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電子ブック
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1. Fundamentals of Data Analytics : With a View to Machine Learning. 1st ed. 2020
by Rudolf Mathar, Gholamreza Alirezaei, Emilio Balda, Arash Behboodi
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
オンライン: https://doi.org/10.1007/978-3-030-56831-3
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1 Introduction
2 Prerequisites from Matrix Analysis
3 Multivariate Distributions and Moments
4 Dimensionality Reduction
5 Classification and Clustering
6 Support Vector Machines
7 Machine Learning
Index
1 Introduction
2 Prerequisites from Matrix Analysis
3 Multivariate Distributions and Moments
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電子ブック
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2. An Introduction to Statistical Learning : with Applications in R. 2nd ed. 2021
by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
出版情報: New York, NY : Springer US : Imprint: Springer, 2021
シリーズ名: Springer Texts in Statistics ;
オンライン: https://doi.org/10.1007/978-1-0716-1418-1
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Preface
1 Introduction
2 Statistical Learning
3 Linear Regression
4 Classification
5 Resampling Methods
6 Linear Model Selection and Regularization
7 Moving Beyond Linearity
8 Tree-Based Methods
9 Support Vector Machines
10 Deep Learning
11 Survival Analysis and Censored Data
12 Unsupervised Learning
13 Multiple Testing
Index
Preface
1 Introduction
2 Statistical Learning
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電子ブック
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3. Geometric Structures of Statistical Physics, Information Geometry, and Learning : SPIGL'20, Les Houches, France, July 27–31. 1st ed. 2021
edited by Frédéric Barbaresco, Frank Nielsen
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2021
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 361
オンライン: https://doi.org/10.1007/978-3-030-77957-3
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PART 1: Tribute to Jean-Marie Souriau seminal works: G. de Saxcé and C.-M. Marle, Structure des Systèmes Dynamiques
Jean-Marie Souriau’s book 50th birthday
F. Barbaresco, Jean-Marie Souriau’s Symplectic Model of Statistical Physics : Seminal papers on Lie Groups Thermodynamics - Quod Erat Demonstrandum
PART 2: Lie Group Geometry & Diffeological Model of Statistical Physics and Information Geometry: F. Barbaresco - Souriau-Casimir Lie Groups Thermodynamics & Machine Learning
K. Tojo and T. Yoshino, An exponential family on the upper half plane and its conjugate prior
E. Chevallier and N. Guigui, Wrapped statistical models on manifolds: motivations, the case SE(n), and generalization to symmetric spaces
G. de Saxcé, Galilean Thermodynamics of Continua
H. Vân Lê and A. Tuzhilin, Nonparametric estimations and the diffeological Fisher metric
PART 3: Advanced Geometrical Models of Statistical Manifolds in Information Geometry: J.-P. Francoise, Information Geometry and Integrable Hamiltonian Systems
M. N. Boyom, Relevant Differential topology in statistical manifolds
G. Pistone, A lecture about the use of Orlicz Spaces in Information Geometry
F. Nielsen and G. Hadjeres, Quasiconvex Jensen divergences and quasiconvex Bregman divergences
PART 4: Geometric Structures of Mechanics, Thermodynamics & Inference for Learning: F. Gay-Balmaz and H. Yoshimura, Dirac Structures and Variational Formulation of Thermodynamics for Open Systems
A. A. Simoes, D. Martín de Diego, M. L. Valcázar and Manuel de León, The geometry of some thermodynamic systems
F. Chinesta, E. Cueto, M. Grmela, B. Mioya, M. Pavelka and M. Sipka, Learning Physics from Data: a Thermodynamic Interpretation
Z. Terze, V. Pandža, M. Andrić and D. Zlatar, Computational dynamics of reduced coupled multibody-fluid system in Lie group setting
F. Masi, I. Stefanou, P. Vannucci and V. Maffi-Berthier, Material modeling via Thermodynamics-based Artificial Neural Networks
K. Grosvenor, Information Geometry and Quantum Fields
PART 5: Hamiltonian Monte Carlo, HMC Sampling and Learning on Manifolds: A. Barp, The Geometric Integration of Measure-Preserving Flows for Sampling and Hamiltonian Monte Carlo
A. Fradi, I. Adouani and C. Samir, Bayesian inference on local distributions of functions and multidimensional curves with spherical HMC sampling
S. Huntsman, Sampling and Statistical Physics via Symmetry
T. Gerald, H. Zaatiti and H. Hajri, A Practical hands-on for learning Graph Data Communities on Manifolds
PART 1: Tribute to Jean-Marie Souriau seminal works: G. de Saxcé and C.-M. Marle, Structure des Systèmes Dynamiques
Jean-Marie Souriau’s book 50th birthday
F. Barbaresco, Jean-Marie Souriau’s Symplectic Model of Statistical Physics : Seminal papers on Lie Groups Thermodynamics - Quod Erat Demonstrandum