NEURIPS 2025 "non-convex optimization" Papers

Balancing Gradient and Hessian Queries in Non-Convex Optimization

Deeksha Adil, Brian Bullins, Aaron Sidford et al.

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

Andrew Lowy, Daogao Liu

Efficient Adaptive Federated Optimization

Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.

Efficient Federated Learning against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients

Shiyuan Zuo, Xingrun Yan, Rongfei Fan et al.

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains

Dongzhe Zheng, Wenjie Mei

Non-convex entropic mean-field optimization via Best Response flow

Razvan-Andrei Lascu, Mateusz Majka

Non-Convex Tensor Recovery from Tube-Wise Sensing

Tongle Wu, Ying Sun

Quantum Speedups for Minimax Optimization and Beyond

Chengchang Liu, Zongqi Wan, Institute of Computing Jialin Zhang et al.

Spike-timing-dependent Hebbian learning as noisy gradient descent

Niklas Dexheimer, Sascha Gaudlitz, Johannes Schmidt-Hieber

Trained Mamba Emulates Online Gradient Descent in In-Context Linear Regression

Jiarui Jiang, Wei Huang, Miao Zhang et al.

Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training