatiotemporal effects regularized via a graph Laplacian prior at the month‐by‐SA2 regional level to seven SA4 subregions of metropolitan Sydney. The model structure enables
Willem P. Sijp, Mengheng Li
wiley   +1 more source

Complementarity in alliances: How strategic compatibility and hierarchy promote efficient cooperation in international security

American Journal of Political Science, EarlyView.
Abstract How can defense alliances reap the efficiency gains of working together when coordination and opportunism costs are high? Although specializing as part of a collective comes with economic and functional benefits, states must bargain over the distribution of those gains and ensure the costs of collective action are minimized.
J. Andrés Gannon
wiley   +1 more source

Computing Skinning Weights via Convex Duality

Computer Graphics Forum, EarlyView.
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley   +1 more source

Democratising Multi‐Projector Displays

Computer Graphics Forum, EarlyView.
Spatially augmented reality (SAR) transforms large, surround, collaborative experiences out of VR/AR headsets to the real world by merging content from projectors with the physical environment. This detailed state‐of‐the‐art survey reports on the advancements in multi‐projector aggregation and hardware technologies used to achieve SAR and build ...
Aditi Majumder, Muhammad Twaha Ibrahim
wiley   +1 more source