distributionally robust optimization 1minimax 1nonconvex-nonconcave 1smoothing methods 1stochastic optimization 1
From the 1 of 3 linked papers with an AI index.
3 papers
math.OC2026
A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization
Wei Liu, Muhammad Khan, Gabriel Mancino-Ball +1
The paper introduces a stochastic smoothing proximal gradient algorithm for solving nonconvex‑nonconcave minimization‑expectation‑maximization (minEmax) problems, providing converg…
cs.CV2026
Advancing Reliable Synthetic Video Detection: Insights from the SAFE Challenge
Kirill Trapeznikov, Gabriel Mancino-Ball, Jonathan Li +9
The proliferation of generative video technologies has intensified the need for reliable methods to detect and characterize synthetic media. To address this challenge, we organized…
math.OC2025
Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks
Molly Noel, Gabriel Mancino-Ball, Yangyang Xu
Graph convolutional networks (GCNs) are a powerful tool for graph representation learning. Due to the recursive neighborhood aggregations employed by GCNs, efficient training metho…