Cover Image

Parametrising the Inhomogeneity Inducing Capacity of a Training Set, and its Impact on Supervised Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Roy, Gargi, Chakrabarty, Dalia
Format:	Preprint
Published:	2025
Subjects:	Machine Learning 62H20, 60G10, 68T05, 68T27, 60J20
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online Regularized Learning Algorithms in RKHS with $β$- and $ϕ$-Mixing Sequences
by: Roy, Priyanka, et al.
Published: (2025)

Markov Chain Gradient Descent in Hilbert Spaces
by: Roy, Priyanka, et al.
Published: (2024)

Gradient Descent Algorithm in Hilbert Spaces under Stationary Markov Chains with $ϕ$- and $β$-Mixing
by: Roy, Priyanka, et al.
Published: (2025)

Model-free filtering in high dimensions via projection and score-based diffusions
by: Christensen, Sören, et al.
Published: (2025)

Radial Extremality for LRU Caching and the Fill--Holst Conjecture
by: Long, Christopher D.
Published: (2026)

Error analysis for learning fractional stochastic differential equations with applications in neural approximations
by: Dehshiri, Mahdi, et al.
Published: (2026)

A Theory of Non-Acyclic Generative Flow Networks
by: Brunswic, Leo Maxime, et al.
Published: (2023)

Dirichlet kernel density estimation for strongly mixing sequences on the simplex
by: Daayeb, Hanen, et al.
Published: (2025)

Conditioning of Banach Space Valued Gaussian Random Variables: An Approximation Approach Based on Martingales
by: Steinwart, Ingo
Published: (2024)

Anchored Likelihood-Ratio Geometry of Anonymous Shuffle Experiments: Exact Privacy Envelopes and Universal Low-Budget Design
by: Shvets, Alex
Published: (2026)

Uniform-in-time convergence bounds for Persistent Contrastive Divergence Algorithms
by: Oliva, Paul Felix Valsecchi, et al.
Published: (2025)

Towards a Mathematical Theory of Adaptive Memory: From Time-Varying to Responsive Fractional Brownian Motion
by: Jiang, Jiahao
Published: (2025)

Joint FCLT for Sample Quantile and Measures of Dispersion for Functionals of Mixing Processes
by: Bräutigam, Marcel, et al.
Published: (2021)

Stein's method for the matrix normal distribution
by: Gaunt, Robert E., et al.
Published: (2026)

Estimating the number of clusters of a Block Markov Chain
by: van Vuren, Thomas, et al.
Published: (2024)

Imbalanced Classification under Capacity Constraints
by: Fraiman, Daniel, et al.
Published: (2026)

On nonparametric estimation of the interaction function in particle system models
by: Belomestny, Denis, et al.
Published: (2024)

Spatio-temporal probabilistic forecast using MMAF-guided learning
by: Bardi, Leonardo, et al.
Published: (2026)

Zero-Coupon Treasury Rates and Returns using the Volatility Index
by: Park, Jihyun, et al.
Published: (2024)

A New Reliable & Parsimonious Learning Strategy Comprising Two Layers of Gaussian Processes, to Address Inhomogeneous Empirical Correlation Structures
by: Roy, Gargi, et al.
Published: (2024)

On the dependence between a Wiener process and its running maxima and running minima processes
by: Dąbrowski, Karol, et al.
Published: (2021)

Physics-Informed Singular-Value Learning for Cross-Covariances Forecasting in Financial Markets
by: Manolakis, Efstratios, et al.
Published: (2026)

Kernel Limit for a Class of Recurrent Neural Networks Trained on Ergodic Data Sequences
by: Lam, Samuel Chun-Hei, et al.
Published: (2023)

Ancestral Inference and Learning for Branching Processes in Random Environments
by: Jiang, Xiaoran, et al.
Published: (2025)

A New Stock Market Valuation Measure with Applications to Retirement Planning
by: Sarantsev, Andrey
Published: (2019)

State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics
by: Li, Zhuoyuan, et al.
Published: (2024)

Ising Models with Hidden Markov Structure: Applications to Probabilistic Inference in Machine Learning
by: Herrera, F., et al.
Published: (2025)

Central limit theorems for the eigenvalues of graph Laplacians on data clouds
by: Li, Chenghui, et al.
Published: (2025)

Convergence rate of Euler-Maruyama scheme to the invariant probability measure under total variation distance
by: Wang, Yuke, et al.
Published: (2025)

Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
by: Lam, Samuel Chun-Hei, et al.
Published: (2025)

Generator-based Graph Generation via Heat Diffusion
by: Stephenson, Anthony, et al.
Published: (2026)

Nonparametric Inference for Noise Covariance Kernels in Parabolic SPDEs using Space-Time Infill-Asymptotics
by: Petersson, Andreas, et al.
Published: (2025)

Perfect sampling of stochastic matching models with reneging
by: Masanet, Thomas, et al.
Published: (2022)

Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood
by: Naslidnyk, Masha, et al.
Published: (2023)

Distribution-free Measures of Association based on Optimal Transport
by: Deb, Nabarun, et al.
Published: (2024)

Operator Learning Using Random Features: A Tool for Scientific Computing
by: Nelsen, Nicholas H., et al.
Published: (2024)

Multiple Random Walks on Graphs: Mixing Few to Cover Many
by: Rivera, Nicolás, et al.
Published: (2020)

A high-order recombination algorithm for weak approximation of stochastic differential equations
by: Ninomiya, Syoiti, et al.
Published: (2025)

An Exponential Averaging Process with Strong Convergence Properties
by: Köhne, Frederik, et al.
Published: (2025)

Time-Biased Random Walks and Robustness of Expanders
by: Olesker-Taylor, Sam, et al.
Published: (2024)