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Explore dynamic optimization for advertising strategies under uncertain production costs. Learn two approaches for solving two-stage optimal control problems in marketing applications.
Explore operational challenges in integrated mobility systems, focusing on synchronization, sustainability, and ethical considerations for improved user experience and reduced emissions.
Explore a dynamic model for native advertising, examining its effectiveness and impact on media credibility through a Stackelberg differential game approach.
Explorez les stratégies de contrôle distribué hiérarchique pour les systèmes énergétiques, en mettant l'accent sur les agrégateurs et la gestion de la demande distribuée.
Explore Koopman Operator Theory for machine learning of dynamical systems, covering applications in fluid dynamics, power grids, network security, and more.
Explore optimal smart home deployment strategies, including DER investment, management, and tariff considerations. Analyze V2G's role in profitable DER investments using real-world data and mathematical models.
Explore maximum matchings in one-to-one markets with consecutive acceptance intervals. Learn about algorithms, characterizations, and serial dictatorships for optimal matchings.
Explore strategic pricing and environmental quality investment in a two-stage game, analyzing greenwashing's impact on firm strategies, consumer behavior, and market dynamics.
Explore cortical linguistics, neural circuits, and brain dynamics. Discover how mathematical properties and firing rates drive memory, information processing, and motion control, with applications for neurological impairments.
Explore mean-field control techniques for resource allocation in weakly coupled MDPs and restless bandits, focusing on LP-based relaxations and asymptotic optimality.
Explore gradient and Hessian approximations for blackbox optimization, covering theoretical foundations, novel techniques, and practical applications in medical physics.
Explore partial centralization in durable-good supply chains, analyzing equilibrium outcomes and optimal ownership levels based on product durability and decision horizons.
Explore a data-driven matching algorithm for ride pooling, leveraging rank aggregation and machine learning to optimize driver-rider pairings using real-world data from a startup.
Explore limitations of Elo ratings in real-world games. Discover a new disc ranking system with skill and consistency scores. Examine empirical validation on bot and human game data.
Explore an alternative dynamic theory of coalition breakdown, examining endogenous exit problems and characterizing solutions in a linear-quadratic frame with time-invariant sharing rules.
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