NeurIPS "stochastic optimization" Papers
9 papers found
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
Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules
Gonzalo E. Constante, Hao Chen, Can Li
NeurIPS 2025posterarXiv:2505.13858
4
citations
Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto et al.
NeurIPS 2025posterarXiv:2508.15071
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
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
Shaocong Ma, Heng Huang
NeurIPS 2025spotlightarXiv:2510.19953
2
citations
Quantum speedup of non-linear Monte Carlo problems
Jose Blanchet, Yassine Hamoudi, Mario Szegedy et al.
NeurIPS 2025spotlightarXiv:2502.05094