MKEL: Multiple Kernel Ensemble Learning via Unified Ensemble Loss for Image Classification
暂无分享,去创建一个
Zhengjun Zha | Sumet Mehta | Jianping Fan | Xiangjun Shen | Kou Lu | Jianming Zhang | Weifeng Liu | Zhengjun Zha | Xiang-jun Shen | Weifeng Liu | Sumet Mehta | Jianping Fan | Jianming Zhang | K. Lu
[1] Jian Yang,et al. Selective Kernel Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Masashi Sugiyama,et al. Dual-Augmented Lagrangian Method for Efficient Sparse Reconstruction , 2009, IEEE Signal Processing Letters.
[3] Fabio Aiolli,et al. EasyMKL: a scalable multiple kernel learning algorithm , 2015, Neurocomputing.
[4] Zheng-Jun Zha,et al. SLiKER: Sparse loss induced kernel ensemble regression , 2021, Pattern Recognit..
[5] Lei Guo,et al. When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[6] Jon Atli Benediktsson,et al. Nonlinear Multiple Kernel Learning With Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[7] Taiji Suzuki,et al. SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels , 2011, Machine Learning.
[8] Qionghai Dai,et al. Explaining the Genetic Causality for Complex Phenotype via Deep Association Kernel Learning , 2020, Patterns.
[9] Zheng-Jun Zha,et al. Robust Deep Co-Saliency Detection With Group Semantic and Pyramid Attention , 2020, IEEE Transactions on Neural Networks and Learning Systems.
[10] Xiaoqiang Lu,et al. Remote Sensing Image Scene Classification: Benchmark and State of the Art , 2017, Proceedings of the IEEE.
[11] Patrick J. F. Groenen,et al. GenSVM: A Generalized Multiclass Support Vector Machine , 2016, J. Mach. Learn. Res..
[12] John Shawe-Taylor,et al. A Note on Improved Loss Bounds for Multiple Kernel Learning , 2011, ArXiv.
[13] Tat-Seng Chua,et al. Mining Travel Patterns from GPS-Tagged Photos , 2011, MMM.
[14] Xuelong Li,et al. Scene Classification With Recurrent Attention of VHR Remote Sensing Images , 2019, IEEE Transactions on Geoscience and Remote Sensing.
[15] Michael I. Jordan,et al. Computing regularization paths for learning multiple kernels , 2004, NIPS.
[16] Alexander Binder,et al. Theory and Algorithms for the Localized Setting of Learning Kernels , 2015, FE@NIPS.
[17] Shyam Visweswaran,et al. Deep Multiple Kernel Learning , 2013, 2013 12th International Conference on Machine Learning and Applications.
[18] Xuelong Li,et al. Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification , 2019, IEEE Transactions on Geoscience and Remote Sensing.
[19] Dustin Boswell,et al. Introduction to Support Vector Machines , 2002 .
[20] Mikhail Belkin,et al. Laplacian Support Vector Machines Trained in the Primal , 2009, J. Mach. Learn. Res..
[21] Yixin Yang,et al. Localized Multiple Kernel Learning With Dynamical Clustering and Matrix Regularization , 2018, IEEE Transactions on Neural Networks and Learning Systems.
[22] Lei Zhang,et al. Higher-Order Integration of Hierarchical Convolutional Activations for Fine-Grained Visual Categorization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[23] S. V. N. Vishwanathan,et al. SPF-GMKL: generalized multiple kernel learning with a million kernels , 2012, KDD.
[24] Hao Wang,et al. Multi-scale structural kernel representation for object detection , 2021, Pattern Recognit..
[25] Hongwei Sun,et al. Mercer theorem for RKHS on noncompact sets , 2005, J. Complex..
[26] Jie Xu,et al. Multi-Class Support Vector Machine via Maximizing Multi-Class Margins , 2017, IJCAI.
[27] Ethem Alpaydin,et al. Multiple Kernel Learning Algorithms , 2011, J. Mach. Learn. Res..
[28] Claudio Gallicchio,et al. Enhancing deep neural networks via multiple kernel learning , 2020, Pattern Recognit..
[29] Ivor W. Tsang,et al. Two-Layer Multiple Kernel Learning , 2011, AISTATS.
[30] Sebastian Nowozin,et al. On feature combination for multiclass object classification , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[31] Li Bai,et al. Cosine Similarity Metric Learning for Face Verification , 2010, ACCV.
[32] Jianping Fan,et al. A generalized least-squares approach regularized with graph embedding for dimensionality reduction , 2020, Pattern Recognit..
[33] Michael I. Jordan,et al. Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.
[34] Ganesh Ramakrishnan,et al. Efficient Rule Ensemble Learning using Hierarchical Kernels , 2011, ICML.
[35] Alexander J. Smola,et al. Guest editorial: model selection and optimization in machine learning , 2011, Machine Learning.
[36] Yixin Yang,et al. Matrix-Regularized Multiple Kernel Learning via $(r,~p)$ Norms , 2018, IEEE Transactions on Neural Networks and Learning Systems.
[37] Manik Varma,et al. More generality in efficient multiple kernel learning , 2009, ICML '09.
[38] Tri Dao,et al. A Kernel Theory of Modern Data Augmentation , 2018, ICML.
[39] Yujian Li,et al. Deep neural mapping support vector machines , 2017, Neural Networks.
[40] Xiao-Yuan Jing,et al. Heterogeneous Defect Prediction Through Multiple Kernel Learning and Ensemble Learning , 2017, 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME).
[41] Gunnar Rätsch,et al. Large Scale Multiple Kernel Learning , 2006, J. Mach. Learn. Res..
[42] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[43] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[44] Steven C. H. Hoi,et al. MKBoost: A Framework of Multiple Kernel Boosting , 2013, IEEE Trans. Knowl. Data Eng..
[45] Andrew Gordon Wilson,et al. Deep Kernel Learning , 2015, AISTATS.
[46] Hao Wang,et al. Multi-scale Location-Aware Kernel Representation for Object Detection , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[47] Yang Yang,et al. Robust (Semi) Nonnegative Graph Embedding , 2014, IEEE Transactions on Image Processing.
[48] Yves Grandvalet,et al. More efficiency in multiple kernel learning , 2007, ICML '07.
[49] Peter L. Bartlett,et al. A Unifying View of Multiple Kernel Learning , 2010, ECML/PKDD.
[50] John Shawe-Taylor,et al. Improved Loss Bounds For Multiple Kernel Learning , 2011, AISTATS.
[51] Koby Crammer,et al. Kernel Design Using Boosting , 2002, NIPS.
[52] Fang Liu,et al. Selective multiple kernel learning for classification with ensemble strategy , 2013, Pattern Recognit..
[53] Klaus-Robert Müller,et al. Efficient and Accurate Lp-Norm Multiple Kernel Learning , 2009, NIPS.
[54] Francis R. Bach,et al. Consistency of the group Lasso and multiple kernel learning , 2007, J. Mach. Learn. Res..
[55] Alexander Zien,et al. lp-Norm Multiple Kernel Learning , 2011, J. Mach. Learn. Res..
[56] Yichuan Tang,et al. Deep Learning using Linear Support Vector Machines , 2013, 1306.0239.
[57] Yiming Yang,et al. Implicit Kernel Learning , 2019, AISTATS.
[58] Rama Chellappa,et al. Multiple Kernel Learning for Sparse Representation-Based Classification , 2014, IEEE Transactions on Image Processing.