• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 45 matches

• 2024
• 
  Lingli Cui, Zhichao Jiang, Dongdong Liu, Huaqing Wang:
  A novel adaptive generalized domain data fusion-driven kernel sparse representation classification method for intelligent bearing fault diagnosis. Expert Syst. Appl. 247: 123225 (2024)
• 
  Paolo Didier Alfano, Vito Paolo Pastore, Lorenzo Rosasco, Francesca Odone:
  Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods. Image Vis. Comput. 142: 104894 (2024)
• 2023
• 
  Changzhi Su, Li Zhang, Lei Zhao:
  Online local fisher risk minimization: a new online kernel method for online classification. Appl. Intell. 53(14): 17662-17678 (2023)
• 
  Prasenjit Dhar, K. Suganya Devi, P. Srinivasan:
  CNN-RSVM: a hybrid approach for classification of poikilocytosis using convolutional neural network and radial kernel basis support vector machine. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(6): 2118-2129 (2023)
• 
  Li Liu, Haocheng Sun, Fanzhang Li:
  A Lie group kernel learning method for medical image classification. Pattern Recognit. 142: 109735 (2023)
• 
  Ines Moudjari, Caroline Pautard, Clément Jouanneau, Régine Le Bouquin Jeannes:
  On the Use of Kernel Fisher Discriminant Analysis as a Reduction Method for the Classification of EMG Signals. EUSIPCO 2023: 1125-1129
• 2020
• 
  Chandan Gautam, Pratik K. Mishra, Aruna Tiwari, Bharat Richhariya, Hari Mohan Pandey, Shuihua Wang, Muhammad Tanveer:
  Minimum variance-embedded deep kernel regularized least squares method for one-class classification and its applications to biomedical data. Neural Networks 123: 191-216 (2020)
• 2019
• 
  Farzaneh Elahifasaee, Fan Li, Ming Yang:
  A Classification Algorithm by Combination of Feature Decomposition and Kernel Discriminant Analysis (KDA) for Automatic MR Brain Image Classification and AD Diagnosis. Comput. Math. Methods Medicine 2019: 1437123:1-1437123:14 (2019)
• 
  Yue Ma, Xinyu Wu, Can Wang, Zhengkun Yi, Guoyuan Liang:
  Gait Phase Classification and Assist Torque Prediction for a Lower Limb Exoskeleton System Using Kernel Recursive Least-Squares Method. Sensors 19(24): 5449 (2019)
• 
  Boxiang Wang, Hui Zou:
  A Multicategory Kernel Distance Weighted Discrimination Method for Multiclass Classification. Technometrics 61(3): 396-408 (2019)
• 2018
• 
  André M. Carrington:
  Kernel Methods and Measures for Classification with Transparency, Interpretability and Accuracy in Health Care. University of Waterloo, Ontario, Canada, 2018
• 
  Mourtadha Badiane, Martin O'Reilly, Padraig Cunningham:
  Kernel Methods for Time Series Classification and Regression. AICS 2018: 54-65
• 
  Chen Zhao, Kaicheng Li, Xuebin Xu:
  A Method Based on S-transform and Hybrid Kernel Extreme Learning Machine for Complex Power Quality Disturbances Classification. ELM 2018: 303-318
• 
  Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
  A Weighted Kernel-Based Hierarchical Classification Method for Zoning of Sensors in Indoor Wireless Networks. SPAWC 2018: 1-5
• 
  Li Zeng, Zhaolong Yu, Hongyu Zhao:
  A pathway-based kernel boosting method for sample classification using genomic data. CoRR abs/1803.03910 (2018)
• 2017
• 
  Chengming Qi, Lishuan Hu, Xin Yu:
  A framework of multiple kernel ensemble learning for classification using two-stage feature selection method. J. Intell. Fuzzy Syst. 33(5): 2737-2747 (2017)
• 
  Tiejun Cao:
  A Combined Dimensional Kernel Method for Graph Classification. J. Inf. Technol. Res. 10(3): 22-33 (2017)
• 2016
• 
  Pan Li, Yang Liu, GuoJun Liu, Maozu Guo, Zhiyong Pan:
  A robust local sparse coding method for image classification with Histogram Intersection Kernel. Neurocomputing 184: 36-42 (2016)
• 
  Yi Wang, Yan Zhang, Haiwei Song:
  A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images. Remote. Sens. 8(11): 919 (2016)
• 2015
• 
  José María Lillo-Castellano, Inmaculada Mora-Jiménez, Rafael Moreno-González, María Monserrat-García-de-Pablo, Arcadi García-Alberola, José Luis Rojo-Álvarez:
  Big-Data Analytics for Arrhythmia Classification using Data Compression and Kernel Methods. CinC 2015: 661-664
• 
  Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo:
  A nonlinear feature selection method based on kernel separability measure for hyperspectral image classification. IGARSS 2015: 461-464
• 
  Huan Liu, Tianzhu Liu, Yanfeng Gu:
  A novel multiple kernel boosting method for hyperspectral image classification. IGARSS 2015: 1714-1716
• 
  Adnan Shakoor, Qinke Peng, Shiquan Sun, Xiao Wang, Jia Lv:
  GT-kernelPLS: Game theory based hybrid gene selection method for microarray data classification. SNPD 2015: 205-210
• 2014
• 
  Aditya Tayal:
  Effective and Efficient Optimization Methods for Kernel Based Classification Problems. University of Waterloo, Ontario, Canada, 2014
• 
  Nannan Gu, Di Wang, Mingyu Fan, Deyu Meng:
  A kernel-based sparsity preserving method for semi-supervised classification. Neurocomputing 139: 345-356 (2014)
• 
  Bor-Chen Kuo, Hsin-Hua Ho, Cheng-Hsuan Li, Chih-Cheng Hung, Jin-Shiuh Taur:
  A Kernel-Based Feature Selection Method for SVM With RBF Kernel for Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(1): 317-326 (2014)
• 
  Yusuke Sato, Kazuyuki Narisawa, Ayumi Shinohara:
  A Simple Classification Method for Class Imbalanced Data using the Kernel Mean. KDIR 2014: 327-334
• 
  Pei-Jyun Hsieh, Cheng-Hsuan Li, Kai-Ching Chen, Bor-Chen Kuo:
  A kernel-based feature extraction method for hyperspectral image classification. IGARSS 2014: 513-516
• 
  Sidney M. L. de Lima, Abel G. Silva-Filho, Wellington Pinheiro dos Santos:
  A methodology for classification of lesions in mammographies using Zernike Moments, ELM and SVM Neural Networks in a multi-kernel approach. SMC 2014: 988-991
• 2013
• 
  Yanfeng Gu, Kai Feng, Hong Wang:
  A new sparse multiple-kernel learning method for classification of hyperspectral imagery. WHISPERS 2013: 1-4

skipping 15 more matches