Results 11 to 20 of about 108,723 (292)
Stochastic Approximations and Differential Inclusions; Part II: Applications [PDF]
Mathematics of Operations Research, 2005 We apply the theoretical results on ``stochastic approximations and differential inclusions'' developed in Benaïm Hofbauer and Sorin (2003) to several adaptive processes used in game theory including: classical and generalized approachability, no-regrets
Benaïm, Michel +2 more
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Asynchronous stochastic approximation with differential inclusions [PDF]
Stochastic Systems, 2012 The asymptotic pseudo-trajectory approach to stochastic approximation of Benaïm, Hofbauer and Sorin is extended for asynchronous stochastic approximations with a set-valued mean field.
David S. Leslie, Steven Perkins
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Stochastic differential inclusions with Hilfer fractional derivative
Annals of the University of Craiova, Mathematics and Computer Science Series, 2022 In this paper, we study the existence of mild solutions of Hilfer fractional stochastic differential inclusions driven by sub fractional Brownian motion in the cases when the multivalued map is convex and non convex.
Meryem Chaouche, Toufik Guendouzi
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Stochastic approximation with discontinuous dynamics, differential inclusions, and applications
The Annals of Applied Probability, 2023 This work develops new results for stochastic approximation algorithms. The emphases are on treating algorithms and limits with discontinuities. The main ingredients include the use of differential inclusions, set-valued analysis, and non-smooth analysis, and stochastic differential inclusions. Under broad conditions, it is shown that a suitably scaled
Nguyen, Nhu, Yin, George
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Smale Strategies for Network Prisoner's Dilemma Games [PDF]
, 2015 Smale's approach \cite{Smale80} to the classical two-players repeated Prisoner's Dilemma game is revisited here for $N$-players and Network games in the framework of Blackwell's approachability, stochastic approximations and differential ...
Behrstock, Kashi +2 more
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Stochastic Langevin Differential Inclusions with Applications to Machine Learning
CoRR, 2022 Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a conceptual model of the stochastic gradient flow in training over-parameterized models.
Fabio V. Difonzo +2 more
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Alexandria Engineering Journal, 2023 Fractional calculus is now used to accurately depict a range of real occurrences because it can explain the “long-tail memory” phenomena that have been seen through empirical research. Standard differential equations with integer order derivatives cannot
Yong-Ki Ma +7 more
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Известия высших учебных заведений. Поволжский регион: Физико-математические науки, 2021 Background. E. Nelson [1-3] introduced derivatives on the average in the works and over time, they began to be studied as a separate class of stochastic differential equations.
O.O. Zheltikova
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THE BOUNDEDNESS OF SOLUTIONS FOR STOCHASTIC DIFFERENTIAL INCLUSIONS [PDF]
Bulletin of the Korean Mathematical Society, 2003 Let \((\Omega,{\mathcal F},P)\) be a complete probability with a right-continuous increasing family \(({\mathcal F_t})_{t\geq 0}\) of \(\sigma\)-fields each containing all \(P\)-nul sets. Let \(B= (B_t)_{t\geq 0}\) be an \(r\)-dimensional \(({\mathcal F}_t)\)-Brownian motion.
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On the Relationship Between Solutions of Stochastic and Random Differential Inclusions [PDF]
Stochastic Analysis and Applications, 2003 Some results on the relationship of the solutions of a stochastic di erential inclusion and the corresponding random di erential inclusion obtained after a change of variable are proved. As a consequence, we obtain the pullback convergence of the solutions of the stochastic inclusion to a compact random set.
Caraballo Garrido, Tomás +2 more
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