Results 11 to 20 of about 16,029 (238)
Stochastic Approximations and Differential Inclusions [PDF]
SIAM Journal on Control and Optimization, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Benaïm, Michel +2 more
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Stochastic Approximations and Differential Inclusions, Part II: Applications [PDF]
Mathematics of Operations Research, 2006 We apply the theoretical results on “stochastic approximations and differential inclusions” developed in Benaïm et al. [M. Benaïm, J. Hofbauer, S. Sorin. 2005. Stochastic approximations and differential inclusions. SIAM J. Control Optim. 44 328–348] to several adaptive processes used in game theory, including classical and generalized approachability,
Benaïm, Michel +2 more
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Mathematics, 2022 The work is dedicated to mathematical modelling of random diffusion flows of admixture particles in a two-phase stratified strip with stochastic disposition of phases and random thickness of inclusion-layers.
Olha Chernukha +4 more
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Inferring temporal dynamics from cross-sectional data using Langevin dynamics
Royal Society Open Science, 2021 Cross-sectional studies are widely prevalent since they are more feasible to conduct compared with longitudinal studies. However, cross-sectional data lack the temporal information required to study the evolution of the underlying dynamics. This temporal
Pritha Dutta +4 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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Remote Sensing, 2021 The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis.
Ester Carbó +5 more
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Applied Sciences, 2022 The optimal methods for the synthesis of mechanisms in rehabilitation usually require solving constrained optimization problems. Metaheuristic algorithms are frequently used to solve these problems with the inclusion of Constraint-Handling Techniques ...
José Saúl Muñoz-Reina +3 more
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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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A market model: uncertainty and reachable sets
International Journal for Simulation and Multidisciplinary Design Optimization, 2015 Uncertain parameters are always present in models that include human factor. In marketing the uncertain consumer behavior makes it difficult to predict the future events and elaborate good marketing strategies.
Raczynski Stanislaw
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