3 papers
cs.CR2026
Lap2: Revisiting Laplace DP-SGD for High Dimensions via Majorization Theory
Meisam Mohammady, Qin Yang, Nicholas Stout +4
Differentially Private Stochastic Gradient Descent (DP-SGD) is a cornerstone technique for ensuring privacy in deep learning, widely used in both training from scratch and fine-tun…
cs.LG2025
A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback
Vaneet Aggarwal, Shweta Jain, Subham Pokhriyal +1
We study bi-criteria combinatorial optimization under noisy function evaluations. While resilience and black-box offline-to-online reductions have been studied in single-objective…
cs.LG2024
Stochastic -Submodular Bandits with Full Bandit Feedback
Guanyu Nie, Vaneet Aggarwal, Christopher John Quinn
In this paper, we present the first sublinear -regret bounds for online -submodular optimization problems with full-bandit feedback, where is a corresponding offline appr…