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Stochastic control
STOCHASTIC CONTROL Contents 1. Introduction 1 2. Mathematical Probability 1 3. Stochastic Calculus 3 4. Diffusions 7 5. the Stoc
MARKOV DECISION PROCESSES Abstract: the Theory of Markov
On Some Recent Aspects of Stochastic Control and Their Applications 507
Stochastic Control
Stochastic Bridges of Linear Systems Yongxin Chen and Tryphon Georgiou
Numerical Methods for Mean Field Games and Mean Field Type Control
Markov Chains
Applications of Stochastic Optimal Control to Economics and Finance
Machine Learning, Lecture 5 Kernel Machines
Mean Field Simulation for Monte Carlo Integration MONOGRAPHS on STATISTICS and APPLIED PROBABILITY
Hidden Markov Model Multiarm Bandits: a Methodology for Beam Scheduling in Multitarget Tracking Vikram Krishnamurthy, Senior Member, IEEE, and Robin J
A Framework of Stochastic Power Management Using Hidden Markov Model
PF-MPC: Particle Filter-Model Predictive Control
Application of Stochastic Control in Optimal Execution Algorithms
On Some Recent Aspects of Stochastic Control and Their Applications∗
Analysis of Solvability and Applications of Stochastic Optimal Control Problems Through Systems of Forward-Backward Stochastic Differential Equations
Stochastic Optimal Control in Mathematical Finance
Stochastic Model Predictive Control with Driver Behavior Learning for Improved Powertrain Control
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Approximate Stochastic Control Based on Deep Learning and Forward Backward Stochastic Differential Equations
Forecast in Capital Markets
Wave Function Method to Forecast Foreign Currencies Exchange Rates at Ultra High Frequency Electronic Trading in Foreign Currencies Exchange Markets
Stochastic Processes, Optimization, and Control Theory Applications In
Stochastic Calculus, Filtering, and Stochastic Control
|||GET||| Introduction to Stochastic Processes 1St Edition
Stochastic Control and Dynamic Asset Allocation∗
A Probabilistic Weak Formulation of Mean Field Games and Applications
Constraint Ornstein-Uhlenbeck Bridges
An Introduction to Stochastic Control
Use of Particle Filters in an Active Control Algorithm for Noisy Nonlinear
Approximate Stochastic Control Based on Deep Learning and Forward Backward Stochastic Differential Equations
Stochastic Optimal Control-A Forward and Backward Sampling Approach
Particle Filtering: a Priori Estimation of Observational Errors of a State-Space Model with Linear Observation Equation †
Optimal Control of Energy Production in a Market with Emission Allowances Leonhard Kunczik University of Wisconsin-Milwaukee
Journal of Mathematical Psychology the Hitchhiker's Guide to Nonlinear
Hidden Markov Models
Mean Field Games and Interacting Particle Systems