Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games

13 June 2020

Papers citing "Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games"

8 / 8 papers shown

Title
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems Jongyeong Lee Junya Honda Shinji Ito Min-hwan Oh 12 0 0 26 Aug 2025
Hybrid Real- and Complex-valued Neural Network Architecture Alex Young L. V. Fiorio Bo Yang B. Karanov Wim J. van Houtum Ronald M. Aarts 125 0 0 04 Apr 2025
Efficient Learning in Polyhedral Games via Best Response Oracles Darshan Chakrabarti Gabriele Farina Christian Kroer 88 5 0 06 Dec 2023
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits Kiarash Banihashem Mohammadtaghi Hajiaghayi Suho Shin Max Springer 140 2 0 29 Oct 2023
Towards Optimal Randomized Strategies in Adversarial Example Game Jiahao Xie Chao Zhang Weijie Liu Wensong Bai Hui Qian AAML 86 0 0 29 Jun 2023
Optimistic No-regret Algorithms for Discrete Caching N. Mhaisen Abhishek Sinha G. Paschos Georgios Iosifidis 121 13 0 15 Aug 2022
Some performance considerations when using multi-armed bandit algorithms in the presence of missing data Xijin Chen K. M. Lee S. Villar D. Robertson 133 2 0 08 May 2022
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time Anshul Nasery Soumyadeep Thakur Vihari Piratla A. De Sunita Sarawagi AI4TS 94 33 0 15 Aug 2021