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Sergios Theodoridis is professor emeritus of machine learning and data processing with the National and Kapodistrian University of Athens, Athens, Greece. He has also served as distinguished professor with the Aalborg University Denmark and as professor with the Chinese University of Hong Kong, Shenzhen, China. In 2023, he received an honorary doctorate degree ([...]) from the University of Edinburgh, U.K. He has also received a number of prestigious awards, including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the [...]opean Association for Signal Processing (EURASIP) Athanasios Papoulis Award, the 2014 IEEE Signal Processing Society Carl Friedrich Gauss Education Award, and the [...]ASIP Meritorious Service Award. He has served as president of EURASIP and vice president for the IEEE Signal Processing Society. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
1. Introduction 2. Probability and stochastic Processes 3. Learning in parametric Modeling: Basic Concepts and Directions 4. Mean-Square Error Linear Estimation 5. Stochastic Gradient Descent: the LMS Algorithm and its Family 6. The Least-Squares Family 7. Classification: A Tour of the Classics 8. Parameter Learning: A Convex Analytic Path 9. Sparsity-Aware Learning: Concepts and Theoretical Foundations 10. Sparsity-Aware Learning: Algorithms and Applications 11. Learning in Reproducing Kernel Hilbert Spaces 12. Bayesian Learning: Inference and the EM Algorithm 13. Bayesian Learning: Approximate Inference and nonparametric Models 14. Montel Carlo Methods 15. Probabilistic Graphical Models: Part 1 16. Probabilistic Graphical Models: Part 2 17. Particle Filtering 18. Neural Networks and Deep Learning 19. Dimensionality Reduction and Latent Variables Modeling
Erscheinungsjahr: | 2020 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: | Gebunden |
ISBN-13: | 9780128188033 |
ISBN-10: | 0128188030 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Theodoridis, Sergios |
Hersteller: | Elsevier Science Publishing Co Inc |
Maße: | 241 x 195 x 63 mm |
Von/Mit: | Sergios Theodoridis |
Erscheinungsdatum: | 06.03.2020 |
Gewicht: | 2,36 kg |
Sergios Theodoridis is professor emeritus of machine learning and data processing with the National and Kapodistrian University of Athens, Athens, Greece. He has also served as distinguished professor with the Aalborg University Denmark and as professor with the Chinese University of Hong Kong, Shenzhen, China. In 2023, he received an honorary doctorate degree ([...]) from the University of Edinburgh, U.K. He has also received a number of prestigious awards, including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the [...]opean Association for Signal Processing (EURASIP) Athanasios Papoulis Award, the 2014 IEEE Signal Processing Society Carl Friedrich Gauss Education Award, and the [...]ASIP Meritorious Service Award. He has served as president of EURASIP and vice president for the IEEE Signal Processing Society. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
1. Introduction 2. Probability and stochastic Processes 3. Learning in parametric Modeling: Basic Concepts and Directions 4. Mean-Square Error Linear Estimation 5. Stochastic Gradient Descent: the LMS Algorithm and its Family 6. The Least-Squares Family 7. Classification: A Tour of the Classics 8. Parameter Learning: A Convex Analytic Path 9. Sparsity-Aware Learning: Concepts and Theoretical Foundations 10. Sparsity-Aware Learning: Algorithms and Applications 11. Learning in Reproducing Kernel Hilbert Spaces 12. Bayesian Learning: Inference and the EM Algorithm 13. Bayesian Learning: Approximate Inference and nonparametric Models 14. Montel Carlo Methods 15. Probabilistic Graphical Models: Part 1 16. Probabilistic Graphical Models: Part 2 17. Particle Filtering 18. Neural Networks and Deep Learning 19. Dimensionality Reduction and Latent Variables Modeling
Erscheinungsjahr: | 2020 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: | Gebunden |
ISBN-13: | 9780128188033 |
ISBN-10: | 0128188030 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Theodoridis, Sergios |
Hersteller: | Elsevier Science Publishing Co Inc |
Maße: | 241 x 195 x 63 mm |
Von/Mit: | Sergios Theodoridis |
Erscheinungsdatum: | 06.03.2020 |
Gewicht: | 2,36 kg |