3D ROC Histogram: A New ROC Analysis Tool Incorporating Information on Instances
IEEE Access, 2019 While Receiver Operator Characteristic (ROC) curves have been a standard tool in the design and evaluation of binary classification problems, they have sometimes been blamed for ignoring some vital information in the evaluation process, such as predicted
Rui Guo, Xuanjing Shen, Xiaoli Zhang
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On the capacity of channels with block memory [PDF]
, 1988 The capacity of channels with block memory is investigated. It is shown that, when the problem is modeled as a game-theoretic problem, the optimum coding and noise distributions when block memory is permitted are independent from symbol to symbol within ...
McEliece, Robert J., Stark, Wayne E.
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Overhead Analysis and Evaluation of Approaches to Host-Based Bot Detection
International Journal of Distributed Sensor Networks, 2015 Host-based bot detection approaches discover malicious bot processes by signature comparison or behavior analysis. Existing approaches have low performance which has become a bottleneck blocking its wider deployment.
Yuede Ji, Qiang Li, Yukun He, Dong Guo
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A Novel Multi-Thread Parallel Constraint Propagation Scheme
IEEE Access, 2019 Constraint Programming (CP) is an efficient technique for solving combinatorial (optimization) problems. In modern constraint solver, a CP Model is defined over reversible variables that take values in domains and propagators which filter the domains of ...
Zhe Li +4 more
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An Efficient v-Minimum Absolute Deviation Distribution Regression Machine
IEEE Access, 2020 Support Vector Regression (SVR) and its variants are widely used regression algorithms, and they have demonstrated high generalization ability. This research proposes a new SVR-based regressor: v-minimum absolute deviation distribution regression (v-MADR)
Yan Wang +6 more
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DenSec: Secreted Protein Prediction in Cerebrospinal Fluid Based on DenseNet and Transformer
Mathematics, 2022 Cerebrospinal fluid (CSF) exists in the surrounding spaces of mammalian central nervous systems (CNS); therefore, there are numerous potential protein biomarkers associated with CNS disease in CSF.
Lan Huang +4 more
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A multi-task positive-unlabeled learning framework to predict secreted proteins in human body fluids
Complex & Intelligent Systems, 2023 Body fluid biomarkers are very important, because they can be detected in a non-invasive or minimally invasive way. The discovery of secreted proteins in human body fluids is an essential step toward proteomic biomarker identification for human diseases.
Kai He, Yan Wang, Xuping Xie, Dan Shao
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Semiclassical approximation and noncommutative geometry [PDF]
, 2011 We consider the long time semiclassical evolution for the linear Schr\"odinger equation. We show that, in the case of chaotic underlying classical dynamics and for times up to $\hbar^{-2+\epsilon},\ \epsilon>0$, the symbol of a propagated observable by ...
Paul, Thierry
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CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins
BMC Bioinformatics, 2020 Background Compared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection.
Wei Du +5 more
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Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification
Molecules, 2023 Cerebrospinal fluid (CSF) proteins are very important because they can serve as biomarkers for central nervous system diseases. Although many CSF proteins have been identified with wet experiments, the identification of CSF proteins is still a challenge.
Kai He, Yan Wang, Xuping Xie, Dan Shao
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