:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Stewart, Lawrence, Bach, Francis, Berthet, Quentin
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.02996
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
by: Dubois-Taine, Benjamin, et al.
Published: (2022)

Generalization Properties of Score-matching Diffusion Models for Intrinsically Low-dimensional Data
by: Chakraborty, Saptarshi, et al.
Published: (2026)

Optimizing Estimators of Squared Calibration Errors in Classification
by: Gruber, Sebastian G., et al.
Published: (2024)

Super-Level-Set Regression: Conditional Quantiles via Volume Minimization
by: Braun, Sacha, et al.
Published: (2026)

On the Effectiveness of the z-Transform Method in Quadratic Optimization
by: Bach, Francis
Published: (2025)

A Convex Loss Function for Set Prediction with Optimal Trade-offs Between Size and Conditional Coverage
by: Bach, Francis
Published: (2025)

Control Variate Score Matching for Diffusion Models
by: Kahouli, Khaled, et al.
Published: (2025)

Optimal Stopping in Latent Diffusion Models
by: Wu, Yu-Han, et al.
Published: (2025)

Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)

Minimum Volume Conformal Sets for Multivariate Regression
by: Braun, Sacha, et al.
Published: (2025)

A Spectral Framework for Closed-Form Relative Density Estimation
by: Bach, Francis
Published: (2026)

Nonparametric Linear Feature Learning in Regression Through Regularisation
by: Follain, Bertille, et al.
Published: (2023)

MIND: Monge Inception Distance for Generative Models Evaluation
by: Berthet, Quentin, et al.
Published: (2026)

Sampling Binary Data by Denoising through Score Functions
by: Bach, Francis, et al.
Published: (2025)

Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity
by: Beyler, Eliot, et al.
Published: (2025)

Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance
by: Beyler, Eliot, et al.
Published: (2025)

Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods
by: Follain, Bertille, et al.
Published: (2024)

Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf's Law
by: Kunstner, Frederik, et al.
Published: (2025)

The Galerkin method beats Graph-Based Approaches for Spectral Algorithms
by: Cabannes, Vivien, et al.
Published: (2023)

The compressible Neural Particle Method for Simulating Compressible Viscous Fluid Flows
by: Shibukawa, Masato, et al.
Published: (2025)

Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
by: Holzmüller, David, et al.
Published: (2023)

An Uncertainty Principle for Linear Recurrent Neural Networks
by: François, Alexandre, et al.
Published: (2025)

Spectral structure learning for clinical time series
by: Lerner, Ivan, et al.
Published: (2025)

Variational Inference on the Boolean Hypercube with the Quantum Entropy
by: Beyler, Eliot, et al.
Published: (2024)

Backward Conformal Prediction
by: Gauthier, Etienne, et al.
Published: (2025)

E-Values Expand the Scope of Conformal Prediction
by: Gauthier, Etienne, et al.
Published: (2025)

Statistical Collusion by Collectives on Learning Platforms
by: Gauthier, Etienne, et al.
Published: (2025)

Adaptive Coverage Policies in Conformal Prediction
by: Gauthier, Etienne, et al.
Published: (2025)

Explaining and Preventing Alignment Collapse in Iterative RLHF
by: Gauthier, Etienne, et al.
Published: (2026)

Generation of non-stationary stochastic fields using Generative Adversarial Networks
by: Abdellatif, Alhasan, et al.
Published: (2022)

Bridged Clustering: Semi-Supervised Sparse Bridging
by: Ye, Patrick Peixuan, et al.
Published: (2025)

Implicit Diffusion: Efficient Optimization through Stochastic Sampling
by: Marion, Pierre, et al.
Published: (2024)

Bridging the Theoretical Gap in Randomized Smoothing
by: Delattre, Blaise, et al.
Published: (2025)

Statistical and Geometrical properties of regularized Kernel Kullback-Leibler divergence
by: Chazal, Clémentine, et al.
Published: (2024)

Fair Federated Data Clustering through Personalization: Bridging the Gap between Diverse Data Distributions
by: Gupta, Shivam, et al.
Published: (2024)

Conformal Prediction via Regression-as-Classification
by: Guha, Etash, et al.
Published: (2024)

Towards Build Optimization Using Digital Twins
by: Aïdasso, Henri, et al.
Published: (2025)

On Approaches to Building Surrogate ODE Models for Diffusion Bridges
by: Khilchuk, Maria, et al.
Published: (2025)

Physics-informed kernel learning
by: Doumèche, Nathan, et al.
Published: (2024)

Convergence of Shallow ReLU Networks on Weakly Interacting Data
by: Dana, Léo, et al.
Published: (2025)