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Hierarchical Bayesian adaptive lasso methods on exponential random graph models
The analysis of network data has become an increasingly prominent and demanding field across multiple research fields including data science, health,...
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Adaptive Methods for Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators
AbstractThis paper is devoted to some adaptive methods for variational inequalities with relatively smooth and relatively strongly monotone...
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Dual channel and multi-scale adaptive morphological methods for infrared small targets
Infrared small target detection is a challenging task. Morphological operators with a single structural element size are easily affected by complex...
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Weather forecasting based on hybrid decomposition methods and adaptive deep learning strategy
Many global climate-affecting factors are combined to influence the weather and the most challenging ones are the wind speed and the air temperature....
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Adaptive discontinuous Galerkin finite element methods for the Allen-Cahn equation on polygonal meshes
In this paper, we develop a polygonal mesh adaptation algorithm for a fully implicit scheme based on discontinuous Galerkin (DG) finite element...
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Novel numerical methods based on graded, adaptive and uniform meshes for a time-fractional advection-diffusion equation subjected to weakly singular solution
This paper presents adaptive, graded and uniform mesh schemes to approximate the solution of a fractional order advection-diffusion model, which...
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An adaptive multi-class imbalanced classification framework based on ensemble methods and deep network
Data imbalance is one of the most difficult problems in machine learning. The improved ensemble learning model is a promising solution to mitigate...
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Effects of adaptive feedback through a digital tool – a mixed-methods study on the course of self-regulated learning
Lifelong learning is emerging as a key priority for promoting equity and sustainability in societies. Self-regulated learning (SRL) is a fundamental...
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Adaptive Localized Reduced Basis Methods for Large Scale PDE-Constrained Optimization
In this contribution, we introduce and numerically evaluate a certified and adaptive localized reduced basis method as a local model in a...
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Blind adaptive identification and equalization using bias-compensated NLMS methods
In this paper, two new blind adaptive identification and equalization algorithms based on second-order statistics are proposed. We consider a...
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A robust optimization method for label noisy datasets based on adaptive threshold: Adaptive-k
The use of all samples in the optimization process does not produce robust results in datasets with label noise. Because the gradients calculated...
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Clustering Methods for Adaptive e-Commerce User Interfaces
Typical online shops have one interface provided to all users, regardless of their use of the shop. Meanwhile, user behavior varies and therefore...
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Rigorous engineering of collective adaptive systems – 2nd special section
An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive...
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Triple methods-based empirical assessment of the effectiveness of adaptive cyber defenses in the cloud
The flexible and cost-effective service provided by cloud computing has led to the development of a vast array of applications in smart cities....
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An optimal adaptive reweighted sampling-based adaptive block compressed sensing for underwater image compression
The use of Block Compressed Sensing (BCS) as an alternative to conventional Compressed Sensing (CS) in image sampling and acquisition has gained...
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Adaptive Strategies Metric Suite
Self-Adaptive Systems (SAS) are able to cope with the changes occurring dynamically in their execution environment in an autonomous and automated...
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Adaptive Instructional Systems 5th International Conference, AIS 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings
This book constitutes the refereed proceedings of the 5th International Conference, AIS 2023, held as part of the 25th International Conference, HCI...
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Visual-based vehicle detection with adaptive oversampling
In this study, the class imbalance issue in vehicle detection was addressed. Specifically, certain classes such as Tow Truck were found to have...
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MDAA: multi-scale and dual-adaptive attention network for breast cancer classification
Attention mechanism is crucial in the auxiliary diagnosis of breast cancer. However, methods relying on a single attention mechanism may not always...
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Image adaptive sampling using reinforcement learning
Adaptive sampling and mesh representation of images play an important role in image compression and vectorization. In this paper, a multi-points...
