Abstract: Long-term hydropower operation is a complex optimization problem, as the uncertainty of natural inflow should be considered. Sampling stochastic dynamic programming (SSDP) is a method that ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

In the '8_sgd_vs_gd' folder, the 'gd_and_sgd.ipynb' file, there is a logic flaw in the Stochastic Gradient Descent code, Since for SGD, it uses 1 randomly selected ...

This is an mini-course on "Deep Learning for Solving Dynamic Stochastic Models", held from Wednesday, May 22nd, 2024 2 - Friday, May 24th, 2024 at Central-German Doctoral Program Economics, University ...

Robbie has been an avid gamer for well over 20 years. During that time, he's watched countless franchises rise and fall. He's a big RPG fan but dabbles in a little bit of everything. Writing about ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

Abstract: This paper describes a stochastic dynamic programming based approach to solve sensor resource management (SRM) problems such as occur in tracking multiple targets with electronically scanned ...

Stochastic reaction networks are important in understanding complex systems, but representing their solution space through brute force would require an unacceptable computational complexity and ...