Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...

Abstract: This paper investigates the distributed convex optimization problem where dimension of the feasible set is fluctuated. To address this, we formulate an open consensus algorithm that enables ...

Abstract: A recently created optimization algorithm named the Dynamic Hunting Leadership (DHL) algorithm was inspired by the leadership tactics used in hunting operations. The foundation of DHL is the ...