Greedy feature selection: Classifier-dependent feature selection via greedy methods
Fuente:
arXiv
Saved in:
| Main Authors: | Camattari, Fabiana, Guastavino, Sabrina, Marchetti, Francesco, Piana, Michele, Perracchione, Emma |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Feature Understanding and Sparsity Enhancement via 2-Layered kernel machines (2L-FUSE)
by: Camattari, Fabiana, et al.
Published: (2025)
by: Camattari, Fabiana, et al.
Published: (2025)
Physics-informed features in supervised machine learning
by: Lampani, Margherita, et al.
Published: (2025)
by: Lampani, Margherita, et al.
Published: (2025)
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks
by: Adcock, Ben, et al.
Published: (2022)
by: Adcock, Ben, et al.
Published: (2022)
A Recipe for Learning Variably Scaled Kernels via Discontinuous Neural Networks
by: Audone, Gianluca, et al.
Published: (2024)
by: Audone, Gianluca, et al.
Published: (2024)
Learning Geometric-Aware Quadrature Rules for Functional Minimization
by: Smaragdakis, Costas
Published: (2025)
by: Smaragdakis, Costas
Published: (2025)
An algorithmic approach to direct spline products: procedures and computational aspects
by: Patrizi, Francesco, et al.
Published: (2026)
by: Patrizi, Francesco, et al.
Published: (2026)
Quantitative Universal Approximation for Noisy Quantum Neural Networks
by: Gonon, Lukas, et al.
Published: (2026)
by: Gonon, Lukas, et al.
Published: (2026)
Accuracy and stability of Artificial Neural Networks for HP-Splines frequency parameter selection
by: Bruni, Vittoria, et al.
Published: (2026)
by: Bruni, Vittoria, et al.
Published: (2026)
Analysis of Regularized Learning in Banach Spaces for Linear-functional Data
by: Ye, Qi
Published: (2021)
by: Ye, Qi
Published: (2021)
Teaching and Learning under Deductive Errors
by: Telle, Jan Arne, et al.
Published: (2026)
by: Telle, Jan Arne, et al.
Published: (2026)
Regularity and tailored regularization of Deep Neural Networks, with application to parametric PDEs in uncertainty quantification
by: Keller, Alexander, et al.
Published: (2025)
by: Keller, Alexander, et al.
Published: (2025)
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs
by: Gonon, Lukas, et al.
Published: (2023)
by: Gonon, Lukas, et al.
Published: (2023)
GAN-based iterative motion estimation in HASTE MRI
by: Feinler, Mathias S., et al.
Published: (2024)
by: Feinler, Mathias S., et al.
Published: (2024)
Multi- and Infinite-variate Integration and $L^2$-Approximation on Hilbert Spaces with Gaussian Kernels
by: Gnewuch, Michael, et al.
Published: (2024)
by: Gnewuch, Michael, et al.
Published: (2024)
Graph-Instructed Neural Networks for Sparse Grid-Based Discontinuity Detectors
by: Della Santa, Francesco, et al.
Published: (2024)
by: Della Santa, Francesco, et al.
Published: (2024)
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators
by: Fabiani, Gianluca, et al.
Published: (2024)
by: Fabiani, Gianluca, et al.
Published: (2024)
NLAFormer: Transformers Learn Numerical Linear Algebra Operations
by: Ma, Zhantao, et al.
Published: (2025)
by: Ma, Zhantao, et al.
Published: (2025)
A quantum-inspired multi-level tensor-train monolithic space-time method for nonlinear PDEs
by: Rapaka, N. R., et al.
Published: (2026)
by: Rapaka, N. R., et al.
Published: (2026)
Least Squares with Equality constraints Extreme Learning Machines for the resolution of PDEs
by: De Falco, Davide Elia, et al.
Published: (2025)
by: De Falco, Davide Elia, et al.
Published: (2025)
Solving Approximation Tasks with Greedy Deep Kernel Methods
by: Klink, Marian, et al.
Published: (2025)
by: Klink, Marian, et al.
Published: (2025)
Sparse Implementation of Versatile Graph-Informed Layers
by: Della Santa, Francesco
Published: (2024)
by: Della Santa, Francesco
Published: (2024)
Sprecher Networks: A Parameter-Efficient Kolmogorov-Arnold Architecture
by: Hägg, Christian, et al.
Published: (2025)
by: Hägg, Christian, et al.
Published: (2025)
Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data
by: Kratsios, Anastasis, et al.
Published: (2025)
by: Kratsios, Anastasis, et al.
Published: (2025)
Regime-Aware Time Weighting for Physics-Informed Neural Networks
by: Turinici, Gabriel
Published: (2024)
by: Turinici, Gabriel
Published: (2024)
Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches
by: Guastavino, Sabrina, et al.
Published: (2024)
by: Guastavino, Sabrina, et al.
Published: (2024)
Quantum circuits for the advection-diffusion equation with boundary conditions based on LCHS
by: Chen, Leyu, et al.
Published: (2026)
by: Chen, Leyu, et al.
Published: (2026)
Prediction of discretization of online GMsFEM using deep learning for Richards equation
by: Spiridonov, Denis, et al.
Published: (2024)
by: Spiridonov, Denis, et al.
Published: (2024)
pETNNs: Partial Evolutionary Tensor Neural Networks for Solving Time-dependent Partial Differential Equations
by: Kao, Tunan, et al.
Published: (2024)
by: Kao, Tunan, et al.
Published: (2024)
Autoencoded UMAP-Enhanced Clustering for Unsupervised Learning
by: Chavooshi, Malihehsadat, et al.
Published: (2025)
by: Chavooshi, Malihehsadat, et al.
Published: (2025)
Dynamics-Encoded Deep Learning for Robust System Identification and Parameter Estimation
by: Ho, Caitlin, et al.
Published: (2024)
by: Ho, Caitlin, et al.
Published: (2024)
Different Statistical Perspectives for Understanding Generalisation in Graph Neural Networks
by: Ayday, Nil, et al.
Published: (2026)
by: Ayday, Nil, et al.
Published: (2026)
Entropy stable conservative flux form neural networks
by: Liu, Lizuo, et al.
Published: (2024)
by: Liu, Lizuo, et al.
Published: (2024)
RIS: Regularized Imaging Spectroscopy for STIX on-board Solar Orbiter
by: Volpara, Anna, et al.
Published: (2024)
by: Volpara, Anna, et al.
Published: (2024)
Trustworthy AI in numerics: On verification algorithms for neural network-based PDE solvers
by: Haugen, Emil, et al.
Published: (2025)
by: Haugen, Emil, et al.
Published: (2025)
Solving the BGK Model and Boltzmann equation by Fourier Neural Operator with conservative constraints
by: Hu, Boyun, et al.
Published: (2025)
by: Hu, Boyun, et al.
Published: (2025)
Learning Neural Pushforward Samplers for Distributions from Fokker-Planck Equations by Weak Adversarial Training
by: He, Andrew Qing, et al.
Published: (2025)
by: He, Andrew Qing, et al.
Published: (2025)
Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
by: Codega, Gabriele, et al.
Published: (2025)
by: Codega, Gabriele, et al.
Published: (2025)
Computational homogenization for aerogel-like polydisperse open-porous materials using neural network--based surrogate models on the microscale
by: Klawonn, Axel, et al.
Published: (2024)
by: Klawonn, Axel, et al.
Published: (2024)
A Model-Consistent Data-Driven Computational Strategy for PDE Joint Inversion Problems
by: Ren, Kui, et al.
Published: (2022)
by: Ren, Kui, et al.
Published: (2022)
Deep asymptotic expansion method for solving singularly perturbed time-dependent reaction-advection-diffusion equations
by: Zhu, Qiao, et al.
Published: (2025)
by: Zhu, Qiao, et al.
Published: (2025)
Similar Items
-
Feature Understanding and Sparsity Enhancement via 2-Layered kernel machines (2L-FUSE)
by: Camattari, Fabiana, et al.
Published: (2025) -
Physics-informed features in supervised machine learning
by: Lampani, Margherita, et al.
Published: (2025) -
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks
by: Adcock, Ben, et al.
Published: (2022) -
A Recipe for Learning Variably Scaled Kernels via Discontinuous Neural Networks
by: Audone, Gianluca, et al.
Published: (2024) -
Learning Geometric-Aware Quadrature Rules for Functional Minimization
by: Smaragdakis, Costas
Published: (2025)