Papers citing 'A Generalized Bias-Variance Decomposition for Bregman Divergences'

Title
Why Machine Learning Models Fail to Fully Capture Epistemic Uncertainty Sebastián Jiménez Mira Jürgens Willem Waegeman UD PER 488 2 0 29 May 2025
Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Michael Kirchhof Gjergji Kasneci Enkelejda Kasneci LLMAG 234 8 0 28 May 2025
Proper scoring rules for estimation and forecast evaluation Kartik Waghmare Johanna Ziegel AI4TS 471 8 0 02 Apr 2025
MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records Zekai Wang Tieming Liu B. Yao 389 2 0 30 Jun 2024
Reassessing How to Compare and Improve the Calibration of Machine Learning Models M. Chidambaram Rong Ge 269 4 0 06 Jun 2024
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks Bálint Mucsányi Michael Kirchhof Seong Joon Oh UQCV BDL OODD 1.1K 56 1 29 Feb 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 290 3 0 16 Feb 2024
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic DatasetsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Ossi Raisa Antti Honkela 293 1 0 06 Feb 2024
It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models Lin Chen Michal Lukasik Wittawat Jitkrittum Chong You Sanjiv Kumar 230 1 0 13 Oct 2023
Bias-Variance Decompositions for Margin LossesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Danny Wood Tingting Mu Gavin Brown UQCV 76 6 0 26 Apr 2022
Small Footprint Multi-channel ConvMixer for Keyword Spotting with Centroid Based Awareness Dianwen Ng Jing Pang Yanghua Xiao Biao Tian Qiang Fu Eng Siong Chng 129 2 0 11 Apr 2022
Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent -- an Open Problem Rémi Le Priol Frederik Kunstner Damien Scieur Damien Scieur 102 1 0 12 Nov 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition Yaodong Yu Zitong Yang Guang Cheng Jacob Steinhardt Yi-An Ma 202 18 0 17 Mar 2021
Rethinking Bias-Variance Trade-off for Generalization of Neural NetworksInternational Conference on Machine Learning (ICML), 2020 Zitong Yang Yaodong Yu Chong You Jacob Steinhardt Yi-An Ma 282 208 0 26 Feb 2020