The DeepFilterNet (DFN) architecture was recently proposed as a deep learning model suited for hearing aid devices. Despite its competitive performance on numerous benchmarks, it still follows a ‘one-size-fits-all’ ...
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Text-based password authentication remains essential for identity verification on internet platforms and blockchain systems. However, as computational power advances, security threats to user passwords have intensifie...
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Inferring sky surface brightness distributions from noisy interferometric data in a principled statistical framework has been a key challenge in radio astronomy. In this work, we introduce Imaging for Radio Interferom...
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Counterfactual inference aims to estimate the counterfactual outcome at the individual level given knowledge of an observed treatment and the factual outcome, with broad applications in fields such as epidemiology, ec...
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作者:
Zhang, LeiNing, HaoranTang, JiaxinChen, ZhenxiangZhong, YapingHan, YahongTianjin University
College of Intelligence and Computing the Tianjin Key Laboratory of Advanced Network Technology and Application Tianjin300050 China
Key Laboratory of Computing Power Network and Information Security Ministry of Education China University of Jinan
Shandong Provincial Key Laboratory of Ubiquitous Intelligent Computing the School of Information Science and Engineering Jinan250022 China Wuhan Sports University
Sports Big-data Research Center Wuhan430079 China Tianjin University
College of Intelligence and Computing the Tianjin Key Laboratory of Machine Learning Tianjin300350 China
The inherent complexity of Wi-Fi signals makes video-aided Wi-Fi 3D pose estimation difficult. The challenges include the limited generalizability of the task across diverse environments, its significant signal hetero...
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Uncertainty quantification has received increasing attention in machinelearning in the recent past. In particular, a distinction between aleatoric and epistemic uncertainty has been found useful in this regard. The l...
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An optimality principle is proposed for making investment decisions based on efficiency and risk assessments with a sparse covariance matrix. The method is implemented as a program with a graphical interface and demon...
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An assessment of the investor's risk profile is proposed as a risk coefficient in a model with a linear convolution of expected return and variance. The value of the risk coefficient is found from solving the opti...
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In this paper, a family of support vector novelty detection (or SVND) in hidden space is presented. Firstly a hidden-space SVND (or HSVND) algorithm is proposed. The data in an input space is mapped into a hidden spac...
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