Manifold Learning Algorithms – Bücher zum Thema Manifold Learning Algorithms finden und kaufen

Kernel Learning Algorithms for Face Recognition

Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
Springer US
149.79 € · Hardcover

Analysis Based Face Recognition Kernel Clustering Kernel Construction Kernel Manifold Learning Kernel Neural Network Kernel Optimization Kernel learning Pattern recognition face recognition feature extraction

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involv...

Computational Methods for Deep Learning

Wei Qi Yan
Springer Singapore
96.29 € · Hardcover

Deep Learning Machine Learning Pattern Analysis Manifold Learning Machine Vision Reinforcement Learning Natural Language Processing Autoencoder Generative Adversarial Networks Transfer Learning Time-Series Analysis Calculus Linear Algebra Numerical Analysis Tensor Algebra

The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this...

Advances in Data Science

Springer International Publishing
181.89 € · Hardcover

data analysis dimension reduction tensor decomposition graph algorithms active learning semi-supervised learning path metrics manifold learning geometric measures feature learning geometric signature of data embedding techniques text embeddings

This volume features recent advances in data science ranging from algebraic geometry used for existence and uniqueness proofs of low rank approximations for tensor data, to category theory used for natural language processing applications, to approximation and optimization frameworks developed for c...

Kernel Learning Algorithms for Face Recognition

Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
Springer US
106.99 € · eBook

Analysis Based Face Recognition Kernel Clustering Kernel Construction Kernel Manifold Learning Kernel Neural Network Kernel Optimization Kernel learning Pattern recognition face recognition feature extraction

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involv...

Kernel Learning Algorithms for Face Recognition

Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
Springer US
117.69 € · Paperback

Analysis Based Face Recognition Kernel Clustering Kernel Construction Kernel Manifold Learning Kernel Neural Network Kernel Optimization Kernel learning Pattern recognition face recognition feature extraction

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involv...

Computational Methods for Deep Learning

Wei Qi Yan
Springer Singapore
96.29 € · eBook

Deep Learning Machine Learning Pattern Analysis Manifold Learning Machine Vision Reinforcement Learning Natural Language Processing Autoencoder Generative Adversarial Networks Transfer Learning Time-Series Analysis Calculus Linear Algebra Numerical Analysis Tensor Algebra

The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this...

Open Problems in Spectral Dimensionality Reduction

Harry Strange, Reyer Zwiggelaar
Springer International Publishing
53.49 € · eBook

Big Data Machine Learning Manifold Learning Algorithms Nonlinear Dimensionality Reduction (NLDR) Principal Component Analysis (PCA) data structures algorithm analysis and problem complexity

The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements w...

Open Problems in Spectral Dimensionality Reduction

Harry Strange, Reyer Zwiggelaar
Springer International Publishing
53.49 € · Paperback

Big Data Machine Learning Manifold Learning Algorithms Nonlinear Dimensionality Reduction (NLDR) Principal Component Analysis (PCA) data structures algorithm analysis and problem complexity

The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements w...

Advances in Data Science

Springer International Publishing
171.19 € · eBook

data analysis dimension reduction tensor decomposition graph algorithms active learning semi-supervised learning path metrics manifold learning geometric measures feature learning geometric signature of data embedding techniques text embeddings

This volume features recent advances in data science ranging from algebraic geometry used for existence and uniqueness proofs of low rank approximations for tensor data, to category theory used for natural language processing applications, to approximation and optimization frameworks developed for c...

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