Image de couverture de livre

Bias-variance decompositions: the exclusive privilege of Bregman divergences

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Heskes, Tom
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Symplectic Bregman divergences
par: Nielsen, Frank
Publié: (2024)

Autoencoders for Anomaly Detection are Unreliable
par: Bouman, Roel, et autres
Publié: (2025)

How to Evaluate Uncertainty Estimates in Machine Learning for Regression?
par: Sluijterman, Laurens, et autres
Publié: (2021)

Curved representational Bregman divergences and their applications
par: Nielsen, Frank
Publié: (2025)

Unsupervised anomaly detection algorithms on real-world data: how many do we need?
par: Bouman, Roel, et autres
Publié: (2023)

Calibeating for general proper losses: A Bregman divergence approach
par: Fichtl, Maximilian, et autres
Publié: (2026)

Composite Quantile Regression With XGBoost Using the Novel Arctan Pinball Loss
par: Sluijterman, Laurens, et autres
Publié: (2024)

A direct proof of a unified law of robustness for Bregman divergence losses
par: Das, Santanu, et autres
Publié: (2024)

A Generalized Bias-Variance Decomposition for Bregman Divergences
par: Pfau, David
Publié: (2025)

Generalising maximum mean discrepancy: kernelised functional Bregman divergences
par: Tsuchida, Russell, et autres
Publié: (2026)

Bregman-Hausdorff divergence: strengthening the connections between computational geometry and machine learning
par: Pham, Tuyen, et autres
Publié: (2025)

Unsupervised domain adaptation by learning using privileged information
par: Breitholtz, Adam, et autres
Publié: (2023)

Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
par: Kumar, Shivam, et autres
Publié: (2025)

Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series Measurements
par: Bouman, Roel, et autres
Publié: (2024)

Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid
par: van Nooten, Charlotte Cambier, et autres
Publié: (2023)

LSTSVR-PI: Least square twin support vector regression with privileged information
par: Kumari, Anuradha, et autres
Publié: (2023)

Rethinking Bregman Divergences in Kronecker-Factored Optimizers
par: Liu, Bing, et autres
Publié: (2026)

Stream separation improves Bregman conditioning in transformers
par: Kerce, James Clayton
Publié: (2026)

High-dimensional online learning via asynchronous decomposition: Non-divergent results, dynamic regularization, and beyond
par: Liu, Shixiang, et autres
Publié: (2026)

Graders should cheat: privileged information enables expert-level automated evaluations
par: Zhou, Jin Peng, et autres
Publié: (2025)

Adaptive Regularization for Sparsity Control in Bregman-Based Optimizers
par: Aloradi, Ahmad, et autres
Publié: (2026)

Bregman Douglas-Rachford Splitting Method
par: Ma, Shiqian, et autres
Publié: (2025)

Geometric Convergence Analysis of Variational Inference via Bregman Divergences
par: Bohara, Sushil, et autres
Publié: (2025)

Online Nonconvex Bilevel Optimization with Bregman Divergences
par: Bohne, Jason, et autres
Publié: (2024)

Learning density ratios in causal inference using Bregman-Riesz regression
par: Hines, Oliver J., et autres
Publié: (2025)

External Division of Two Bregman Proximity Operators for Poisson Inverse Problems
par: Haishima, Kazuki, et autres
Publié: (2026)

k-MLE, k-Bregman, k-VARs: Theory, Convergence, Computation
par: Yue, Zuogong, et autres
Publié: (2024)

Robust Sublinear Convergence Rates for Iterative Bregman Projections
par: Peyré, Gabriel
Publié: (2026)

Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities
par: Gebre, Binyam, et autres
Publié: (2024)

Coreset selection for the Sinkhorn divergence and generic smooth divergences
par: Kokot, Alex, et autres
Publié: (2025)

On the effectiveness of multimodal privileged knowledge distillation in two vision transformer based diagnostic applications
par: Baur, Simon, et autres
Publié: (2025)

An Accelerated Alternating Partial Bregman Algorithm for ReLU-based Matrix Decomposition
par: Wang, Qingsong, et autres
Publié: (2025)

Lower Difficulty and Better Robustness: A Bregman Divergence Perspective for Adversarial Training
par: Wu, Zihui, et autres
Publié: (2022)

Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning
par: Jacobs, Tom, et autres
Publié: (2026)

Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training
par: Sander, Tom, et autres
Publié: (2024)

Bregman Centroid Guided Cross-Entropy Method
par: Gu, Yuliang, et autres
Publié: (2025)

Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
par: Jacobs, Tom, et autres
Publié: (2025)

Hyperbolic Aware Minimization: Implicit Bias for Sparsity
par: Jacobs, Tom, et autres
Publié: (2025)

A Bregman firmly nonexpansive proximal operator for baryconvex optimization
par: Achab, Mastane
Publié: (2024)

Online Bayesian Imbalanced Learning with Bregman-Calibrated Deep Networks
par: Alsulaimawi, Zahir
Publié: (2026)