2001 LearningWithKernels

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Subject Headings: Support Vector Machine Classifier, Kernel Function.

Notes

Cited By

2004

Quotes

Book Overview

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- kernels -- for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.

Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

1 A Tutorial Introduction

1.1  Data Representation and Similarity . . . . . . . . . . . . . . . . . . .   1
1.2  A Simple Pattern Recognition Algorithm  . . . . . . . . . . . . . . .   3
1.3  Some Insights From Statistical Learning Theory . . . . . . . . . . . .   6
1.4  Hyperplane Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . .  10
1.5  Support Vector Classification . . . . . . . . . . . . . . . . . . . . . . 13
1.6  Support Vector Regression . . . . . . . . . . . . . . . . . . . . . . . .  16
1.7  Kernel Principal Component Analysis  . . . . . . . . . . . . . . . . .  18
1.8  Empirical Results and Implementations  . . . . . . . . . . . . . . . .  19

...

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  • 727. Hastagiri P. Vanchinathan, Isidor Nikolic, Fabio De Bona, Andreas Krause, Explore-exploit in Top-N Recommender Systems via Gaussian Processes, Proceedings of the 8th ACM Conference on Recommender Systems, October 06-10, 2014, Foster City, Silicon Valley, California, USA
  • 728. Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He, Online Kernel Learning with a Near Optimal Sparsity Bound, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
  • 729. Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani, Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications, Proceedings of the 31st International Conference on International Conference on Machine Learning, June 21-26, 2014, Beijing, China
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  • 732. Min-Ling Zhang, Bin-Bin Zhou, Xu-Ying Liu, Partial Label Learning via Feature-Aware Disambiguation, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 13-17, 2016, San Francisco, California, USA
  • 733. Hichem Sedjelmaci, Sidi Mohammed Senouci, An Accurate and Efficient Collaborative Intrusion Detection Framework to Secure Vehicular Networks, Computers and Electrical Engineering, v.43 N.C, p.33-47, April 2015
  • 734. Anthony Bourrier, Florent Perronnin, Rémi Gribonval, Patrick Pérez, Hervé Jégou, Explicit Embeddings for Nearest Neighbor Search with Mercer Kernels, Journal of Mathematical Imaging and Vision, v.52 n.3, p.459-468, July 2015
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  • 739. Koby Crammer, Tal Wagner, Volume Regularization for Binary Classification, Proceedings of the 25th International Conference on Neural Information Processing Systems, p.332-340, December 03-06, 2012, Lake Tahoe, Nevada
  • 740. Zhe Xue, Guorong Li, Qingming Huang, Joint Multi-view Representation Learning and Image Tagging, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona
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  • 742. Eunjung Park, John Cavazos, Marco A. Alvarez, Using Graph-based Program Characterization for Predictive Modeling, Proceedings of the Tenth International Symposium on Code Generation and Optimization, March 31-April 04, 2012, San Jose, California
  • 743. D. Sculley, Gabriel M. Wachman, Relaxed Online SVMs for Spam Filtering, Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 23-27, 2007, Amsterdam, The Netherlands
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  • 745. Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke, Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), v.4 n.2, p.216-226, April 2007
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  • 747. Arthur Tenenhaus, Alain Giron, Emmanuel Viennet, Michel Béra, Gilbert Saporta, Bernard Fertil, Kernel Logistic PLS: A Tool for Supervised Nonlinear Dimensionality Reduction and Binary Classification, Computational Statistics & Data Analysis, v.51 n.9, p.4083-4100, May, 2007
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  • 749. Hui-Ling Chen, Bo Yang, Jie Liu, Da-You Liu, A Support Vector Machine Classifier with Rough Set-based Feature Selection for Breast Cancer Diagnosis, Expert Systems with Applications: An International Journal, v.38 n.7, p.9014-9022, July, 2011
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  • 752. Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura, Convex Sets As Prototypes for Classifying Patterns, Engineering Applications of Artificial Intelligence, v.22 n.1, p.101-108, February, 2009
  • 753. Wolfgang Konen, Patrick Koch, Oliver Flasch, Thomas Bartz-Beielstein, Martina Friese, Boris Naujoks, Tuned Data Mining: A Benchmark Study on Different Tuners, Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, July 12-16, 2011, Dublin, Ireland
  • 754. Ying Zhao, Justin Zobel, Entropy-based Authorship Search in Large Document Collections, Proceedings of the 29th European Conference on IR Research, April 02-05, 2007, Rome, Italy
  • 755. Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan, Learning Kernel-Based Halfspaces with the 0-1 Loss, SIAM Journal on Computing, v.40 n.6, p.1623-1646, November 2011
  • 756. J. Farquhar, 2009 Special Issue: A Linear Feature Space for Simultaneous Learning of Spatio-spectral Filters in BCI, Neural Networks, v.22 n.9, p.1278-1285, November, 2009
  • 757. Carlotta Orsenigo, Carlo Vercellis, Time Series Gene Expression Data Classification via L<inf>1</inf>-norm Temporal SVM, Proceedings of the 5th IAPR International Conference on Pattern Recognition in Bioinformatics, September 22-24, 2010, Nijmegen, The Netherlands
  • 758. Hongfang Liu, Manabu Torii, Guixian Xu, Zhangzhi Hu, Johannes Goll, Learning from Positive and Unlabeled Documents for Retrieval of Bacterial Protein-protein Interaction Literature, Proceedings of the 2009 Workshop of the BioLink Special Interest Group, International Conference on Linking Literature, Information, and Knowledge for Biology, June 28-29, 2009, Stockholm
  • 759. Bernhard Moser, Gernot Stübl, Jean-Luc Bouchot, On a Non-monotonicity Effect of Similarity Measures, Proceedings of the First International Conference on Similarity-based Pattern Recognition, September 28-30, 2011, Venice, Italy
  • 760. Emanuele Olivetti, Paolo Avesani, Supervised Segmentation of Fiber Tracts, Proceedings of the First International Conference on Similarity-based Pattern Recognition, September 28-30, 2011, Venice, Italy
  • 761. Francisco S. Melo, Manuel Lopes, Learning from Demonstration Using MDP Induced Metrics, Proceedings of the 2010 European Conference on Machine Learning and Knowledge Discovery in Databases: Part II, September 20-24, 2010, Barcelona, Spain
  • 762. Matthieu Solnon, Sylvain Arlot, Francis Bach, Multi-task Regression Using Minimal Penalties, The Journal of Machine Learning Research, v.13 n.1, p.2773-2812, January 2012
  • 763. Subhabrata Choudhury, Subhajyoti Ghosh, Arnab Bhattacharya, Kiran Jude Fernandes, Manoj Kumar Tiwari, A Real Time Clustering and SVM based Price-volatility Prediction for Optimal Trading Strategy, Neurocomputing, 131, p.419-426, May, 2014
  • 764. Zhixiang Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Cost-sensitive Tree of Classifiers, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
  • 765. Yan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu, Non-linear Cross-domain Collaborative Filtering via Hyper-structure Transfer, Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 06-11, 2015, Lille, France
  • 766. Xiang-Yang Wang, Xian-Jin Zhang, Hong-Ying Yang, Juan Bu, A Pixel-based Color Image Segmentation Using Support Vector Machine and Fuzzy C-means, Neural Networks, 33, p.148-159, September, 2012
  • 767. Chen Jing, Jian Hou, SVM and PCA based Fault Classification Approaches for Complicated Industrial Process, Neurocomputing, v.167 N.C, p.636-642, November 2015
  • 768. Yuhong Guo, Dale Schuurmans, Multi-label Classification with Output Kernels, Proceedings, Part II, of the European Conference on Machine Learning and Knowledge Discovery in Databases, September 23-27, 2013, Prague, Czech Republic
  • 769. Ryan Turner, Steven Bottone, Bhargav Avasarala, A Complete Variational Tracker, Proceedings of the 27th International Conference on Neural Information Processing Systems, p.496-504, December 08-13, 2014, Montreal, Canada
  • 770. Liang Sun, Betul Ceran, Jieping Ye, A Scalable Two-stage Approach for a Class of Dimensionality Reduction Techniques, Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 25-28, 2010, Washington, DC, USA
  • 771. Josip Djolonga, Andreas Krause, Volkan Cevher, High-dimensional Gaussian Process Bandits, Proceedings of the 26th International Conference on Neural Information Processing Systems, p.1025-1033, December 05-10, 2013, Lake Tahoe, Nevada
  • 772. Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffrey M. Voelker, Beyond Blacklists: Learning to Detect Malicious Web Sites from Suspicious URLs, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France
  • 773. Jun Zhu, Ning Chen, Eric P. Xing, Infinite SVM: A Dirichlet Process Mixture of Large-margin Kernel Machines, Proceedings of the 28th International Conference on International Conference on Machine Learning, p.617-624, June 28-July 02, 2011, Bellevue, Washington, USA
  • 774. Michael Fink, Shimon Ullman, From Aardvark to Zorro: A Benchmark for Mammal Image Classification, International Journal of Computer Vision, v.77 n.1-3, p.143-156, May 2008
  • 775. Eyke Hüllermeier, Klaus Brinker, Learning Valued Preference Structures for Solving Classification Problems, Fuzzy Sets and Systems, v.159 n.18, p.2337-2352, September, 2008
  • 776. Tsuneyoshi Ishii, Masamichi Ashihara, Shigeo Abe, Kernel Discriminant Analysis based Feature Selection, Neurocomputing, v.71 n.13-15, p.2544-2552, August, 2008
  • 777. Bhavani Raskutti, Adam Kowalczyk, Extreme Re-balancing for SVMs: A Case Study, ACM SIGKDD Explorations Newsletter, v.6 n.1, June 2004
  • 778. Abdulrahman Alenezi, Scott A. Moses, Theodore B. Trafalis, Real-time Prediction of Order Flowtimes Using Support Vector Regression, Computers and Operations Research, v.35 n.11, p.3489-3503, November, 2008
  • 779. Chunyuan Zhang, Qingxin Zhu, Xinzheng Niu, Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization, Computational Intelligence and Neuroscience, 2016, p.4, June 2016
  • 780. Ginés Rubio, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Design of Specific-to-problem Kernels and Use of Kernel Weighted K-nearest Neighbours for Time Series Modelling, Neurocomputing, v.73 n.10-12, p.1965-1975, June, 2010
  • 781. Zhiqiang Ge, Zhihuan Song, A Distribution-free Method for Process Monitoring, Expert Systems with Applications: An International Journal, v.38 n.8, p.9821-9829, August, 2011
  • 782. Murat Ekinci, Murat Aykut, Improved Gait Recognition by Multiple-projections Normalization, Machine Vision and Applications, v.21 n.2, p.143-161, February 2010
  • 783. Rob Fergus, Hector Bernal, Yair Weiss, Antonio Torralba, Semantic Label Sharing for Learning with Many Categories, Proceedings of the 11th European Conference on Computer Vision: Part I, September 05-11, 2010, Heraklion, Crete, Greece
  • 784. Cleriston Araujo Silva, Aristófanes Corrêa Silva, Stelmo Magalhães Netto, Anselmo Cardoso Paiva, Geraldo Braz Junior, Rodolfo Acatauassú Nunes, Lung Nodules Classification in CT Images Using Simpson's Index, Geometrical Measures and One-Class SVM, Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition, July 23-25, 2009, Leipzig, Germany
  • 785. Miriam Schmidt, Günther Palm, Friedhelm Schwenker, Spectral Graph Features for the Classification of Graphs and Graph Sequences, Computational Statistics, v.29 n.1-2, p.65-80, February 2014
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  • 788. Bartosz Krawczyk, Michał Woźniak, Combining Diverse One-class Classifiers, Proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, March 28-30, 2012, Salamanca, Spain
  • 789. P. Pankajakshan, V. Kumar, Detail-preserving Image Information Restoration Guided by SVM based Noise Mapping, Digital Signal Processing, v.17 n.3, p.561-577, May, 2007
  • 790. Fan Bu, Hang Li, Xiaoyan Zhu, String Re-writing Kernel, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers, July 08-14, 2012, Jeju Island, Korea
  • 791. Elham Parhizkar, Mahdi Abadi, BeeOWA, Neurocomputing, v.166 N.C, p.367-381, October 2015
  • 792. Jia Cai, Yi Tang, Jianjun Wang, Kernel Canonical Correlation Analysis via Gradient Descent, Neurocomputing, v.182 N.C, p.322-331, March 2016
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  • 794. Jongbin Ryu, Hyun S. Yang, Locality-preserving Descriptor for Robust Texture Feature Representation, Neurocomputing, v.214 N.C, p.729-738, November 2016
  • 795. Ming-Feng Tsai, Chuan-Ju Wang, Po-Chuan Chien, Discovering Finance Keywords via Continuous-Space Language Models, ACM Transactions on Management Information Systems (TMIS), v.7 n.3, p.1-17, October 2016
  • 796. Ahmed Kharrat, Karim Gasmi, Mohamed Ben Messaoud, Nacéra Benamrane, Mohamed Abid, Medical Image Classification Using An Optimal Feature Extraction Algorithm and a Supervised Classifier Technique, International Journal of Software Science and Computational Intelligence, v.3 n.2, p.19-33, April 2011
  • 797. Shian-Chang Huang, Yu-Cheng Tang, Chih-Wei Lee, Ming-Jen Chang, Kernel Local Fisher Discriminant Analysis based Manifold-regularized SVM Model for Financial Distress Predictions, Expert Systems with Applications: An International Journal, v.39 n.3, p.3855-3861, February, 2012
  • 798. Ouessai Asmaa, Keche Mokhtar, Ouamri Abdelaziz, Road Traffic Density Estimation Using Microscopic and Macroscopic Parameters, Image and Vision Computing, v.31 n.11, p.887-894, November, 2013
  • 799. Yifei Li, Chaoli Wang, Ching-Kuang Shene, Extracting Flow Features via Supervised Streamline Segmentation, Computers and Graphics, v.52 N.C, p.79-92, November 2015
  • 800. Sartra Wongthanavasu, Jetsada Ponkaew, A Cellular Automata-based Learning Method for Classification, Expert Systems with Applications: An International Journal, v.49 N.C, p.99-111, May 2016
  • 801. Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone, Preconditioning Kernel Matrices, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
  • 802. Muhammad Farooq, Ingo Steinwart, An SVM-like Approach for Expectile Regression, Computational Statistics & Data Analysis, v.109 N.C, p.159-181, May 2017
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  • 804. Siyuan Liu, Shuhui Wang, Feida Zhu, Jinbo Zhang, Ramayya Krishnan, HYDRA: Large-scale Social Identity Linkage via Heterogeneous Behavior Modeling, Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, June 22-27, 2014, Snowbird, Utah, USA
  • 805. Eyke Hüllermeier, Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization, International Journal of Approximate Reasoning, v.55 n.7, p.1519-1534, October, 2014
  • 806. Mario Frank, Fred A. Hamprecht, Image-based Supervision of a Periodically Working Machine, Pattern Analysis & Applications, v.16 n.3, p.407-416, August 2013
  • 807. Wenye Li, Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach, Proceedings of the 28th International Conference on Neural Information Processing Systems, p.2620-2628, December 07-12, 2015, Montreal, Canada
  • 808. Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou, Multiple Kernel Learning from Noisy Labels by Stochastic Programming, Proceedings of the 29th International Coference on International Conference on Machine Learning, p.123-130, June 26-July 01, 2012, Edinburgh, Scotland
  • 809. Jesse Alama, Tom Heskes, Daniel Kühlwein, Evgeni Tsivtsivadze, Josef Urban, Premise Selection for Mathematics by Corpus Analysis and Kernel Methods, Journal of Automated Reasoning, v.52 n.2, p.191-213, February 2014
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  • 811. Yeyong Pang, Shaojun Wang, Yu Peng, Xiyuan Peng, Nicholas J. Fraser, Philip H. W. Leong, A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology, ACM Transactions on Reconfigurable Technology and Systems (TRETS), v.10 n.1, p.1-22, December 2016
  • 812. Ming-Der Yang, Tung-Ching Su, Automated Diagnosis of Sewer Pipe Defects based on Machine Learning Approaches, Expert Systems with Applications: An International Journal, v.35 n.3, p.1327-1337, October, 2008
  • 813. Chin-Chun Chang, Tzung-Ying Lin, Linear Feature Extraction by Integrating Pairwise and Global Discriminatory Information via Sequential Forward Floating Selection and Kernel QR Factorization with Column Pivoting, Pattern Recognition, v.41 n.4, p.1373-1383, April, 2008
  • 814. Jingneng Liu, Guihua Zeng, Jianping Fan, Fast Local Self-Similarity for Describing Interest Regions, Pattern Recognition Letters, v.33 n.9, p.1224-1235, July, 2012
  • 815. Roland Kwitt, Nuno Vasconcelos, Nikhil Rasiwasia, Scene Recognition on the Semantic Manifold, Proceedings of the 12th European Conference on Computer Vision, October 07-13, 2012, Florence, Italy
  • 816. Holger Franken, Alexander Seitz, Rainer Lehmann, Hans-Ulrich Häring, Norbert Stefan, Andreas Zell, Inferring Disease-related Metabolite Dependencies with a Bayesian Optimization Algorithm, Proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, April 11-13, 2012, Málaga, Spain
  • 817. Changxin Gao, Nong Sang, Qiling Tang, On Selection and Combination of Weak Learners in AdaBoost, Pattern Recognition Letters, v.31 n.9, p.991-1001, July, 2010
  • 818. Till Rumpf, Christoph Römer, Martin Weis, Markus Sökefeld, Roland Gerhards, Lutz Plümer, Sequential Support Vector Machine Classification for Small-grain Weed Species Discrimination with Special Regard to Cirsium Arvense and Galium Aparine, Computers and Electronics in Agriculture, 80, p.89-96, January, 2012
  • 819. Turgay Celik, Tardi Tjahjadi, Multiscale Texture Classification Using Dual-tree Complex Wavelet Transform, Pattern Recognition Letters, v.30 n.3, p.331-339, February, 2009
  • 820. M. Fatih Akay, Ipek Abasıkeleş, Predicting the Performance Measures of An Optical Distributed Shared Memory Multiprocessor by Using Support Vector Regression, Expert Systems with Applications: An International Journal, v.37 n.9, p.6293-6301, September, 2010
  • 821. Xiaoyang Tan, Bill Triggs, Fusing Gabor and LBP Feature Sets for Kernel-based Face Recognition, Proceedings of the 3rd International Conference on Analysis and Modeling of Faces and Gestures, October 20, 2007, Rio De Janeiro, Brazil
  • 822. Vladimir Norkin, Michiel Keyzer, On Stochastic Optimization and Statistical Learning in Reproducing Kernel Hilbert Spaces by Support Vector Machines (SVM), Informatica, v.20 n.2, p.273-292, April 2009
  • 823. Jong Kyoung Kim, Sung-Yang Bang, Seungjin Choi, Sequence-driven Features for Prediction of Subcellular Localization of Proteins, Pattern Recognition, v.39 n.12, p.2301-2311, December, 2006
  • 824. Estevão Esmi, Peter Sussner, Marcos Eduardo Valle, Fábio Sakuray, Laécio Barros, Fuzzy Associative Memories based on Subsethood and Similarity Measures with Applications to Speaker Identification, Proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, March 28-30, 2012, Salamanca, Spain
  • 825. Maria-Florina Balcan, Avrim Blum, Santosh Vempala, Kernels As Features: On Kernels, Margins, and Low-dimensional Mappings, Machine Learning, v.65 n.1, p.79-94, October 2006
  • 826. Rong Jin, Steven C. H. Hoi, Tianbao Yang, Online Multiple Kernel Learning: Algorithms and Mistake Bounds, Proceedings of the 21st International Conference on Algorithmic Learning Theory, October 06-08, 2010, Canberra, Australia
  • 827. GramSchmidt Process based Incremental Extreme Learning Machine, Neurocomputing, v.241 N.C, p.1-17, June 2017
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  • 830. Erik Zawadzki, Sebastien Lahaie, Nonparametric Scoring Rules, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, p.3635-3641, January 25-30, 2015, Austin, Texas
  • 831. Jacob R. Gardner, Matt J. Kusner, Zhixiang Xu, Kilian Q. Weinberger, John P. Cunningham, Bayesian Optimization with Inequality Constraints, Proceedings of the 31st International Conference on International Conference on Machine Learning, June 21-26, 2014, Beijing, China
  • 832. Wen Chan, Jintao Du, Weidong Yang, Jinhui Tang, Xiangdong Zhou, Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification, Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, November 03-07, 2014, Shanghai, China
  • 833. Marco Cuturi, Jean-Philippe Vert, 2005 Special Issue: The Context-tree Kernel for Strings, Neural Networks, v.18 n.8, p.1111-1123, October 2005
  • 834. Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz, Training Computationally Efficient Smartphone—Based Human Activity Recognition Models, Proceedings of the 23rd International Conference on Artificial Neural Networks and Machine Learning — ICANN 2013, September 10-13, 2013
  • 835. P. Mahesha, D. S. Vinod, Support Vector Machine-based Stuttering Dysfluency Classification Using GMM Supervectors, International Journal of Grid and Utility Computing, v.6 n.3/4, p.143-149, July 2015
  • 836. Holger Wendland, Christian Rieger, Approximate Interpolation with Applications to Selecting Smoothing Parameters, Numerische Mathematik, v.101 n.4, p.729-748, October 2005
  • 837. Daniel M. M. Da Costa, Henrique Passos, Sarajane Marques Peres, Clodoaldo A. M. De Lima, A Comparative Study of Feature Level Fusion Strategies for Multimodal Biometric Systems based on Face and Iris, Proceedings of the Annual Conference on Brazilian Symposium on Information Systems: Information Systems: A Computer Socio-Technical Perspective, May 26-29, 2015, Goiania, Goias, Brazil
  • 838. Nicolas Couellan, Sophie Jan, Tom Jorquera, Jean-Pierre Georgé, Self-adaptive Support Vector Machine, Expert Systems with Applications: An International Journal, v.42 n.9, p.4284-4298, June 2015
  • 839. Bin Gu, Victor S. Sheng, Zhijie Wang, Derek Ho, Said Osman, Shuo Li, Incremental Learning for Ν -Support Vector Regression, Neural Networks, v.67 N.C, p.140-150, July 2015
  • 840. Ju-Jie Zhang, Min Fang, Hongchun Wang, Xiao Li, Dependence Maximization based Label Space Dimension Reduction for Multi-label Classification, Engineering Applications of Artificial Intelligence, v.45 N.C, p.453-463, October 2015
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  • 842. Arash Afkanpour, András György, Csaba Szepesvári, Michael Bowling, A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
  • 843. Philipp Rapp, Martin Mesch, Harald Giessen, Cristina Tarín, Regression Methods for Ophthalmic Glucose Sensing Using Metamaterials, Journal of Electrical and Computer Engineering, 2011, p.5-5, January 2011
  • 844. Truc-Vien T. Nguyen, Alessandro Moschitti, Giuseppe Riccardi, Kernel-based Reranking for Named-entity Extraction, Proceedings of the 23rd International Conference on Computational Linguistics: Posters, p.901-909, August 23-27, 2010, Beijing, China
  • 845. Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz, Alberto Suárez, Non-linear Causal Inference Using Gaussianity Measures, The Journal of Machine Learning Research, v.17 n.1, p.939-977, January 2016
  • 846. Lei Yang, Shaogao Lv, Junhui Wang, Model-free Variable Selection in Reproducing Kernel Hilbert Space, The Journal of Machine Learning Research, v.17 n.1, p.2885-2908, January 2016
  • 847. Haizhang Zhang, Yuesheng Xu, Qinghui Zhang, Refinement of Operator-valued Reproducing Kernels, The Journal of Machine Learning Research, v.13 n.1, p.91-136, January 2012
  • 848. Amar Khoukhi, Hybrid Soft Computing Systems for Reservoir PVT Properties Prediction, Computers & Geosciences, 44, p.109-119, July, 2012
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  • 855. Geraldo Braz Junior, Anselmo Cardoso De Paiva, Aristófanes Corrêa Silva, Alexandre Cesar Muniz De Oliveira, Classification of Breast Tissues Using Moran's Index and Geary's Coefficient As Texture Signatures and SVM, Computers in Biology and Medicine, v.39 n.12, p.1063-1072, December, 2009
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  • 869. Eduard Gabriel Băzăvan, Fuxin Li, Cristian Sminchisescu, Fourier Kernel Learning, Proceedings of the 12th European Conference on Computer Vision, October 07-13, 2012, Florence, Italy
  • 870. Kuo-Ching Ying, Shih-Wei Lin, Zne-Jung Lee, Yen-Tim Lin, An Ensemble Approach Applied to Classify Spam E-mails, Expert Systems with Applications: An International Journal, v.37 n.3, p.2197-2201, March, 2010
  • 871. Chong Zhang, Chongxun Zheng, Xiaolin Yu, Yi Ouyang, Estimating VDT Mental Fatigue Using Multichannel Linear Descriptors and KPCA-HMM, EURASIP Journal on Advances in Signal Processing, 2008, p.1-11, January 2008
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  • 873. Kar-Ann Toh, Youngsung Kim, Sangyoun Lee, Jaihie Kim, Fusion of Visual and Infra-red Face Scores by Weighted Power Series, Pattern Recognition Letters, v.29 n.5, p.603-615, April, 2008
  • 874. Pengfei Zhu, Qinghua Hu, Rule Extraction from Support Vector Machines based on Consistent Region Covering Reduction, Knowledge-Based Systems, 42, p.1-8, April, 2013
  • 875. Shan-Hung Wu, Keng-Pei Lin, Chung-Min Chen, Ming-Syan Chen, Asymmetric Support Vector Machines: Low False-positive Learning under the User Tolerance, Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2008, Las Vegas, Nevada, USA
  • 876. Fernando Soares Sérvulo De Oliveira, Antonio Oseas De Carvalho Filho, Aristófanes Corrêa Silva, Anselmo Cardoso De Paiva, Marcelo Gattass, Classification of Breast Regions As Mass and Non-mass based on Digital Mammograms Using Taxonomic Indexes and SVM, Computers in Biology and Medicine, v.57 N.C, p.42-53, February 2015
  • 877. Shuyuan Yang, Min Wang, Li Jin, Shigang Wang, Fang Liu, Licheng Jiao, Learning Compressive Sampling via Multiscale and Steerable Support Value Transform, Knowledge-Based Systems, v.82 N.C, p.128-138, July 2015
  • 878. Daniel T. H. Lai, Pazit Levinger, Rezaul K. Begg, Wendy Lynne Gilleard, Marimuthu Palaniswami, Automatic Recognition of Gait Patterns Exhibiting Patellofemoral Pain Syndrome Using a Support Vector Machine Approach, IEEE Transactions on Information Technology in Biomedicine, v.13 n.5, p.810-817, September 2009
  • 879. Ting Liu, Xiao Ding, Yiheng Chen, Haochen Chen, Maosheng Guo, Predicting Movie Box-office Revenues by Exploiting Large-scale Social Media Content, Multimedia Tools and Applications, v.75 n.3, p.1509-1528, February 2016
  • 880. Yajuan Cai, Guoqiang Zhong, Yuchen Zheng, Kaizhu Huang, Junyu Dong, Is DeCAF Good Enough for Accurate Image Classification?, Proceeings, Part II, of the 22nd International Conference on Neural Information Processing, p.354-363, November 09-12, 2015, Istanbul, Turkey
  • 881. Ang Li, Zhenjiang Miao, Yigang Cen, Tian Wang, Viacheslav Voronin, Histogram of Maximal Optical Flow Projection for Abnormal Events Detection in Crowded Scenes, International Journal of Distributed Sensor Networks, 2015, p.3-3, January 2015
  • 882. Matthias Feurer, Jost Tobias Springenberg, Frank Hutter, Using Meta-learning to Initialize Bayesian Optimization of Hyperparameters, Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection, September 19, 2014, Prague, Czech Republic
  • 883. Hachem Kadri, Alain Rakotomamonjy, Francis Bach, Philippe Preux, Multiple Operator-valued Kernel Learning, Proceedings of the 25th International Conference on Neural Information Processing Systems, p.2429-2437, December 03-06, 2012, Lake Tahoe, Nevada
  • 884. Pietro Cottone, Salvatore Gaglio, Giuseppe Lo Re, Marco Ortolani, A Machine Learning Approach for User Localization Exploiting Connectivity Data, Engineering Applications of Artificial Intelligence, v.50 N.C, p.125-134, April 2016
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  • 890. Vladimir I. Norkin, Michiel A. Keyzer, On Convergence of Kernel Learning Estimators, SIAM Journal on Optimization, v.20 n.3, p.1205-1223, August 2009
  • 891. Yutaka I. Leon-Suematsu, Kentaro Inui, Sadao Kurohashi, Yutaka Kidawara, Web Spam Detection by Exploring Densely Connected Subgraphs, Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, p.124-129, August 22-27, 2011
  • 892. Takumi Kobayashi, Kernel-based Transition Probability Toward Similarity Measure for Semi-supervised Learning, Pattern Recognition, v.47 n.5, p.1994-2010, May, 2014
  • 893. Gabriel Gómez Sena, Pablo Belzarena, Statistical Traffic Classification by Boosting Support Vector Machines, Proceedings of the 7th Latin American Networking Conference, October 04-05, 2012, Medellín, Columbia
  • 894. Santiago D. Villalba, Pádraig Cunningham, An Evaluation of Dimension Reduction Techniques for One-class Classification, Artificial Intelligence Review, v.27 n.4, p.273-294, April 2007
  • 895. Yuichi Takano, Jun-Ya Gotoh, Multi-period Portfolio Selection Using Kernel-based Control Policy with Dimensionality Reduction, Expert Systems with Applications: An International Journal, v.41 n.8, p.3901-3914, June, 2014
  • 896. Ying Zhao, Justin Zobel, Searching with Style: Authorship Attribution in Classic Literature, Proceedings of the Thirtieth Australasian Conference on Computer Science, p.59-68, January 30-February 02, 2007, Ballarat, Victoria, Australia
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  • 899. Truc-Vien T. Nguyen, Alessandro Moschitti, Giuseppe Riccardi, Convolution Kernels on Constituent, Dependency and Sequential Structures for Relation Extraction, Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3, August 06-07, 2009, Singapore
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  • 904. Kirthevasan Kandasamy, Yaoliang Yu, Additive Approximations in High Dimensional Nonparametric Regression via the SALSA, Proceedings of the 33rd International Conference on International Conference on Machine Learning, June 19-24, 2016, New York, NY, USA
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  • 908. Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan, Ali Oran, Patrick Jaillet, John Dolan, Gaurav Sukhatme, Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena, Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, August 14-18, 2012, Catalina Island, CA
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  • 910. Longhua Qian, Guodong Zhou, Qiaoming Zhu, Employing Constituent Dependency Information for Tree Kernel-Based Semantic Relation Extraction Between Named Entities, ACM Transactions on Asian Language Information Processing (TALIP), v.10 n.3, p.1-24, September 2011
  • 911. D. Sculley, Robert G. Malkin, Sugato Basu, Roberto J. Bayardo, Predicting Bounce Rates in Sponsored Search Advertisements, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 01, 2009, Paris, France
  • 912. Gang Wang, Zhicheng Wang, Yufei Chen, Xianhui Liu, Yingchun Ren, Lei Peng, Learning Coherent Vector Fields for Robust Point Matching under Manifold Regularization, Neurocomputing, v.216 N.C, p.393-401, December 2016
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  • 915. H. -S. Park, Y. -D. Chung, S. -K. Oh, W. Pedrycz, H. -K. Kim, Design of Information Granule-oriented RBF Neural Networks and Its Application to Power Supply for High-field Magnet, Engineering Applications of Artificial Intelligence, v.24 n.3, p.543-554, April, 2011
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  • 919. Tobias Petri, Robert Küffner, Ralf Zimmer, Experiment Specific Expression Patterns, Proceedings of the 15th Annual International Conference on Research in Computational Molecular Biology, p.339-354, March 28-31, 2011, Vancouver, BC, Canada
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  • 925. S. Monira Sumi, M. Faisal Zaman, Hideo Hirose, A Rainfall Forecasting Method Using Machine Learning Models and Its Application to the Fukuoka City Case, International Journal of Applied Mathematics and Computer Science, v.22 n.4, p.841-854, 12 2012
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  • 955. Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye, Multisource Domain Adaptation and Its Application to Early Detection of Fatigue, ACM Transactions on Knowledge Discovery from Data (TKDD), v.6 n.4, p.1-26, December 2012
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  • 957. Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause, Streaming Submodular Maximization: Massive Data Summarization on the Fly, Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2014, New York, New York, USA
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  • 961. Fredrik D. Johansson, Devdatt Dubhashi, Learning with Similarity Functions on Graphs Using Matchings of Geometric Embeddings, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 10-13, 2015, Sydney, NSW, Australia
  • 962. Khuong An Nguyen, Zhiyuan Luo, Reliable Indoor Location Prediction Using Conformal Prediction, Annals of Mathematics and Artificial Intelligence, v.74 n.1-2, p.133-153, June 2015
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  • 964. Rami N. Khushaba, Sarath Kodagoda, Sara Lal, Gamini Dissanayake, Uncorrelated Fuzzy Neighborhood Preserving Analysis based Feature Projection for Driver Drowsiness Recognition, Fuzzy Sets and Systems, 221, p.90-111, June, 2013
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  • 966. Jalal Shiri, Ozgur Kisi, Heesung Yoon, Kang-Kun Lee, Amir Hossein Nazemi, Predicting Groundwater Level Fluctuations with Meteorological Effect Implications-A Comparative Study Among Soft Computing Techniques, Computers & Geosciences, v.56 N.C, p.32-44, July 2013
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  • 968. Tansu Alpcan, A Framework for Optimization under Limited Information, Journal of Global Optimization, v.55 n.3, p.681-706, March 2013
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  • 1087. Nick J. Pizzi, Fuzzy Quartile Encoding As a Preprocessing Method for Biomedical Pattern Classification, Theoretical Computer Science, v.412 n.42, p.5909-5925, September, 2011
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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2001 LearningWithKernelsBernhard Schölkopf
Alexander J. Smola
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
AuthorBernhard Schölkopf + and Alexander J. Smola +
titleLearning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond +