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<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/et7hjqz36jfnjaenyti2fjiq6m" style="color: black;">IEEE Transactions on Reliability</a> </i> &nbsp;
Software Testing, Verification, and Quality Assurance Hierarchically Localizing Software Faults Using DNN . . . . . . . . . . . . . . . . . . . . . A. Dutta, R. Manral, P. Mitra, and R.  ...  Illahi 1341 WR-ELM: Weighted Regularization Extreme Learning Machine for Imbalance Learning in Software Fault Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tr.2020.3026765">doi:10.1109/tr.2020.3026765</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m3vjew4erbdixhaya5zrhndwbi">fatcat:m3vjew4erbdixhaya5zrhndwbi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201204145535/https://ieeexplore.ieee.org/ielx7/24/9274445/09274554.pdf?tp=&amp;arnumber=9274554&amp;isnumber=9274445&amp;ref=" 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/e6/a0/e6a03be53780c4b9f12c5112906c8fb5289c6b13.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tr.2020.3026765"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Black-Box Testing of Deep Neural Networks through Test Case Diversity [article]

Zohreh Aghababaeyan, Manel Abdellatif, Lionel Briand, Ramesh S, Mojtaba Bagherzadeh
<span title="2021-12-20">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We then analyse their statistical association with fault detection using two datasets and three DNN models. We further compare diversity with state-of-the-art white-box coverage criteria.  ...  Despite very active research on DNN coverage, several recent studies have questioned the usefulness of such criteria in guiding DNN testing.  ...  We then analyse their associations with fault detection in DNNs using two widely-used datasets and three different DNN models.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.12591v1">arXiv:2112.12591v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oj6oqjoh3jbvfol4amsnlaggyy">fatcat:oj6oqjoh3jbvfol4amsnlaggyy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220104021704/https://arxiv.org/pdf/2112.12591v1.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/ad/c9/adc92b822cf0dda4c6c00cfac7a82f89a4977255.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.12591v1" 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>

2020 Index IEEE Transactions on Reliability Vol. 69

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/et7hjqz36jfnjaenyti2fjiq6m" style="color: black;">IEEE Transactions on Reliability</a> </i> &nbsp;
Umer, Q., +, TR Dec. 2020 1341-1354 Hierarchically Localizing Software Faults Using DNN.  ...  Lv, M., +, TR June 2020 715-724 Fault location Hierarchically Localizing Software Faults Using DNN.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tr.2021.3050424">doi:10.1109/tr.2021.3050424</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fpn4y3gddvfobm3v7c25iogmxi">fatcat:fpn4y3gddvfobm3v7c25iogmxi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210214163133/https://ieeexplore.ieee.org/ielx7/24/9274445/09353051.pdf?tp=&amp;arnumber=9353051&amp;isnumber=9274445&amp;ref=" 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/99/26/9926d434e507df0408aaeb3f2480e1958d00e3db.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tr.2021.3050424"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

DeepMutation: Mutation Testing of Deep Learning Systems [article]

Lei Ma, Fuyuan Zhang, Jiyuan Sun, Minhui Xue, Bo Li, Felix Juefei-Xu, Chao Xie, Li Li, Yang Liu, Jianjun Zhao, Yadong Wang
<span title="2018-08-14">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In traditional software testing, mutation testing is a well-established technique for quality evaluation of test suites, which analyzes to what extent a test suite detects the injected faults.  ...  To do this, by sharing the same spirit of mutation testing in traditional software, we first define a set of source-level mutation operators to inject faults to the source of DL (i.e., training data and  ...  is often written in high-level languages, the DNN itself is represented and stored as a hierarchical data structure (e.g., .h5 format for Keras [9] ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1805.05206v2">arXiv:1805.05206v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mni2zmroenf5bitxu66msjvef4">fatcat:mni2zmroenf5bitxu66msjvef4</a> </span>
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An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software [article]

Rick Salay, Rodrigo Queiroz, Krzysztof Czarnecki
<span title="2017-09-07">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we analyze the impacts that the use of ML as an implementation approach has on ISO 26262 safety lifecycle and ask what could be done to address them.  ...  More powerful ML models (e.g., DNN) are typically trained using local optimization algorithms, and there can be multiple optima.  ...  Therefore, fault tolerance strategies for software must be required.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1709.02435v1">arXiv:1709.02435v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ci747pyhbbb25b6o25rl3v4asi">fatcat:ci747pyhbbb25b6o25rl3v4asi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200902201838/https://arxiv.org/pdf/1709.02435v1.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/cb/86/cb86d55bdf8bc0de1ccb2d0852aa11f17b4d96ab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1709.02435v1" 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>

Data Preprocessing Techniques in Convolutional Neural Network based on Fault Diagnosis towards Rotating Machinery

Shengnan Tang, Shouqi Yuan, Yong Zhu
<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;
However, the unpredictable machinery faults may lead to the severe damage and losses. Hence, it is of great value to explore the precise approaches for fault diagnosis.  ...  With the development of the intelligent fault diagnosis methods based on deep learning, convolutional neural network (CNN) has aroused the attention of researchers in machinery fault diagnosis.  ...  By the use of data augmentation strategy based on Gaussian white noise via MatLab software, a typical CNN was employed to classify simulated ovalization fault data of journal bearings [68] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3012182">doi:10.1109/access.2020.3012182</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j6btd65gtnbjzbdbowtrqd6qju">fatcat:j6btd65gtnbjzbdbowtrqd6qju</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210718040322/https://ieeexplore.ieee.org/ielx7/6287639/8948470/09149875.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/19/12/1912794650dc946684be9dab8a205d8a1e64568e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3012182"> <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>

You Can't See the Forest for Its Trees: Assessing Deep Neural Network Testing via NeuraL Coverage [article]

Yuanyuan Yuan, Qi Pang, Shuai Wang
<span title="2021-12-03">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper summarizes eight design requirements for DNN testing criteria, taking into account distribution properties and practical concerns.  ...  NLC treats a single DNN layer as the basic computational unit (rather than a single neuron) and captures four critical features of neuron output distributions.  ...  It is seen that fault-triggering images generated by using NLC as the guidance cover the most classes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.01955v1">arXiv:2112.01955v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/inbz5nfbundfrgkc2nb6oj4kfm">fatcat:inbz5nfbundfrgkc2nb6oj4kfm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211207012700/https://arxiv.org/pdf/2112.01955v1.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.01955v1" 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>

Machine Learning and Deep Learning in Chemical Health and Safety: A Systematic Review of Techniques and Applications

Zeren Jiao, Pingfan Hu, Hongfei Xu, Qingsheng Wang
<span title="2020-10-18">2020</span> <i title="American Chemical Society (ACS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hcbdryxtwfev5lp5asfgrsbjpa" style="color: black;">Journal of Chemical Health and Safety</a> </i> &nbsp;
In this Review, commonly used ML/DL tools and concepts as well as popular ML/DL algorithms are introduced and discussed.  ...  This Review can serve as useful guidance for researchers who are interested in implementing ML/DL into chemical health and safety research and for readers who try to learn more information about novel  ...  For applications, most of the software contains a hierarchical clustering module like MATLAB, SAS, and Mathematica.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1021/acs.chas.0c00075">doi:10.1021/acs.chas.0c00075</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aldsumfj7bcazf4nkuhvoge7xm">fatcat:aldsumfj7bcazf4nkuhvoge7xm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201023064154/https://pubs.acs.org/doi/pdf/10.1021/acs.chas.0c00075" 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/da/72/da72c1e3c099a818e43f2dbad5b8c3b8aaad2369.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1021/acs.chas.0c00075"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acs.org </button> </a>

Automatic Fault Detection for Deep Learning Programs Using Graph Transformations [article]

Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh
<span title="2021-05-31">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we propose NeuraLint, a model-based fault detection approach for DL programs, using meta-modelling and graph transformations.  ...  Like any software, a DL program can be faulty, which implies substantial challenges of software quality assurance, especially in safety-critical domains.  ...  It makes sense that by using CNNs, the locality of information is crucial for performing the task.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.08095v2">arXiv:2105.08095v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5olxzsls4ngibcpgtfca3imlee">fatcat:5olxzsls4ngibcpgtfca3imlee</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210603103348/https://arxiv.org/pdf/2105.08095v2.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/7d/b4/7db41746d0e5fa83ca7268f833e3d15eaf367534.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2105.08095v2" 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>

Deep Learning and Its Applications to Machine Health Monitoring: A Survey [article]

Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, Robert X. Gao
<span title="2016-12-16">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Meanwhile, deep learning provides useful tools for processing and analyzing these big machinery data.  ...  Similarly, Verma et al. also used these three domains features to fed into a SAE-based DNN for fault diagnosis of air compressors [58] .  ...  In the fault size evaluation layer, based on each fault type, ADCNN with the same structure was used to predict fault size. Here, the classification mechanism is still used.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1612.07640v1">arXiv:1612.07640v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/46zurdmo2bcabo352qqppv5zki">fatcat:46zurdmo2bcabo352qqppv5zki</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200823215428/https://arxiv.org/pdf/1612.07640v1.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/44/f4/44f4b1b90f8d5515f2486e07e4cb4b9589c27518.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1612.07640v1" 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>

A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

Moussa Hamadache, Joon Ha Jung, Jungho Park, Byeng D. Youn
<span title="2019-05-16">2019</span> <i title="Springer Science and Business Media LLC"> JMST Advances </i> &nbsp;
A brief description of the different bearing-failure modes is given, then, the paper presents a comprehensive representation of the different health features (indexes, criteria) used for REB fault diagnostics  ...  Finally, deep-learning approaches for fault detection, diagnosis, and prognosis for REB are comprehensively reviewed.  ...  Finally, the different bearing faults were classified using a top-layer classifier of AE-based DNN outputs. S. Tao et al.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s42791-019-0016-y">doi:10.1007/s42791-019-0016-y</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sb3armogsvdebmwxjgpzfxwgju">fatcat:sb3armogsvdebmwxjgpzfxwgju</a> </span>
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Self-optimizing optical network with cloud-edge collaboration: architecture and application [Invited]

Zhuotong Li, Yongli Zhao, Yajie Li, Mingzhe Liu, Zebin Zeng, Xiangjun Xin, Feng Wang, Xinghua Li, Jie Zhang
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/k7cf45sp7faezjq6aasftgokc4" style="color: black;">IEEE Open Journal of the Computer Society</a> </i> &nbsp;
With the continuous upgrading of functions and performance, small AI-based chips can be used in optical networks as on-board AI.  ...  Proof by facts, the combination of artificial intelligence (AI) technology and software-defined networking (SDN) can improve significant optimization effects and management for optical transport networks  ...  Fault localization use case proposes the concept of alarm knowledge graphs (KGs). According to the alarm knowledge in the equipment manual, the knowledge graph is automatically constructed.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ojcs.2020.3030957">doi:10.1109/ojcs.2020.3030957</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ofprvvfirrbg7kurtjrwr7iduq">fatcat:ofprvvfirrbg7kurtjrwr7iduq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429152512/https://ieeexplore.ieee.org/ielx7/8782664/9024218/09224150.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/5b/3f/5b3fff80f10efc86190d342e50e0035524cbbe7e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ojcs.2020.3030957"> <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>

A Bearing Fault Diagnosis Method Using Multi-Branch Deep Neural Network

Van-Cuong Nguyen, Duy-Tang Hoang, Xuan-Toa Tran, Mien Van, Hee-Jun Kang
<span title="2021-12-09">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kduey52ubfebzlnyz5tuez7sl4" style="color: black;">Machines</a> </i> &nbsp;
In this paper, a novel vibration signal-based bearing fault diagnosis method using DNN is proposed.  ...  Feature extraction from a signal is the most important step in signal-based fault diagnosis. Deep learning or deep neural network (DNN) is an effective method to extract features from signals.  ...  Using the MDIR data and MB-DNN, the proposed fault diagnosis method is illustrated in Figure 5.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/machines9120345">doi:10.3390/machines9120345</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/trcqhhphrrh27lzerrjuywb5bq">fatcat:trcqhhphrrh27lzerrjuywb5bq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220106132523/https://mdpi-res.com/d_attachment/machines/machines-09-00345/article_deploy/machines-09-00345.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/96/9d/969dadf575118df6629f52a254259c8ba44d5b6e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/machines9120345"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

What does fault tolerant Deep Learning need from MPI? [article]

Vinay Amatya, Abhinav Vishnu, Charles Siegel, Jeff Daily
<span title="2017-09-11">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Our evaluation using the ImageNet dataset and AlexNet, and GoogLeNet neural network topologies demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM.  ...  We implement our approaches by ex- tending MaTEx-Caffe for using ULFM-based implementation.  ...  Lessons Learned We observe that existing local fault notification in the MPI specification and implementations may be used for developing fault tolerant DL implementations.  ... 
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Testing Feedforward Neural Networks Training Programs [article]

Houssem Ben Braiek, Foutse Khomh
<span title="2022-04-01">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Therefore, it is crucial to detect and correct errors throughout all the engineering steps of DNN-based software systems and not only on the resulting DNN model.  ...  Then, we design, TheDeepChecker, an end-to-end property-based debugging approach for DNN training programs.  ...  software systems Faults Base NN Perf.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.00694v1">arXiv:2204.00694v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u75eyoipkzaxhoyr5zn7fjsbjm">fatcat:u75eyoipkzaxhoyr5zn7fjsbjm</a> </span>
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