Big Data Deep Learning: Challenges and Perspectives
Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, bi...
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| Published in | IEEE access Vol. 2; pp. 514 - 525 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Piscataway
IEEE
2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, big data brings big opportunities and transformative potential for various sectors; on the other hand, it also presents unprecedented challenges to harnessing data and information. As the data keeps getting bigger, deep learning is coming to play a key role in providing big data predictive analytics solutions. In this paper, we provide a brief overview of deep learning, and highlight current research efforts and the challenges to big data, as well as the future trends. |
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| AbstractList | Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, big data brings big opportunities and transformative potential for various sectors; on the other hand, it also presents unprecedented challenges to harnessing data and information. As the data keeps getting bigger, deep learning is coming to play a key role in providing big data predictive analytics solutions. In this paper, we provide a brief overview of deep learning, and highlight current research efforts and the challenges to big data, as well as the future trends. |
| Author | Chen, Xue-Wen Lin, Xiaotong |
| Author_xml | – sequence: 1 givenname: Xue-Wen surname: Chen fullname: Chen, Xue-Wen email: xwen.chen@gmail.com organization: Department of Computer Science, Wayne State University, Detroit, MI, USA – sequence: 2 givenname: Xiaotong surname: Lin fullname: Lin, Xiaotong organization: Department of Computer Science and Engineering, Oakland University, Rochester, MI, USA |
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| CODEN | IAECCG |
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| Cites_doi | 10.1109/TPAMI.2008.128 10.1145/1390156.1390294 10.1103/PhysRevE.56.3426 10.1109/TASL.2011.2134090 10.1109/ICASSP.2012.6288333 10.1109/TNN.2010.2091281 10.1142/S0218213008004059 10.1162/neco.2006.18.7.1527 10.1109/ACCESS.2014.2319813 10.1145/279943.279962 10.1109/TNNLS.2013.2242090 10.1103/PhysRevLett.74.4337 10.1145/1390156.1390303 10.1016/S0924-6509(08)70038-2 10.1162/NECO_a_00052 10.1109/IJCNN.2009.5178779 10.1109/TPAMI.1984.4767596 10.1109/TKDE.2009.191 10.2307/2685208 10.1017/CBO9781139042918.020 10.1126/science.1127647 10.1109/72.750549 10.1561/2200000018 10.1088/0305-4470/28/20/002 10.1109/MSP.2012.2205597 10.1561/2200000006 10.1145/1553374.1553486 10.1109/TNN.2004.828757 10.1038/505146a 10.1109/CVPR.2009.5206545 10.1109/5.726791 10.1109/TNN.2008.2003998 10.1113/jphysiol.1968.sp008455 10.1145/267460.267475 10.1109/ICCV.2011.6126474 10.1145/1273496.1273592 10.1145/1273496.1273596 10.1109/TNN.2011.2160459 10.1007/3-540-49430-8_2 10.1162/089976602760128018 10.1088/0305-4470/30/22/005 10.14778/1920841.1920931 10.1109/TNN.2006.880583 10.1038/323533a0 10.1109/ICASSP.2013.6639343 10.1109/TNN.2006.889943 10.1109/TNN.2006.879766 10.1145/103418.103467 10.1145/2213836.2213958 10.1109/TSMCC.2003.813150 10.1145/1273496.1273598 10.1016/S0305-0548(03)00104-7 10.1109/ICDAR.2003.1227801 10.1002/9781119992691.ch5 10.7551/mitpress/9780262017091.001.0001 10.1109/TNN.2008.2000082 10.1017/CBO9781139042918.003 10.1007/BF00115301 10.1109/TNN.2006.881710 10.1145/1390156.1390256 10.1109/TPAMI.2012.268 10.1007/978-3-642-16108-7_6 |
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| References | ref53 lecun (ref38) 1998 ref52 ref54 freund (ref74) 0 dean (ref56) 0 (ref49) 2013 ref51 ref50 ref45 ref48 ref41 nair (ref23) 2009; 22 ref44 ref43 marc'aurelio ranzato (ref11) 0; 20 hinton (ref28) 2010 collobert (ref25) 2011; 12 duchi (ref57) 2011; 12 ref8 ref6 gantz (ref3) 2010 ref5 ref40 cire?an (ref36) 0 ref31 ref32 (ref60) 2012 srivastava (ref70) 0 ref39 ng (ref7) 0; 19 bengio (ref99) 2012; 27 bottou (ref88) 0 ref24 kirk (ref20) 2013 ref26 (ref4) 2011 ref22 ref21 krizhevsky (ref47) 2009 vanhoucke (ref46) 0 gantz (ref2) 2011 ref27 ref29 laney (ref63) 2012 krizhevsky (ref55) 0 mesnil (ref101) 2011; 7 haberlin (ref61) 0 ref13 (ref62) 2013 ref12 pan (ref106) 2011; 22 ref15 ref14 ref97 ref96 ref98 ref16 ref19 scherer (ref37) 0 ref18 ref93 ref92 seide (ref35) 0 ref95 ref94 ref91 ref90 ref89 ref85 ref87 coats (ref58) 2013; 28 ngiam (ref69) 0 glorot (ref100) 0 fergus (ref68) 0 tomov (ref59) 2011 ref82 ref81 ref84 ref83 sinha (ref67) 0 ref80 ref79 ref78 ref75 ref104 ref105 ref77 ref102 ref76 ref103 wang (ref65) 2007; 8 (ref1) 0 mesnil (ref107) 0 bengio (ref30) 0 bengio (ref10) 0; 12 larochelle (ref33) 2009; 10 ref73 ref72 lee (ref34) 0 ref64 ref66 martens (ref42) 0 crego (ref9) 2013 bottou (ref71) 1998 ruiz de angulo (ref86) 1995; 6 efrati (ref17) 2013 |
| References_xml | – ident: ref64 doi: 10.1109/TPAMI.2008.128 – start-page: 437 year: 0 ident: ref35 article-title: Conversational speech transcription using context-dependent deep neural networks publication-title: Proc INTERSPEECH – volume: 7 start-page: 1 year: 2011 ident: ref101 article-title: Unsupervised and transfer learning challenge: A deep learning approach publication-title: J Mach Learn Res – ident: ref32 doi: 10.1145/1390156.1390294 – ident: ref83 doi: 10.1103/PhysRevE.56.3426 – start-page: 325 year: 0 ident: ref74 article-title: Game theory, on-line prediction and boosting publication-title: Proc 9th Annu Conf Comput Learn Theory – volume: 8 start-page: 1867 year: 2007 ident: ref65 article-title: Large margin semi-supervised learning publication-title: J Mach Learn Res – ident: ref12 doi: 10.1109/TASL.2011.2134090 – year: 2013 ident: ref20 publication-title: Universities IBM join forces to build a brain-like computer PCWorld – ident: ref44 doi: 10.1109/ICASSP.2012.6288333 – volume: 22 start-page: 199 year: 2011 ident: ref106 article-title: Domain adaptation via transfer component analysis publication-title: IEEE Trans Neural Netw doi: 10.1109/TNN.2010.2091281 – ident: ref103 doi: 10.1142/S0218213008004059 – volume: 6 start-page: 657 year: 1995 ident: ref86 article-title: On-line learning with minimal degradation in feedforward networks publication-title: Torras – year: 0 ident: ref1 publication-title: National Security Agency The National Security Agency Missions Authorities Oversight and Partnerships – ident: ref29 doi: 10.1162/neco.2006.18.7.1527 – year: 2011 ident: ref4 publication-title: Big Data The Next Frontier for Innovation Competition and Productivity – ident: ref43 doi: 10.1109/ACCESS.2014.2319813 – ident: ref104 doi: 10.1145/279943.279962 – year: 2013 ident: ref17 publication-title: How 'deep learning' works at Apple beyond Information – volume: 19 start-page: 281 year: 0 ident: ref7 article-title: Map-reduce for machine learning on multicore publication-title: Proc Adv Neu Inf Proc Sys – ident: ref90 doi: 10.1109/TNNLS.2013.2242090 – ident: ref82 doi: 10.1103/PhysRevLett.74.4337 – start-page: 1106 year: 0 ident: ref55 article-title: ImageNet classification with deep convolutional neural networks publication-title: Proc Adv NIPS – volume: 22 start-page: 1339 year: 2009 ident: ref23 article-title: 3D object recongition with deep belief nets publication-title: Proc Adv NIPS – year: 2013 ident: ref9 publication-title: Business – ident: ref66 doi: 10.1145/1390156.1390303 – ident: ref77 doi: 10.1016/S0924-6509(08)70038-2 – year: 2012 ident: ref60 publication-title: Obama Administration Unveils Big Data Initiative Announces $200 Million in New R&D Investments [R] – ident: ref15 doi: 10.1162/NECO_a_00052 – ident: ref92 doi: 10.1109/IJCNN.2009.5178779 – volume: 12 start-page: 2493 year: 2011 ident: ref25 article-title: Natural language processing almost from scratch publication-title: J Mach Learn Res – ident: ref52 doi: 10.1109/TPAMI.1984.4767596 – ident: ref102 doi: 10.1109/TKDE.2009.191 – ident: ref53 doi: 10.2307/2685208 – year: 0 ident: ref69 article-title: Multimodal deep learning publication-title: Proc 28th Int Conf Mach Learn – ident: ref48 doi: 10.1017/CBO9781139042918.020 – ident: ref21 doi: 10.1126/science.1127647 – ident: ref84 doi: 10.1109/72.750549 – ident: ref76 doi: 10.1561/2200000018 – ident: ref81 doi: 10.1088/0305-4470/28/20/002 – ident: ref13 doi: 10.1109/MSP.2012.2205597 – year: 0 ident: ref100 article-title: Domain adaptation for large-scale sentiment classification: A deep learning approach publication-title: Proc 28th Int Conf Mach Learn – ident: ref22 doi: 10.1561/2200000006 – year: 1998 ident: ref71 article-title: Online algorithms and stochastic approximations publication-title: On-Line Learning in Neural Networks – ident: ref41 doi: 10.1145/1553374.1553486 – ident: ref96 doi: 10.1109/TNN.2004.828757 – ident: ref18 doi: 10.1038/505146a – ident: ref39 doi: 10.1109/CVPR.2009.5206545 – ident: ref24 doi: 10.1109/5.726791 – start-page: 153 year: 0 ident: ref30 article-title: Greedy layer-wise training of deep networks publication-title: Proc Neural Inf Process Syst – ident: ref95 doi: 10.1109/TNN.2008.2003998 – ident: ref40 doi: 10.1113/jphysiol.1968.sp008455 – ident: ref72 doi: 10.1145/267460.267475 – volume: 12 start-page: 2121 year: 2011 ident: ref57 article-title: Adaptive subgradient methods for online learning and stochastic optimization publication-title: J Mach Learn Res – year: 0 ident: ref42 article-title: Deep learning via Hessian-free optimization publication-title: Proc 27th Int Conf Mach Learn – ident: ref16 doi: 10.1109/ICCV.2011.6126474 – ident: ref105 doi: 10.1145/1273496.1273592 – ident: ref14 doi: 10.1145/1273496.1273596 – ident: ref93 doi: 10.1109/TNN.2011.2160459 – year: 1998 ident: ref38 article-title: Efficient backprop publication-title: Neural Networks Tricks of the Trade doi: 10.1007/3-540-49430-8_2 – ident: ref31 doi: 10.1162/089976602760128018 – volume: 12 start-page: 400 year: 0 ident: ref10 article-title: Modeling high-dimensional discrete data with multi-layer neural networks publication-title: Proc Adv Neural Inf Process Syst – ident: ref80 doi: 10.1088/0305-4470/30/22/005 – ident: ref6 doi: 10.14778/1920841.1920931 – year: 2013 ident: ref49 publication-title: CUDA C Programming Guide PG-02829-001_v5 5 – ident: ref85 doi: 10.1109/TNN.2006.880583 – ident: ref27 doi: 10.1038/323533a0 – start-page: 92 year: 0 ident: ref37 article-title: Evaluation of pooling operations in convolutional architectures for object recognition publication-title: Proc Int Conf Artif Neural Netw – ident: ref50 doi: 10.1109/ICASSP.2013.6639343 – ident: ref97 doi: 10.1109/TNN.2006.889943 – year: 2010 ident: ref3 publication-title: The Digital Universe Decade-Are You Ready – ident: ref26 doi: 10.1109/TNN.2006.879766 – volume: 28 start-page: 1337 year: 2013 ident: ref58 article-title: Deep Learning with COTS HPS systems publication-title: J Mach Learn Res – ident: ref75 doi: 10.1145/103418.103467 – year: 0 ident: ref70 article-title: Multimodal learning with deep Boltzmann machines publication-title: Proc Adv NIPS – start-page: 1687 year: 0 ident: ref67 article-title: Semi-supervised learning using sparse eigenfunction bases publication-title: Proc Adv NIPS – ident: ref5 doi: 10.1145/2213836.2213958 – volume: 10 start-page: 1 year: 2009 ident: ref33 article-title: Exploring strategies for training deep neural networks publication-title: J Mach Learn Res – start-page: 522 year: 0 ident: ref68 article-title: Semi-supervised learning in gigantic image collections publication-title: Proc Adv NIPS – year: 2011 ident: ref2 publication-title: Extracting Value from Chaos – ident: ref79 doi: 10.1109/TSMCC.2003.813150 – ident: ref89 doi: 10.1145/1273496.1273598 – ident: ref78 doi: 10.1016/S0305-0548(03)00104-7 – year: 2012 ident: ref63 publication-title: The Importance of 'Big Data' A Definition – start-page: 345 year: 0 ident: ref107 article-title: Unsupervised and transfer learning under uncertainty: From object detections to scene categorization publication-title: Proc ICPR – volume: 27 start-page: 17 year: 2012 ident: ref99 article-title: Deep learning of representations for unsupervised and transfer learning publication-title: J Mach Learn Res – ident: ref54 doi: 10.1109/ICDAR.2003.1227801 – ident: ref19 doi: 10.1002/9781119992691.ch5 – start-page: 801 year: 0 ident: ref34 article-title: Efficient sparse coding algorithms publication-title: Proc Neural Info Proc Sys – year: 2009 ident: ref47 publication-title: Learning multiple layers of features from tiny images – ident: ref91 doi: 10.7551/mitpress/9780262017091.001.0001 – start-page: 1237 year: 0 ident: ref36 article-title: Flexible, high performance convolutional neural networks for image classification publication-title: Proc 22nd Conf Artif Intell – year: 2013 ident: ref62 publication-title: Fact Sheet Brain Initiative – ident: ref94 doi: 10.1109/TNN.2008.2000082 – volume: 20 start-page: 1185 year: 0 ident: ref11 article-title: Sparse feature learning for deep belief networks publication-title: Proc Adv Neural Inf Process Syst – year: 0 ident: ref88 article-title: Stochastic gradient learning in neural networks publication-title: Proc Neuro-Nimes – ident: ref8 doi: 10.1017/CBO9781139042918.003 – year: 2011 ident: ref59 – year: 0 ident: ref46 article-title: Improving the speed of neural networks on CPUs publication-title: Proc NIPS Workshop on Deep Learning and Unsupervised Feature Learning – year: 2010 ident: ref28 article-title: A practical guide to training restricted Boltzmann machines publication-title: Dept Comput Sci Univ Toronto – start-page: 1232 year: 0 ident: ref56 article-title: Large scale distributed deep networks publication-title: Proc Adv NIPS – ident: ref73 doi: 10.1007/BF00115301 – ident: ref87 doi: 10.1109/TNN.2006.881710 – ident: ref51 doi: 10.1145/1390156.1390256 – ident: ref45 doi: 10.1109/TPAMI.2012.268 – year: 0 ident: ref61 publication-title: Governor Patrick Announces New Initiative to Strengthen Massachusetts' Position as a World Leader in Big Data – ident: ref98 doi: 10.1007/978-3-642-16108-7_6 |
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| SubjectTerms | Big Data Classifier design and evaluation Computer vision Data processing Deep learning feature representation Information analysis Machine learning Natural language processing neural nets models parallel processing Pattern recognition Speech recognition |
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| Title | Big Data Deep Learning: Challenges and Perspectives |
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