NeurIPS 2025 "stochastic optimization" Papers

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Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization

Khanh-Hung (Bruce) Giang-Tran, Soroosh Shafiee, Nam Ho-Nguyen

NeurIPS 2025posterarXiv:2505.18037

Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates

Andrew Lowy, Daogao Liu

NeurIPS 2025posterarXiv:2506.12994
1
citations

Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks

Heasung Kim, Taekyun Lee, Hyeji Kim et al.

NeurIPS 2025spotlight

Learning-Augmented Online Bidding in Stochastic Settings

Spyros Angelopoulos, Bertrand Simon

NeurIPS 2025posterarXiv:2510.25582

MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization

Da Chang, Ganzhao Yuan

NeurIPS 2025spotlight