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1. Full Text A novel double deep ELMs ensemble system for time series forecasting
by Song, Gang and Dai, Qun
Knowledge-Based Systems, ISSN 0950-7051, 10/2017, Volume 134, pp. 31 - 49
Extreme Learning Machine (ELM) has proved to be well suited to different kinds of classification and regression problems. However, failing to seek deep... 
Hierarchical ELM (H-ELM) | Time series forecasting (TSF) | Double deep ELMs ensemble system (DD-ELMs-ES) | Deep representations learning via ELM (dr-ELM) | Constrained H-ELM (CH-ELM) | Self-adaptive ReTSP-Trend (SA-ReTSP-Trend) | AUTOENCODERS | REPRESENTATIONS | ALGORITHM | COMBINATION | EXTREME LEARNING-MACHINE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | PREDICTION | NEURAL-NETWORKS | FEEDFORWARD NETWORKS | HYBRID | RESIDUAL ANALYSIS | Analysis | Forecasts and trends | Machine learning | Computer science | Algorithms
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2. After the elm ....
by Clouston, Brian and Stansfield, Kathy
1979, 186
Trees | Dutch elm disease | Elm
Book
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3. Full Text A semi-supervised online sequential extreme learning machine method
by Jia, Xibin and Wang, Runyuan and Liu, Junfa and Powers, David M.W
Neurocomputing, ISSN 0925-2312, 01/2016, Volume 174, pp. 168 - 178
This paper proposes a learning algorithm called Semi-supervised Online Sequential ELM, denoted as SOS-ELM. It aims to provide a solution for streaming data... 
Semi-supervised ELM (SS-ELM) | Semi-supervised online sequential ELM (SOS-ELM) | Online Sequential ELM (OS-ELM) | REGRESSION | NETWORK | ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms | Data mining | Analysis | Methods
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4. Elm
by Richens, Richard Hook
1983, ISBN 0521249163, xii, 347
Elm in art | Elm in literature | Elm
Book
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5. Full Text Optimization method based extreme learning machine for classification
by Huang, Guang-Bin and Ding, Xiaojian and Zhou, Hongming
Neurocomputing, ISSN 0925-2312, 2010, Volume 74, Issue 1, pp. 155 - 163
Extreme learning machine (ELM) as an emergent technology has shown its good performance in regression applications as well as in large dataset (and/or... 
Support vector network | Minimal norm of weights | Extreme learning machine | Support vector machine | ELM feature space | ELM kernel | Equivalence between ELM and SVM | Maximal margin | Primal and dual ELM networks | APPROXIMATION | FEEDFORWARD NETWORKS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Learning | Support vector machines | Computer simulation | Neural networks | Mathematical analysis | Classification | Standards | Optimization
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6. Ten-year performance of the United States national elm trial
by Griffin, Jason J and Jacobi, William R and McPherson, E. Gregory and Sadof, Clifford S and McKenna, James R and Gleason, Mark L and Gauthier, Nicole Ward and Potter, Daniel A and Smitley, David R and Adams, Gerard C and Gould, Ann Brooks and Cash, Christian R and Walla, James A and Starrett, Mark C and Chastagner, Gary and Sibley, Jeff L and Krischik, Vera A and Newby, Adam F
Arboriculture and Urban Forestry, ISSN 1935-5297, 05/2017, Volume 43, Issue 3, pp. 107 - 120
Lacebark elm | Wilson elm | Chalkbark elm | Urban forestry | Smoothleaf elm | Tree evaluation | Ulmus wilsoniana | Japanese elm | Ulmus parvifolia | Scotch elm | Ulmus glabra | Ulmus pumila | Siberian elm | Ulmus carpinifolia | Ulmus japonica | Ulmus propinqua
Journal Article
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7. Full Text Ulmus wilsoniana 'Prospector'
National Arboretum (U.S.). Floral and Nursery Plants Research Unit
1999
Shade trees | United States | Japanese elm
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8. Ten-year performance of the United States national elm trial
by Griffin, Jason J and Jacobi, William R and McPherson, E. Gregory and Sadof, Clifford S and McKenna, James R and Gleason, Mark L and Gauthier, Nicole Ward and Potter, Daniel A and Smitley, David R and Adams, Gerard C and Gould, Ann Brooks and Cash, Christian R and Walla, James A and Starrett, Mark C and Chastagner, Gary and Sibley, Jeff L and Krischik, Vera A and Newby, Adam F
Arboriculture and Urban Forestry, ISSN 1935-5297, 07/2017, Volume 43, Issue 4, pp. 107 - 120
Tree Evaluation | Lacebark Elm | Urban Forestry | Wilson Elm | Chalkbark Elm | Smoothleaf Elm | Ulmus wilsoniana | Japanese Elm | Scotch Elm | Ulmus parvifolia | Ulmus glabra | Ulmus pumila | Siberian Elm | Ulmus carpinifolia | Ulmus japonica | Ulmus propinqua
Journal Article
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9. Elm leaf beetle performance on ozone-fumigated elm
by Barger, Jack H and Hall, Richard W and Townsend, Alden M
1992, Research paper (Northeastern Forest Experiment Station (Radnor, Pa.)), Volume NE-RP-661., 9
Elm leaf-beetle | Diseases and pests | Elm
Book
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10. Dutch elm disease
by Gibbs, J. N and Burdekin, D. A and Brasier, C. M
1977, Forest record (Great Britain. Forestry Commission), ISBN 9780117102378, Volume 115., 11
Dutch elm disease | Diseases and pests | Elm
Book
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11. Elm spanworm
by Fedde, Gerhard F
1971, Rev., Forest pest leaflet (United States. Forest Service), Volume 81., 6
Trees | Diseases and pests | Elm | Elm spanworm
Book
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12. Elm spanworm
by Fedde, Gerhard F
1963, Forest pest leaflet (United States. Forest Service), Volume 81., 7
Trees | Diseases and pests | Elm | Elm spanworm
Book
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13. The status and development of elm disease in Britain
by Peace, T. R
1960, Bulletin (Great Britain. Forestry Commission), Volume 33., iv, 44
Dutch elm disease | Diseases and pests | Elm
Book
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14. Les insectes de l'orme aux niveaux de l'ecorce et du bois et leur rôle avec la maladie Hollandaise
by Robert, Adrien
1952, 364
Dutch elm disease | Diseases and pests | Elm
Book
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15. Full Text Clustering in extreme learning machine feature space
by He, Qing and Jin, Xin and Du, Changying and Zhuang, Fuzhen and Shi, Zhongzhi
Neurocomputing, ISSN 0925-2312, 03/2014, Volume 128, pp. 88 - 95
Extreme learning machine (ELM), used for the “generalized” single-hidden-layer feedforward networks (SLFNs), is a unified learning platform that can use a... 
Extreme learning machine (ELM) | ELM feature space | ELM kMeans | Nonnegative matrix factorization (NMF) | ELM NMF clustering | Data clustering | REGRESSION | EFFICIENT ALGORITHM | CLASSIFICATION | NETWORKS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | KERNEL | NONNEGATIVE MATRIX FACTORIZATION | Algorithms | Learning | Approximation | Mathematical analysis | Elm | Mapping | Clustering | Factorization | Neural networks
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16. Full Text Extreme Learning Machines [Trends & Controversies]
by Cambria, Erik and Huang, Guang-Bin and Kasun, Liyanaarachchi Lekamalage Chamara and Zhou, Hongming and Vong, Chi Man and Lin, Jiarun and Yin, Jianping and Cai, Zhiping and Liu, Qiang and Li, Kuan and Leung, Victor C.M and Feng, Liang and Ong, Yew-Soon and Lim, Meng-Hiot and Akusok, Anton and Lendasse, Amaury and Corona, Francesco and Nian, Rui and Miche, Yoan and Gastaldo, Paolo and Zunino, Rodolfo and Decherchi, Sergio and Yang, Xuefeng and Mao, Kezhi and Oh, Beom-Seok and Jeon, Jehyoung and Toh, Kar-Ann and Teoh, Andrew Beng Jin and Kim, Jaihie and Yu, Hanchao and Chen, Yiqiang and Liu, Junfa
IEEE Intelligent Systems, ISSN 1541-1672, 11/2013, Volume 28, Issue 6, pp. 30 - 59
This special issue includes eight original works that detail the further developments of ELMs in theories, applications, and hardware implementation. In... 
signature biometrics | deep networks | visualization | random projections | ELM | computation outsourcing | Nonhomogeneous media | ensemble | Learning systems | partitioned ELM | Kinect | evolutionary optimization | random permutations | representational learning | Big data | text mining | cloud computing | Adaptive learning | hand gesture signature verification | Special issues and sections | memetic computation | meta meme | Gesture recognition | OS-ELM | Biological neural networks | human-computer interaction | Data visualization | extreme learning machine | knowledge extraction | Machine learning | Artificial intelligence | online sequential ELM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Learning | Permutations | Cloud computing | Neural networks | Projection | Outsourcing | Signatures | Recognition
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17. Dutch elm disease-the early papers
: selected works of seven Dutch women phytopathologists
by Holmes, Francis W and Heybroek, Hans M
1990, ISBN 9780890541104, v, 154
Dutch elm disease | Diseases and pests | Elm | Femmes | Phytopathologistes | Maladies et fléaux | Histoire | Biographie | Recherche | Pays-Bas | Orme | Maladie hollandaise de l'orme
Book
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18. The American elm
: its glorious past, its present dilemma, its hope for protection
American Forestry Association
1937, 32
Maladies et fléaux | Diseases and pests | Orme | Elm
Book
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19. Studies on Cerato-ulmin, a new wilt toxin produced by the Dutch elm disease fungus Ceratocystis ulmi (Buisman) C. Moreau
by Richards, Wayne Cyril
1985, 155
Dutch elm disease
Book
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20. Isolation of elm volatiles attractive to the native elm bark beetle Hylurgopinus rufipes (Eichh.)
: final report
by Kuenen, L. P. S and New Brunswick (N.J.) Research and Productivity Council
1984, Report (New Brunswick Research and Productivity Council), Volume REP C/84/017., Various pagings
Diseases and pests | Elm
Book
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