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1. Machine learning methods in the environmental sciences
: neural networks and kernels
by Hsieh, William Wei
2009, ISBN 0521791928, xiii, 349
Kernel functions | Environmental sciences | Neural networks (Computer science) | Machine learning
Book
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2. Knowledge discovery with support vector machines
by Hamel, Lutz
2009, 1st ed., Wiley series on methods and applications in data mining, ISBN 0470371927, xv, 246
Support vector machines | Computer algorithms | Data mining | Machine learning | COMPUTERS / Databases / Data Mining
Book
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3. Support vector machines and their application in chemistry and biotechnology
2011, ISBN 9781439821275, x, 201
Book
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4. Full Text Multiple kernel extreme learning machine
by Liu, Xinwang and Wang, Lei and Huang, Guang-Bin and Zhang, Jian and Yin, Jianping
Neurocomputing (Amsterdam), ISSN 0925-2312, 02/2015, Volume 149, pp. 253 - 264
Support vector machines | Extreme learning machine | Multiple kernel learning | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Computer science | Military electronics industry | Algorithms | Alzheimer's disease | Mathematical optimization | Learning | Kernels | Neural networks | Classification | Regression | Computational efficiency | Optimization
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5. Full Text Kernel Methods in Machine Learning
by Thomas Hofmann and Bernhard Schölkopf and Alexander J. Smola
The Annals of statistics, ISSN 0090-5364, 6/2008, Volume 36, Issue 3, pp. 1171 - 1220
Approximation | Machine learning | Dot product of vectors | Hilbert spaces | Principal components analysis | Mathematical vectors | Mathematical functions | Mathematics | Learning theory | Modeling | Support vector machines | Graphical models | Reproducing kernels | Statistics & Probability | Physical Sciences | Science & Technology | General topics | Mathematical analysis | Exact sciences and technology | Probability theory and stochastic processes | Markov processes | Functional analysis | Probability and statistics | Statistics | Sciences and techniques of general use | Studies | Algorithms | Linear programming | Nonlinear programming | Estimating techniques | Artificial intelligence | support vector machines | 68T05 | reproducing kernels | graphical models | 30C40
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6. Full Text Structural Minimax Probability Machine
by Bin Gu and Xingming Sun and Sheng, Victor S
IEEE transaction on neural networks and learning systems, ISSN 2162-237X, 07/2017, Volume 28, Issue 7, pp. 1646 - 1656
Support vector machines | Algorithm design and analysis | structural learning | Error analysis | Bayes learning | Hidden Markov models | Mixture models | kernel methods | Market research | second-order cone programming (SOCP) | finite mixture models | Covariance matrices | Engineering | Technology | Computer Science | Engineering, Electrical & Electronic | Computer Science, Artificial Intelligence | Computer Science, Theory & Methods | Computer Science, Hardware & Architecture | Science & Technology | Economic models | Classifiers | Accuracy | Minimax technique | Probability theory | Data sets | Classification | Nonlinearity | Probabilistic methods | Covariance matrix
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7. Full Text Efficient nonparametric n -body force fields from machine learning
by Glielmo, Aldo and Zeni, Claudio and De Vita, Alessandro
Physical review. B, ISSN 2469-9950, 05/2018, Volume 97, Issue 18
Physical Sciences | Materials Science | Technology | Materials Science, Multidisciplinary | Physics, Condensed Matter | Physics | Science & Technology | Physics, Applied | Kernels | Accuracy | Gaussian process | Machine learning | Predictions | Materials selection | Mathematical models | Physics - Computational Physics
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8. Full Text Quantum Machine Learning in Feature Hilbert Spaces
by Schuld, Maria and Killoran, Nathan
Physical review letters, ISSN 0031-9007, 02/2019, Volume 122, Issue 4, pp. 040504 - 040504
Physics, Multidisciplinary | Physical Sciences | Physics | Science & Technology | Kernels | Support vector machines | Feature maps | Quantum computing | Algorithms | Maps | Machine learning | Hilbert space | Artificial intelligence | Quantum theory | Quantum computers | Continuity (mathematics)
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9. Full Text Weighted extreme learning machine for imbalance learning
by Zong, Weiwei and Huang, Guang-Bin and Chen, Yiqiang
Neurocomputing (Amsterdam), ISSN 0925-2312, 02/2013, Volume 101, pp. 229 - 242
Weighted extreme learning machine | Extreme learning machine | Imbalanced learning | Single hidden layer feedforward networks | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Learning | Kernels | Networks | Tasks | Balancing | Classification | Elm | Mapping | Neural networks
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10. Full Text Dlib-ml: A machine learning toolkit
by King, Davis E
Journal of machine learning research, ISSN 1532-4435, 07/2009, Volume 10, pp. 1755 - 1758
Rvm | Kernel clustering, C++ | Bayesian networks | Svm | Kernel-methods | Automation & Control Systems | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology
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11. Full Text The Shogun machine learning toolbox
by Sonnenburg, Sören and Rätsch, Gunnar and Henschel, Sebastian and Widmer, Christian and Behr, Jonas and Zien, Alexander and De Bona, Fabio and Binder, Alexander and Gehl, Christian and Franc, Vojtěch
Journal of machine learning research, ISSN 1532-4435, 06/2010, Volume 11, pp. 1799 - 1802
Kernels | Support vector machines | Octave | Large-scale learning | Python | Automation & Control Systems | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology
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12. Full Text Performance Comparison of Support Vector Machine, Random Forest, and Extreme Learning Machine for Intrusion Detection
by Ahmad, Iftikhar and Basheri, Mohammad and Iqbal, Muhammad Javed and Rahim, Aneel
IEEE access, ISSN 2169-3536, 2018, Volume 6, pp. 33789 - 33795
Support vector machines | Radio frequency | Training | Detection rate | false alarms | NSL–KDD | support vector machine | Intrusion detection | extreme learning machine | Forestry | random forest | Kernel | NSL-KDD | Computer Science, Information Systems | Engineering | Technology | Computer Science | Engineering, Electrical & Electronic | Telecommunications | Science & Technology | Intrusion | Adaptive systems | False alarms | Artificial neural networks | Data mining | Security | Security management | Data sets | Classification | Machine learning | Multilayer perceptrons | Traffic information | Firewalls | Intrusion detection systems
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13. Full Text Kernel methods in system identification, machine learning and function estimation: A survey
by Pillonetto, Gianluigi and Dinuzzo, Francesco and Chen, Tianshi and De Nicolao, Giuseppe and Ljung, Lennart
Automatica (Oxford), ISSN 0005-1098, 03/2014, Volume 50, Issue 3, pp. 657 - 682
Linear system identification | Inverse problems | Model complexity selection | Bias-variance trade-off | Kernel-based regularization | Gaussian processes | Prediction error methods | Reproducing kernel Hilbert spaces | Engineering, Electrical & Electronic | Engineering | Automation & Control Systems | Technology | Science & Technology | Data processing. List processing. Character string processing | Learning and adaptive systems | Memory organisation. Data processing | Exact sciences and technology | Applied sciences | Control theory. Systems | Software | Modelling and identification | Artificial intelligence | Computer science; control theory; systems
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14. Full Text Kernel Methods and Machine Learning
by Kung, S. Y
04/2014, ISBN 9781107024960, Volume 9781107024960, 618
Support vector machines | Kernel functions | Machine learning
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