Now Publishers Spectral Learning on Matrices and Tensors (Foundations and Trends® in Machine Learning)

Name: Spectral Learning on Matrices and Tensors (Foundations and Trends(R) in Machine Learning)
Brand: Now Publishers
Price: 79.5 GBP
Availability: OutOfStock

Architecture & Microprocessors

Price History & Forecast

Last 63 days • 63 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 63 days • 1 price levels

Days at Price

Price Analysis

Most common price: £80 (63 days, 100.0%)

Price range: £80 - £80

Price levels: 1 different prices over 63 days

Description

The authors of this monograph survey recent progress in using spectral methods including matrix and tensor decomposition techniques to learn many popular latent variable models. With careful implementation, tensor-based methods can run efficiently in practice, and in many cases they are the only algorithms with provable guarantees on running time and sample complexity.The focus is on a special type of tensor decomposition called CP decomposition, and the authors cover a wide range of algorithms to find the components of such tensor decomposition. They also discuss the usefulness of this decomposition by reviewing several probabilistic models that can be learned using such tensor methods.The second half of the monograph looks at practical applications. This includes using Tensorly, an efficient tensor algebra software package, which has a simple python interface for expressing tensor operations. It also has a flexible back-end system supporting NumPy, PyTorch, TensorFlow, and MXNet.Spectral Learning on Matrices and Tensors provides a theoretical and practical introduction to designing and deploying spectral learning on both matrices and tensors. It is of interest for all students, researchers and practitioners working on modern day machine learning problems.

Product Specifications

Brand: Now Publishers
Format: paperback
ASIN: 1680836404
Category: Books > Subjects > Computing & Internet > Computer Science > Architecture & Microprocessors
Domain: Amazon UK
Release Date: 30 November 2019
Listed Since: 27 November 2019

Barcode

No barcode data available

Now Publishers Spectral Learning on Matrices and Tensors (Foundations and Trends® in Machine Learning)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions (Foundations and Trends (R) in Machine Learning)

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives (Foundations and Trends in Machine Learning)

Tensor Regression (Foundations and Trends® in Machine Learning)

Theory and Computation of Complex Tensors and its Applications

Tensor Computation for Data Analysis

From Algebraic Structures to Tensors (Digital Signal and Image Processing: Matrices and Tensors in Signal Processing Set)

Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation

Elements of Dimensionality Reduction and Manifold Learning

Tensor Analysis: Spectral Theory and Special Tensors

Deep Learning Through the Prism of Tensors: 162 (Studies in Big Data, 162)

Tensor Decompositions for Data Science

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Non-convex Optimization for Machine Learning (Foundations and Trends in Machine Learning)

Model-Based Deep Learning (Foundations and Trends® in Signal Processing)

Linear Algebra and Optimization for Machine Learning: A Textbook

Advanced Linear and Matrix Algebra

Convex Optimization for Machine Learning (NowOpen)

Parallelism in Matrix Computations (Scientific Computation)

Springer Feature Learning and Understanding Algorithms Book

Neural Networks and Deep Learning: A Textbook

Advanced Linear and Matrix Algebra

Matrix Calculus, Kronecker Product And Tensor Product: A Practical Approach To Linear Algebra, Multilinear Algebra And Tensor Calculus With Software Implementations (Third Edition)

Machine Learning with Python: Theory and Implementation

Basic Mathematical Foundations of AI: Hands on with Python (Mastering Machine Learning)