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- Matrix and Tensor Factorization Techniques for Recommender Systems

- Author : Panagiotis Symeonidis
- Publsiher : Springer
- Release : 25 September 2016
- ISBN : 9783319413563
- Pages : 102 pages
- Rating : 4/5 from 21 reviews

GET THIS BOOKMatrix and Tensor Factorization Techniques for Recommender Systems

Read or download book entitled Matrix and Tensor Factorization Techniques for Recommender Systems written by Panagiotis Symeonidis which was release on 25 September 2016, this book published by Springer. Available in PDF, EPUB and Kindle Format. Book excerpt: This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.

- Author : Panagiotis Symeonidis,Andreas Zioupos
- Publisher : Springer
- Release Date : 2016-09-25
- Total pages : 102
- ISBN : 9783319413563

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**Summary :** This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices ...

- Author : Gérard Favier
- Publisher : Wiley-ISTE
- Release Date : 2021-09-15
- Total pages : 200
- ISBN : 9783319413563

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**Summary :** The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief ...

- Author : Andrzej Cichocki,Rafal Zdunek,Anh Huy Phan,Shun-ichi Amari
- Publisher : John Wiley & Sons
- Release Date : 2009-07-10
- Total pages : 500
- ISBN : 9783319413563

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**Summary :** This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and ...

- Author : Andrzej Cichocki,Rafal Zdunek,Anh Huy Phan,Shun-ichi Amari
- Publisher : Wiley
- Release Date : 2009-10-12
- Total pages : 500
- ISBN : 9783319413563

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**Summary :** This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and ...

- Author : Ferre Knaepkens
- Publisher : Unknown
- Release Date : 2017
- Total pages : 212
- ISBN : 9783319413563

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**Summary :** This thesis studies three different subjects, namely tensors and tensor decomposition, sparse interpolation and Pad\'e or rational approximation theory. These problems find their origin in various fields within mathematics: on the one hand tensors originate from algebra and are of importance in computer science and knowledge technology, while on ...

- Author : Christian Jutten
- Publisher : Unknown
- Release Date : 2021-08-02
- Total pages : 212
- ISBN : 9783319413563

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**Summary :** Download or read online Matrix and Tensor Decomposition written by Christian Jutten, published by which was released on . Get Matrix and Tensor Decomposition Books now! Available in PDF, ePub and Kindle....

- Author : Majid Janzamin,Rong Ge,Jean Kossaifi,Anima Anandkumar
- Publisher : Unknown
- Release Date : 2019-11-25
- Total pages : 156
- ISBN : 9783319413563

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**Summary :** 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 ...

- Author : Panagiotis Symeonidis,Andreas Zioupos
- Publisher : Springer
- Release Date : 2017-01-29
- Total pages : 102
- ISBN : 9783319413563

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**Summary :** This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD), UV-decomposition, Non-negative Matrix Factorization (NMF), etc. and describes in detail the pros and cons of each method for matrices ...

- Author : Gérard Favier
- Publisher : John Wiley & Sons
- Release Date : 2021-09-15
- Total pages : 200
- ISBN : 9783319413563

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**Summary :** The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief ...

- Author : Nauman Shahid
- Publisher : Unknown
- Release Date : 2017
- Total pages : 212
- ISBN : 9783319413563

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**Summary :** Mots-clés de l'auteur: Principal Component Analysis ; graphs ; low-rank and sparse decomposition ; clustering ; low-rank tensors....

- Author : Elina Robeva
- Publisher : Unknown
- Release Date : 2016
- Total pages : 195
- ISBN : 9783319413563

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**Summary :** In this thesis we apply techniques from algebraic geometry to problems arising from optimization and statistics. In particular, we consider data that takes the form of a matrix, a tensor or an image, and we study how to decompose it so as to find additional and seemingly hidden information about ...

- Author : Carla Dee Martin
- Publisher : Unknown
- Release Date : 2005
- Total pages : 482
- ISBN : 9783319413563

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**Summary :** The second problem in this dissertation involves solving shifted linear systems of the form (A - lambdaI) x = b when A is a Kronecker product of matrices. The Schur decomposition is used to reduce the shifted Kronecker product system to a Kronecker product of quasi-triangular matrices. The system is solved ...

- Author : Shi-Ju Ran
- Publisher : Springer Nature
- Release Date : 2020-01-01
- Total pages : 150
- ISBN : 9783319413563

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**Summary :** Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This open access book aims to explain the tensor network contraction approaches in a systematic way, from the basic definitions to ...

- Author : Yimin Wei,Weiyang Ding
- Publisher : Academic Press
- Release Date : 2016-08-28
- Total pages : 148
- ISBN : 9783319413563

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**Summary :** Theory and Computation of Tensors: Multi-Dimensional Arrays investigates theories and computations of tensors to broaden perspectives on matrices. Data in the Big Data Era is not only growing larger but also becoming much more complicated. Tensors (multi-dimensional arrays) arise naturally from many engineering or scientific disciplines because they can represent ...

- Author : Gérard Favier
- Publisher : John Wiley & Sons
- Release Date : 2020-01-02
- Total pages : 318
- ISBN : 9783319413563

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**Summary :** Nowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures ...