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Marco Scutari
Bayesian networks (BNs) are a foundational model in machine learning and causal inference. Their graphical structure can handle high-dimensional problems, divide them into a sparse collection of smaller ones, underlies Judea Pearl?s causality, and determ...
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Yi Zhang, Lanxin Qiu, Yangzhou Xu, Xinjia Wang, Shengjie Wang, Agyemang Paul and Zhefu Wu
Software-Defined Networking (SDN) enhances network control but faces Distributed Denial of Service (DDoS) attacks due to centralized control and flow-table constraints in network devices. To overcome this limitation, we introduce a multi-path routing alg...
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Yuefeng Cen, Mingxing Luo, Gang Cen, Cheng Zhao and Zhigang Cheng
It is meaningful to analyze the market correlations for stock selection in the field of financial investment. Since it is difficult for existing deep clustering methods to mine the complex and nonlinear features contained in financial time series, in ord...
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Xing Wu, Yifan Jin, Jianjia Wang, Quan Qian and Yike Guo
Large-scale automatic speech recognition model has achieved impressive performance. However, huge computational resources and massive amount of data are required to train an ASR model. Knowledge distillation is a prevalent model compression method which ...
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Shunlei Li, Muhammad Adeel Azam, Ajay Gunalan and Leonardo S. Mattos
Optical coherence tomography (OCT) is a rapidly evolving imaging technology that combines a broadband and low-coherence light source with interferometry and signal processing to produce high-resolution images of living tissues. However, the speckle noise...
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Peter Bajcsy, Nicholas J. Schaub and Michael Majurski
This paper addresses the problem of designing trojan detectors in neural networks (NNs) using interactive simulations. Trojans in NNs are defined as triggers in inputs that cause misclassification of such inputs into a class (or classes) unintended by th...
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Han Zheng, Zanyang Cui and Xingchen Zhang
Driving modes play vital roles in understanding the stochastic nature of a railway system and can support studies of automatic driving and capacity utilization optimization. Integrated trajectory data containing information such as GPS trajectories and g...
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Jian Zhang, Zhaoguang Hu, Yanan Zheng, Yuhui Zhou and Ziwei Wan
Unlike existing studies focused on the causal relationship between electricity consumption and economic growth at the macro level, this paper uses monthly data from January 2006 to December 2015 and applies the correlation coefficient, as well as Kullbac...
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Akira Yoshida, Yoshiharu Amano, Noboru Murata, Koichi Ito and Takumi Hasizume
When evaluating residential energy systems like co-generation systems, hot water and electricity demand profiles are critical. In this paper, the authors aim to extract basic time-series demand patterns from two kinds of measured demand (electricity and ...
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