Presents a stochastic extragradient algorithm for variational inequalities with Markovian noise, proving convergence under L-Lipschitzness, strong monotonicity, and noise bounded only at the optimum, plus experiments on mixing time.
Vapnik.Statistical Learning Theory
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Methods for Solving Variational Inequalities with Markovian Stochasticity
Presents a stochastic extragradient algorithm for variational inequalities with Markovian noise, proving convergence under L-Lipschitzness, strong monotonicity, and noise bounded only at the optimum, plus experiments on mixing time.