2024 "excess risk bounds" Papers
9 papers found
A Statistical Framework for Data-dependent Retrieval-Augmented Models
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer
ICML 2024posterarXiv:2408.15399
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data
Yvonne Zhou, Mingyu Liang, Ivan Brugere et al.
ICML 2024posterarXiv:2402.04375
Differentially Private Worst-group Risk Minimization
Xinyu Zhou, Raef Bassily
ICML 2024posterarXiv:2402.19437
Generalization in Kernel Regression Under Realistic Assumptions
Daniel Barzilai, Ohad Shamir
ICML 2024spotlightarXiv:2312.15995
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
ICML 2024posterarXiv:2404.00522
12
citations
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
Changyu Gao, Andrew Lowy, Xingyu Zhou et al.
ICML 2024posterarXiv:2407.09690
RankSEG: A Consistent Ranking-based Framework for Segmentation
Ben Dai, Chunlin Li
ICML 2024posterarXiv:2206.13086
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
Xiaokang Pan, Xingyu Li, Jin Liu et al.
ICML 2024posterarXiv:2407.05286
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
Ming Yang, Xiyuan Wei, Tianbao Yang et al.
ICML 2024posterarXiv:2307.03357