:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Abélès, Baptiste, de Vilmarest, Joseph, Wintemberger, Olivier
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Probability
Online Access:	https://arxiv.org/abs/2402.14684
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online Learning Approach for Survival Analysis
by: Fernandez, Camila, et al.
Published: (2024)

Stochastic approximation in non-markovian environments revisited
by: Borkar, Vivek Shripad
Published: (2026)

Assessing Extrapolation of Peaks Over Thresholds with Martingale Testing
by: de Vilmarest, Joseph, et al.
Published: (2025)

Extraction of informative statistical features in the problem of forecasting time series generated by It{ô}-type processes
by: Korolev, Victor, et al.
Published: (2026)

Sliding-Window Signatures for Time Series: Application to Electricity Demand Forecasting
by: Drobac, Nina, et al.
Published: (2025)

Online-to-PAC generalization bounds under graph-mixing dependencies
by: Abélès, Baptiste, et al.
Published: (2024)

Generalization bounds for mixing processes via delayed online-to-PAC conversions
by: Abeles, Baptiste, et al.
Published: (2024)

Data denoising with self consistency, variance maximization, and the Kantorovich dominance
by: Hiew, Joshua Zoen-Git, et al.
Published: (2025)

Linear Bandits with Non-i.i.d. Noise
by: Abélès, Baptiste, et al.
Published: (2025)

High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
by: Bigot, Jérémie, et al.
Published: (2024)

High-dimensional ridge regression with random features for non-identically distributed data with a variance profile
by: Dabo, Issa-Mbenard, et al.
Published: (2025)

Autocorrelation effects in a stochastic-process model for decision making via time series
by: Yamagami, Tomoki, et al.
Published: (2026)

Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
by: Hayakawa, Satoshi, et al.
Published: (2025)

The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler
by: Bou-Rabee, Nawaf, et al.
Published: (2025)

From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes
by: Chen, Zaiwei, et al.
Published: (2025)

Score matching for bridges without learning time-reversals
by: Baker, Elizabeth L., et al.
Published: (2024)

Forecast collapse of transformer-based models under squared loss in financial time series
by: Andreoletti, Pierre
Published: (2026)

Model orthogonalization and Bayesian forecast mixing via Principal Component Analysis
by: Giuliani, Pablo, et al.
Published: (2024)

Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
by: Leão, Dorival, et al.
Published: (2026)

An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition
by: de Vilmarest, Joseph, et al.
Published: (2023)

Fisher information dissipation for time inhomogeneous stochastic differential equations
by: Feng, Qi, et al.
Published: (2024)

Long-time asymptotics of noisy SVGD outside the population limit
by: Priser, Victor, et al.
Published: (2024)

Comparing statistical and deep learning techniques for parameter estimation of continuous-time stochastic differentiable equations
by: Sankoh, Aroon, et al.
Published: (2025)

Scale-Adaptive Generative Flows for Multiscale Scientific Data
by: Chen, Yifan, et al.
Published: (2025)

The Optimal Approximation Factor in Density Estimation
by: Bousquet, Olivier, et al.
Published: (2019)

Adaptive Estimation of Multivariate Piecewise Polynomials and Bounded Variation Functions by Optimal Decision Trees
by: Chatterjee, Sabyasachi, et al.
Published: (2019)

Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities
by: Li, Matthew T. C., et al.
Published: (2024)

A Unified MDL-based Binning and Tensor Factorization Framework for PDF Estimation
by: Musab, Mustafa, et al.
Published: (2025)

On the Nonconvexity of Push-Forward Constraints and Its Consequences in Machine Learning
by: de Lara, Lucas, et al.
Published: (2024)

Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
by: Lebeau, Hugo, et al.
Published: (2024)

Global universality via discrete-time signatures
by: Ceylan, Mihriban, et al.
Published: (2026)

Gradient-flow SDEs have unique transient population dynamics
by: Guan, Vincent, et al.
Published: (2025)

Ensemble forecasts in reproducing kernel Hilbert space family
by: Dufée, Benjamin, et al.
Published: (2022)

Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models
by: Winkler, Ludwig, et al.
Published: (2024)

Tunable correlation retention: A statistical method for generating synthetic data
by: Jävergård, Nicklas, et al.
Published: (2024)

A note on concentration inequalities for the overlapped batch mean variance estimators for Markov chains
by: Moulines, Eric, et al.
Published: (2025)

Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
by: Gao, Xuefeng, et al.
Published: (2024)

A simple algorithm for output range analysis for deep neural networks
by: Rojas, Helder, et al.
Published: (2024)

Neural stochastic Volterra equations: learning path-dependent dynamics
by: Bergerhausen, Martin, et al.
Published: (2024)

Analysis of Diagnostics (Part II): Prevalence, Linear Independence, and Unsupervised Learning
by: Patrone, Paul N., et al.
Published: (2024)