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Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification [article]

Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zheng-Jun Zha
<span title="2020-12-17">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This would mislead the feature representation learning and deteriorate the performance.  ...  Many unsupervised domain adaptive (UDA) person re-identification (ReID) approaches combine clustering-based pseudo-label prediction with feature fine-tuning.  ...  Figure 2 : Overview of the proposed Uncertainty-guided Noise Resilient Network (UNRN) for UDA person ReID.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.08733v2">arXiv:2012.08733v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2xrbeibijfgfhkx7r6sf5wwqw4">fatcat:2xrbeibijfgfhkx7r6sf5wwqw4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201221010432/https://arxiv.org/pdf/2012.08733v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d4/77/d477e72f93d8b895fd0ccc38f2a1cc04bf96e3f1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.08733v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Tri-Structured-Sparsity Induced Joint Feature Selection and Classification for Hybrid Noise Resilient Multilabel Learning

Lei Xu, Chuancheng Song, Lei Chen
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
The first three items are utilized for feature-noise-robust feature selection which can simultaneously tolerate sample-specific feature noise and select label-specific and label-shared features.  ...  Given this consideration, some methods are proposed to select label-specific features, such as LIFT [17] , learning label-specific features for multilabel classification (LLSF) [21] and joint feature  ...  To show our robustness for different types of noise, we also compare our method with HNOML [14] , which is designed to handle hybrid noise.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3001274">doi:10.1109/access.2020.3001274</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q2iclhoprnelnpl3tmnn6222h4">fatcat:q2iclhoprnelnpl3tmnn6222h4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201108172214/https://ieeexplore.ieee.org/ielx7/6287639/6514899/09113479.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b8/6e/b86eb89a185eb4126fd95a8ba03f5f498dddcdf7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3001274"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Progressive Kernel Extreme Learning Machine for Food Image Analysis via Optimal Features from Quality Resilient CNN

Ghalib Ahmed Tahir, Chu Kiong Loo
<span title="2021-10-14">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
Our feature selection strategy uses the Shapley additive explanation (SHAP) values from the gradient explainer to select the best features.  ...  PKELM extension for multilabel classification detects ingredients by employing a bipolar step function to process test output and then selecting the column labels of the resulting matrix with a value of  ...  Informed Consent Statement: Not applicable. Conflicts of Interest: The authors declare there is no conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app11209562">doi:10.3390/app11209562</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qcjlaot7xjgariwmxrrs2uyd3u">fatcat:qcjlaot7xjgariwmxrrs2uyd3u</a> </span>
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Evaluating Resilience of Encrypted Traffic Classification Against Adversarial Evasion Attacks [article]

Ramy Maarouf, Danish Sattar, Ashraf Matrawy
<span title="2021-05-30">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In most of our experimental results, deep learning shows better resilience against the adversarial samples in comparison to machine learning.  ...  In this paper, we focus on investigating the effectiveness of different evasion attacks and see how resilient machine and deep learning algorithms are.  ...  Feature Selection Feature selection is a crucial part of machine learning to reduce data dimensionality, and extensive research was carried out for a reliable feature selection method [36] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.14564v1">arXiv:2105.14564v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w5rak5pa7neypfgtox5lzpqcai">fatcat:w5rak5pa7neypfgtox5lzpqcai</a> </span>
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Love Thy Neighbors: Image Annotation by Exploiting Image Metadata [article]

Justin Johnson and Lamberto Ballan and Fei-Fei Li
<span title="2015-09-22">2015</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We perform comprehensive experiments on the NUS-WIDE dataset, where we show that our model outperforms state-of-the-art methods for multilabel image annotation even when our model is forced to generalize  ...  We build on this intuition to improve multilabel image annotation.  ...  Russakovsky for helpful comments and discussions. J. Johnson is supported by a Magic Grant from The Brown Institute for Media Innovation and L.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1508.07647v2">arXiv:1508.07647v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pl5igmjsnfbndp5s2cvt5zrd2a">fatcat:pl5igmjsnfbndp5s2cvt5zrd2a</a> </span>
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Love Thy Neighbors: Image Annotation by Exploiting Image Metadata

Justin Johnson, Lamberto Ballan, Li Fei-Fei
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2015 IEEE International Conference on Computer Vision (ICCV)</a> </i> &nbsp;
We perform comprehensive experiments on the NUS-WIDE dataset, where we show that our model outperforms state-of-the-art methods for multilabel image annotation even when our model is forced to generalize  ...  We build on this intuition to improve multilabel image annotation.  ...  Russakovsky for helpful comments and discussions. J. Johnson is supported by a Magic Grant from The Brown Institute for Media Innovation and L.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.525">doi:10.1109/iccv.2015.525</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/JohnsonBL15.html">dblp:conf/iccv/JohnsonBL15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/taklelmptnewhdf5qetpbmiuxu">fatcat:taklelmptnewhdf5qetpbmiuxu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160717215055/http://www-cs-faculty.stanford.edu:80/people/jcjohns/papers/iccv15/JohnsonICCV2015.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/34/12/341226740aba808bf70b0fb9795e738afcec7aa0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2015.525"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Attack Detection and Localization in Smart Grid with Image-based Deep Learning [article]

Mostafa Mohammadpourfard, Istemihan Genc, Subhash Lakshminarayana, Charalambos Konstantinou
<span title="2021-10-21">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Smart grid's objective is to enable electricity and information to flow two-way while providing effective, robust, computerized, and decentralized energy delivery.  ...  These images are then utilized to build a highly reliable and resilient deep Convolutional Neural Network (CNN)-based multi-label classifier capable of learning both low and high level characteristics  ...  In the second step, we meticulously build a reliable and resilient multilabel CNN-based classifier to accurately capture spatial and temporal correlations and create an end-to-end mapping connection between  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.11007v1">arXiv:2110.11007v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/voku4jd2jnckhi5mznp4yolily">fatcat:voku4jd2jnckhi5mznp4yolily</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211026221137/https://arxiv.org/pdf/2110.11007v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fc/ae/fcae95254425e2a1a10c8d37b9da99eab261b759.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.11007v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Synthetic Oversampling of Multi-Label Data based on Local Label Distribution [article]

Bin Liu, Grigorios Tsoumakas
<span title="2019-06-20">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Existing multilabel sampling methods alleviate the (global) imbalance of multi-label datasets.  ...  We propose a new method for synthetic oversampling of multi-label data that focuses on local label distribution to generate more diverse and better labeled instances.  ...  ECCRU3 extends the ECC resilient to class imbalance by coupling undersampling and improving of the exploitation of majority examples [18] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.00609v2">arXiv:1905.00609v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3nbcxqipjbe4vcyxfkxh55eywy">fatcat:3nbcxqipjbe4vcyxfkxh55eywy</a> </span>
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Multi-Label Sampling based on Local Label Imbalance [article]

Bin Liu, Konstantinos Blekas, Grigorios Tsoumakas
<span title="2020-05-19">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
By considering all informative labels, MLSOL creates more diverse and better labeled synthetic instances for difficult examples, while MLUL eliminates instances that are harmful to their local region.  ...  Experimental results on 13 multi-label datasets demonstrate the effectiveness of the proposed measure and sampling approaches for a variety of evaluation metrics, particularly in the case of an ensemble  ...  This scheme is able to create informative instances for locally imbalanced labels without bringing in noises for the rest of the labels.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.03240v2">arXiv:2005.03240v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/52r3ppre2zh6jlypss6pb74ezq">fatcat:52r3ppre2zh6jlypss6pb74ezq</a> </span>
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BigDataGrapes D4.3 - Models and Tools for Predictive Analytics over Extremely Large Datasets

Nicola Tonellotto, Vinicius Monteiro de Lira, Franco Maria Nardini, Raffaele Perego, Cristina Muntean, Ida Mele, Salvatore Trani, Matteo Ceneta
<span title="2019-04-15">2019</span> <i title="Zenodo"> Zenodo </i> &nbsp;
The BDG software stack employs efficient and fault-tolerant tools for distributed processing, aimed at providing scalability and reliability for the target applications.  ...  This accompanying document for deliverable D4.3 (Models and Tools for Predictive Analytics over Extremely Large Datasets) describes the first version of the mechanisms and tools supporting efficient and  ...  Figure 10 : 10 Feature importance for the first feature set. Figure 11 : 11 feature importance for the second feature set.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.2641952">doi:10.5281/zenodo.2641952</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n6ag6qt4gzg6tmnytqs2f7op4u">fatcat:n6ag6qt4gzg6tmnytqs2f7op4u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201228232140/https://zenodo.org/record/2641952/files/D4.3_v2.0%20%28Submitted%20to%20EC%29.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/83/84/8384487cf6d2fb70a707e3b9ff68a5f8d9feab65.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.2641952"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

A Natural Language-Inspired Multi-label Video Streaming Traffic Classification Method Based on Deep Neural Networks [article]

Yan Shi, Dezhi Feng, Subir Biswas
<span title="2019-06-04">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper presents a deep-learning based traffic classification method for identifying multiple streaming video sources at the same time within an encrypted tunnel.  ...  Results are obtained by applying several NLP methods to show that the proposed method performs well on both binary and multilabel traffic classification problems.  ...  We then develop a deep-learning based classifier that exploits the temporal patterns in this feature.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1906.02679v1">arXiv:1906.02679v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bdcwhhimpzajjjp4jjh3mnm5ka">fatcat:bdcwhhimpzajjjp4jjh3mnm5ka</a> </span>
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Deep Networks for Direction-of-Arrival Estimation in Low SNR

Georgios Konstantinos Papageorgiou, Mathini Sellathurai, Yonina C. Eldar
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gkn2pu46ozb4tmkxczacnmtvkq" style="color: black;">IEEE Transactions on Signal Processing</a> </i> &nbsp;
The proposed architecture demonstrates enhanced robustness in the presence of noise, and resilience to a relatively small number of snapshots.  ...  In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL).  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their insightful comments and suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.2021.3089927">doi:10.1109/tsp.2021.3089927</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bckfboewgvhd5glrvq2qvmsjuq">fatcat:bckfboewgvhd5glrvq2qvmsjuq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210718011348/https://ieeexplore.ieee.org/ielx7/78/4359509/09457195.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2e/66/2e66d15c156ce153697940dbce78c67a9fb1ece3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tsp.2021.3089927"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Less Is More: A Comprehensive Framework for the Number of Components of Ensemble Classifiers

Hamed Bonab, Fazli Can
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/j6amxna35bbs5p42wy5crllu2i" style="color: black;">IEEE Transactions on Neural Networks and Learning Systems</a> </i> &nbsp;
Almost all of them are designed for batch-mode, hardly addressing online environments.  ...  The number of component classifiers chosen for an ensemble greatly impacts the prediction ability.  ...  Büyükçakır for their valuable comments. Any opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily reflect those of the sponsors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnnls.2018.2886341">doi:10.1109/tnnls.2018.2886341</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/udli25uwdrdd5c24tddxzeddd4">fatcat:udli25uwdrdd5c24tddxzeddd4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716211042/http://repository.bilkent.edu.tr/bitstream/handle/11693/75936/Less_Is_More_A_Comprehensive_Framework_for_the_Number_of_Components_of_Ensemble_Classifiers.pdf;jsessionid=0F2E2D1BB462F8FDDD3626BC32351BF6?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/46/cb/46cbe096cccb7e236f2313b0089a7f170e7a1c16.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tnnls.2018.2886341"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Semantic Image Segmentation and Object Labeling

Thanos Athanasiadis, Phivos Mylonas, Yannis Avrithis, Stefanos Kollias
<span title="">2007</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jqw2pm7kwvhchpdxpcm5ryoic4" style="color: black;">IEEE transactions on circuits and systems for video technology (Print)</a> </i> &nbsp;
In this paper, we present a framework for simultaneous image segmentation and object labeling leading to automatic image annotation.  ...  Contextual information is based on a novel semantic processing methodology, employing fuzzy algebra and ontological taxonomic knowledge representation.  ...  Concepts sky and sea prove to have great resilience to noise, since we observe nearly stable and close to noise-free series of values even for great variance of Gaussian noise.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2007.890636">doi:10.1109/tcsvt.2007.890636</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zfg3pka255bk5aqwxlkhuwauma">fatcat:zfg3pka255bk5aqwxlkhuwauma</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808185121/http://image.ece.ntua.gr/papers/462.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/00/f7/00f78fcfa652c94ff5883fd17c5b81846a863018.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2007.890636"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Machine Learning for Detecting Data Exfiltration: A Review [article]

Bushra Sabir, Faheem Ullah, M. Ali Babar, Raj Gaire
<span title="2021-03-21">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Method: We used a Systematic Literature Review (SLR) method to select and review 92 papers.  ...  to adversarial learning should be considered and explored during the development of countermeasures to avoid poisoning attacks; and (v) the use of automated feature engineering should be encouraged for  ...  In Feature selection, various techniques (e.g., information gain, Chisquare test [28] ) are applied to choose the best discriminant features from an initial set of features.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.09344v2">arXiv:2012.09344v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zpsptvpqaba5zhtzqxtv5tdqra">fatcat:zpsptvpqaba5zhtzqxtv5tdqra</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210324235611/https://arxiv.org/pdf/2012.09344v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/53/cd/53cd937faa2bf09d3d7388d31a02bc5ccd211406.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.09344v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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