Robust low-rank multiple kernel learning with compound regularization
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Robust low-rank multiple kernel learning with compound regularization
Authors
Keywords
Analytics, Robust estimation, Sparse learning, Multiple kernel learning, Compound regularization
Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2020-12-25
DOI
10.1016/j.ejor.2020.12.024
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Approximate multiple kernel learning with least-angle regression
- (2019) Martin Stražar et al. NEUROCOMPUTING
- Improved fixed-rank Nyström approximation via QR decomposition: Practical and theoretical aspects
- (2019) Farhad Pourkamali-Anaraki et al. NEUROCOMPUTING
- Robust support vector machine with generalized quantile loss for classification and regression
- (2019) Liming Yang et al. APPLIED SOFT COMPUTING
- Temporal hierarchies with autocorrelation for load forecasting
- (2019) Peter Nystrup et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Particle-swarm optimization of ensemble neural networks with negative correlation learning for forecasting short-term wind speed of wind farms in western China
- (2019) Tao Ma et al. INFORMATION SCIENCES
- The impact of special days in call arrivals forecasting: A neural network approach to modelling special days
- (2018) Devon Barrow et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- High dimensional data classification and feature selection using support vector machines
- (2018) Bissan Ghaddar et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Two-Stage Fuzzy Multiple Kernel Learning Based on Hilbert-Schmidt Independence Criterion
- (2018) Tinghua Wang et al. IEEE TRANSACTIONS ON FUZZY SYSTEMS
- Prediction interval forecasting of wind speed and wind power using modes decomposition based low rank multi-kernel ridge regression
- (2018) Jyotirmayee Naik et al. RENEWABLE ENERGY
- Functional-bandwidth kernel for Support Vector Machine with Functional Data: An alternating optimization algorithm
- (2018) R. Blanquero et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- A novel approach for forecasting global horizontal irradiance based on sparse quadratic RBF neural network
- (2017) He Jiang ENERGY CONVERSION AND MANAGEMENT
- ADMM for High-Dimensional Sparse Penalized Quantile Regression
- (2017) Yuwen Gu et al. TECHNOMETRICS
- Weighted quantile regression via support vector machine
- (2015) Qifa Xu et al. EXPERT SYSTEMS WITH APPLICATIONS
- Variable selection for support vector machines in moderately high dimensions
- (2015) Xiang Zhang et al. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
- EasyMKL: a scalable multiple kernel learning algorithm
- (2015) Fabio Aiolli et al. NEUROCOMPUTING
- Adaptive robust variable selection
- (2014) Jianqing Fan et al. ANNALS OF STATISTICS
- Short-term load forecasting using a kernel-based support vector regression combination model
- (2014) JinXing Che et al. APPLIED ENERGY
- Multiple Kernel Learning for Visual Object Recognition: A Review
- (2014) IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- ℓp-norm multiple kernel learning with low-rank kernels
- (2014) Alain Rakotomamonjy et al. NEUROCOMPUTING
- Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates
- (2013) Shangkun Deng et al. Computational Economics
- Interquantile shrinkage and variable selection in quantile regression
- (2013) Liewen Jiang et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
- Applying multiple kernel learning and support vector machine for solving the multicriteria and nonlinearity problems of traffic flow prediction
- (2012) Chenyun Yu et al. JOURNAL OF ADVANCED TRANSPORTATION
- A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems
- (2012) Cun-Hui Zhang et al. STATISTICAL SCIENCE
- Nearly unbiased variable selection under minimax concave penalty
- (2010) Cun-Hui Zhang ANNALS OF STATISTICS
- Learning intransitive reciprocal relations with kernel methods
- (2010) Tapio Pahikkala et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- A multiple-kernel support vector regression approach for stock market price forecasting
- (2010) Chi-Yuan Yeh et al. EXPERT SYSTEMS WITH APPLICATIONS
- Simultaneous analysis of Lasso and Dantzig selector
- (2009) Peter J. Bickel et al. ANNALS OF STATISTICS
- Extended Bayesian information criteria for model selection with large model spaces
- (2008) J. Chen et al. BIOMETRIKA
- L1-Norm Quantile Regression
- (2008) Youjuan Li et al. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
- Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
- (2008) Karim Lounici Electronic Journal of Statistics
- MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
- (2007) Zhe Wang et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search