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ORCIDInformation Theoretic Learning 2010
- José C. Príncipe:
Information Theoretic Learning - Renyi's Entropy and Kernel Perspectives. Springer 2010, ISBN 978-1-4419-1569-6 - José C. Príncipe:
Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces. 1-45 - Dongxin Xu, Deniz Erdogmus:
Renyi's Entropy, Divergence and Their Nonparametric Estimators. 47-102 - Deniz Erdogmus, Weifeng Liu:
Adaptive Information Filtering with Error Entropy and Error Correntropy Criteria. 103-140 - Deniz Erdogmus, Seungju Han, Abhishek Singh:
Algorithms for Entropy and Correntropy Adaptation with Applications to Linear Systems. 141-179 - Deniz Erdogmus, Rodney Morejon, Weifeng Liu:
Nonlinear Adaptive Filtering with MEE, MCC, and Applications. 181-218 - Deniz Erdogmus, Dongxin Xu, Kenneth E. Hild II:
Classification with EEC, Divergence Measures, and Error Bounds. 219-261 - Robert Jenssen, Sudhir Rao:
Clustering with ITL Principles. 263-298 - Sudhir Rao, Deniz Erdogmus, Dongxin Xu, Kenneth E. Hild II:
Self-Organizing ITL Principles for Unsupervised Learning. 299-349 - Jian-Wu Xu, Robert Jenssen, António R. C. Paiva, Il Park
:
A Reproducing Kernel Hilbert Space Framework for ITL. 351-384 - Weifeng Liu, Puskal P. Pokharel, Jian-Wu Xu, Sohan Seth:
Correntropy for Random Variables: Properties and Applications in Statistical Inference. 385-413 - Puskal P. Pokharel, Ignacio Santamaría, Jianwu Xu, Kyu-Hwa Jeong, Weifeng Liu:
Correntropy for Random Processes: Properties and Applications in Signal Processing. 415-455
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