:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Vigouroux, David, Dalmau, Joseba, Béthune, Louis, Boutin, Victor
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2504.07151
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
di: Béthune, Louis, et al.
Pubblicazione: (2025)

Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)
di: Novello, Paul, et al.
Pubblicazione: (2024)

Conformal Semantic Image Segmentation: Post-hoc Quantification of Predictive Uncertainty
di: Mossina, Luca, et al.
Pubblicazione: (2024)

Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures
di: Vesseron, Nina, et al.
Pubblicazione: (2025)

DP-SGD Without Clipping: The Lipschitz Neural Network Way
di: Bethune, Louis, et al.
Pubblicazione: (2023)

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions
di: You, Jingyang, et al.
Pubblicazione: (2025)

The Geometries of Truth Are Orthogonal Across Tasks
di: Azizian, Waiss, et al.
Pubblicazione: (2025)

Improving Out-of-Distribution Detection by Combining Existing Post-hoc Methods
di: Novello, Paul, et al.
Pubblicazione: (2024)

BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
di: Ni, Zelin, et al.
Pubblicazione: (2023)

TaCo: Targeted Concept Erasure Prevents Non-Linear Classifiers From Detecting Protected Attributes
di: Jourdan, Fanny, et al.
Pubblicazione: (2023)

Multivariate Conformal Prediction using Optimal Transport
di: Klein, Michal, et al.
Pubblicazione: (2025)

Decoupled Orthogonal Dynamics: Regularization for Deep Network Optimizers
di: Chen, Hao, et al.
Pubblicazione: (2026)

Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks
di: Bethune, Louis, et al.
Pubblicazione: (2023)

The Data-Quality Illusion: Rethinking Classifier-Based Quality Filtering for LLM Pretraining
di: Saada, Thiziri Nait, et al.
Pubblicazione: (2025)

Scaling Categorical Flow Maps
di: Davis, Oscar, et al.
Pubblicazione: (2026)

Discovering Data Manifold Geometry via Non-Contracting Flows
di: Vigouroux, David, et al.
Pubblicazione: (2026)

Machine Learning Optimized Orthogonal Basis Piecewise Polynomial Approximation
di: Waclawek, Hannes, et al.
Pubblicazione: (2024)

Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
di: Bethune, Louis, et al.
Pubblicazione: (2025)

On the Regularization of Learnable Embeddings for Time Series Forecasting
di: Butera, Luca, et al.
Pubblicazione: (2024)

Improved learning theory for kernel distribution regression with two-stage sampling
di: Bachoc, François, et al.
Pubblicazione: (2023)

Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
di: Thornton, James, et al.
Pubblicazione: (2025)

DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures
di: Gualdoni, Eleonora, et al.
Pubblicazione: (2026)

Basis-to-Basis Operator Learning Using Function Encoders
di: Ingebrand, Tyler, et al.
Pubblicazione: (2024)

Scaling Laws for Optimal Data Mixtures
di: Shukor, Mustafa, et al.
Pubblicazione: (2025)

On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective
di: Serrurier, Mathieu, et al.
Pubblicazione: (2022)

Transmit Weights, Not Features: Orthogonal-Basis Aided Wireless Point-Cloud Transmission
di: Chang, Junlin, et al.
Pubblicazione: (2025)

$\boldsymbolλ$-Orthogonality Regularization for Compatible Representation Learning
di: Ricci, Simone, et al.
Pubblicazione: (2025)

Aircraft Fuel Flow Modelling with Ageing Effects: From Parametric Corrections to Neural Networks
di: Jarry, Gabriel, et al.
Pubblicazione: (2025)

Optimal Splitting of Language Models from Mixtures to Specialized Domains
di: Seto, Skyler, et al.
Pubblicazione: (2026)

On the Generalization Properties of Deep Learning for Aircraft Fuel Flow Estimation Models
di: Jarry, Gabriel, et al.
Pubblicazione: (2024)

Characterizing the Multiclass Learnability of Forgiving 0-1 Loss Functions
di: Trauger, Jacob, et al.
Pubblicazione: (2025)

On the Detection of Aircraft Single Engine Taxi using Deep Learning Models
di: Jarry, Gabriel, et al.
Pubblicazione: (2024)

Learning Unmasking Policies for Diffusion Language Models
di: Jazbec, Metod, et al.
Pubblicazione: (2025)

Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings
di: Jeha, Paul, et al.
Pubblicazione: (2026)

A new model for natural groupings in high-dimensional data
di: Boutin, Mireille, et al.
Pubblicazione: (2019)

Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation
di: Mahon, Louis, et al.
Pubblicazione: (2023)

BasisN: Reprogramming-Free RRAM-Based In-Memory-Computing by Basis Combination for Deep Neural Networks
di: Eldebiky, Amro, et al.
Pubblicazione: (2024)

A Deep Q-Network Based on Radial Basis Functions for Multi-Echelon Inventory Management
di: Cheng, Liqiang, et al.
Pubblicazione: (2024)

Adversarially Robust PAC Learnability of Real-Valued Functions
di: Attias, Idan, et al.
Pubblicazione: (2022)

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
di: Aouali, Imad, et al.
Pubblicazione: (2024)