IEEE

On the Regret of Model Predictive Control With Imperfect Inputs

Abstract: Implementing model predictive control (MPC) in practice faces many subtle but prevalent problems, including modeling errors, solver errors, and actuator faults. In essence, the real control ...

How a machine learning engineer built a churn prediction model that transformed a subscription platform’s retention strategy

A subscription technology platform with over 100,000 users was losing customers each month despite having access to ...
GitHub

StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing

[2025/12/25] We've released RoboCasa evaluation support, which was trained without pretraining and reached SOTA performance. Check out more details in examples/Robocasa_tabletop. [2025/12/15] ...
IEEE

Practical Nonlinear Model Predictive Control With Kolmogorov–Arnold Network Models

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...