Gabriel Mancino-Ball

According to our database, Gabriel Mancino-Ball authored at least 6 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization.

Wei Liu, Khan Muhammad, Gabriel Mancino-Ball, Yangyang Xu

CoRR, February, 2025

2024

BoFire: Bayesian Optimization Framework Intended for Real Experiments.

Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte, Gabriel Mancino-Ball, Benjamin Schiller, Simon Sung, Julian Keupp, Aaron Osburg, Toby Boyne, Ruth Misener, Rosona Eldred, Wagner Steuer Costa, Chrysoula Kappatou, Robert M. Lee, Dominik Linzner, David Walz, Niklas Wulkow, Behrang Shafei

CoRR, 2024

Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization.

Xuan Zhang, Gabriel Mancino-Ball, Necdet Serhat Aybat, Yangyang Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Decentralized Primal-Dual Framework for Non-Convex Smooth Consensus Optimization.

Gabriel Mancino-Ball, Yangyang Xu, Jie Chen

IEEE Trans. Signal Process., 2023

Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems.

Gabriel Mancino-Ball, Yangyang Xu

CoRR, 2023

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization.

Gabriel Mancino-Ball, Shengnan Miao, Yangyang Xu, Jie Chen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023