The following pages link to Mathematics for Machine Learning (Q5237380):
Displaying 28 items.
- Feature selection for multivariate contribution analysis in fault detection and isolation (Q776095) (← links)
- The nonconvex tensor robust principal component analysis approximation model via the weighted \(\ell_p\)-norm regularization (Q2053328) (← links)
- Matrix differential calculus with applications in the multivariate linear model and its diagnostics (Q2062791) (← links)
- \(K\)-expectiles clustering (Q2078530) (← links)
- Unified regression model in fitting potential energy surfaces for quantum dynamics (Q2084807) (← links)
- Mathematical foundation of artificial intelligence (Q2086263) (← links)
- A UMAP-based clustering method for multi-scale damage analysis of laminates (Q2110084) (← links)
- A regularized alternating least-squares method for minimizing a sum of squared Euclidean norms with rank constraint (Q2162388) (← links)
- Tensor product and Hadamard product for the Wasserstein means (Q2197152) (← links)
- Algebraic model selection and experimental design in biological data science (Q2665755) (← links)
- Foundations of machine learning (Q2855955) (← links)
- (Q4524241) (← links)
- (Q5106188) (← links)
- MATHEMATICS OF MACHINE LEARNING: AN INTRODUCTION (Q5121988) (← links)
- Data Science and Machine Learning (Q5206282) (← links)
- Advanced Lectures on Machine Learning (Q5424894) (← links)
- A singular Riemannian geometry approach to deep neural networks. II: Reconstruction of 1-D equivalence classes (Q6053359) (← links)
- On the MDM method for solving the general quadratic problem of mathematical diagnostics (Q6060230) (← links)
- DEEP EQUILIBRIUM NETS (Q6067145) (← links)
- A singular Riemannian geometry approach to deep neural networks. I: Theoretical foundations (Q6077759) (← links)
- Regression-Based Projection for Learning Mori–Zwanzig Operators (Q6084965) (← links)
- A continuous convolutional trainable filter for modelling unstructured data (Q6109268) (← links)
- Machine Learning in Pure Mathematics and Theoretical Physics (Q6109961) (← links)
- Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques (Q6126024) (← links)
- Image segmentation using Bayesian inference for convex variant Mumford-Shah variational model (Q6541913) (← links)
- Multifractional Brownian motion characterization based on Hurst exponent estimation and statistical learning (Q6567626) (← links)
- Enhancing deep learning algorithm accuracy and stability using multicriteria optimization: an application to distributed learning with MNIST digits (Q6589086) (← links)
- Explainable data-driven Q-learning control for a class of discrete-time linear autonomous systems (Q6595363) (← links)
