Cover Image

Ridge Regression from Poisson Resetting: A Renewal Perspective on Spectral Regularization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Jolakoski, Petar
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistical Mechanics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stochastic Resetting Mitigates Latent Gradient Bias of SGD from Label Noise
by: Bae, Youngkyoung, et al.
Published: (2024)

The impact of stochastic resetting on resource allocation: The case of Reallocating geometric Brownian motion
by: Jolakoski, Petar, et al.
Published: (2024)

Response to an external field of a generalized Langevin equation with stochastic resetting of the memory kernel
by: Jolakoski, Petar, et al.
Published: (2025)

Posterior Collapse as Automatic Spectral Pruning
by: Hirn, Johannes
Published: (2026)

Cross-Spectral Witness for Hidden Nonequilibrium Beyond the Scalar Ceiling
by: Bi, Yuda, et al.
Published: (2026)

Dropout Neural Network Training Viewed from a Percolation Perspective
by: Devlin, Finley, et al.
Published: (2025)

Transfer Learning in $\ell_1$ Regularized Regression: Hyperparameter Selection Strategy based on Sharp Asymptotic Analysis
by: Okajima, Koki, et al.
Published: (2024)

The Thermodynamic Costs of Simple Linear Regression
by: D'Ambrosia, Samuel H., et al.
Published: (2026)

Spectral Methods in Complex Systems
by: Caravelli, Francesco
Published: (2025)

Sorting by Resetting
by: Cleuren, Bart, et al.
Published: (2026)

On Distinguishing Capability Elicitation from Capability Creation in Post-Training: A Free-Energy Perspective
by: Li, Yuhao, et al.
Published: (2026)

Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles
by: Rydzewski, Jakub
Published: (2024)

Beyond Poisson: First-Passage Asymptotics of Renewal Shot Noise
by: Brémont, Julien
Published: (2025)

Optimal Computation from Fluctuation Responses
by: Lyu, Jinghao, et al.
Published: (2025)

Discrete distributions are learnable from metastable samples
by: Jayakumar, Abhijith, et al.
Published: (2024)

Solvation Free Energies from Neural Thermodynamic Integration
by: Máté, Bálint, et al.
Published: (2024)

Building causation links in stochastic nonlinear systems from data
by: Chibbaro, Sergio, et al.
Published: (2025)

Stochastic Resetting and Large Deviations
by: Evans, Martin R., et al.
Published: (2024)

First Passage Resetting Gas
by: Biroli, Marco, et al.
Published: (2025)

Autonomous Ratcheting by Stochastic Resetting
by: Ghosh, Pulak K., et al.
Published: (2023)

Minimizing the Profligacy of Searches with Reset
by: Sunil, John C., et al.
Published: (2024)

Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models
by: Máté, Bálint, et al.
Published: (2024)

A differentiable programming framework for spin models
by: Farias, Tiago de Souza, et al.
Published: (2023)

Speed-accuracy relations for diffusion models: Wisdom from nonequilibrium thermodynamics and optimal transport
by: Ikeda, Kotaro, et al.
Published: (2024)

Beyond Explained Variance: A Cautionary Tale of PCA
by: Marchetti, Gionni
Published: (2026)

Susceptibilities and Patterning: A Primer on Linear Response in Bayesian Learning
by: Elliott, Chris, et al.
Published: (2026)

SETOL: A Semi-Empirical Theory of (Deep) Learning
by: Martin, Charles H, et al.
Published: (2025)

Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks
by: Székely, Eszter, et al.
Published: (2023)

Thermodynamic Isomorphism of Transformers: A Lagrangian Approach to Attention Dynamics
by: Kim, Gunn
Published: (2026)

Efficient Identification of Critical Transitions via Flow Matching: A Scalable Generative Approach for Many-Body Systems
by: Lee, Qian-Rui, et al.
Published: (2025)

Learning the Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou Trajectories: A Nonlinear Approach using a Deep Autoencoder Model
by: Marchetti, Gionni
Published: (2026)

Stochastic Resetting Accelerates Policy Convergence in Reinforcement Learning
by: Zhou, Jello, et al.
Published: (2026)

Ising Model with Power Law Resetting
by: K, Anagha V, et al.
Published: (2026)

Reset Induced Multimodality in Unbounded Potential
by: Capała, Karol
Published: (2025)

Review and Prospect of Algebraic Research in Equivalent Framework between Statistical Mechanics and Machine Learning Theory
by: Watanabe, Sumio
Published: (2024)

Statistics of Min-max Normalized Eigenvalues in Random Matrices
by: Nakada, Hyakka, et al.
Published: (2025)

Laws of thermodynamics for exponential families
by: Balsubramani, Akshay
Published: (2025)

Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
by: Hayashi, Taiga, et al.
Published: (2026)

Composing diffusion priors with explicit physical context via generative Gibbs sampling
by: Wang, Weizhou, et al.
Published: (2026)

The topological gap at criticality: scaling exponent d + η, universality, and scope
by: Loftus, Matthew
Published: (2026)