Multiple Constraint

Multiple constraint research focuses on improving systems and models by incorporating multiple limitations or requirements simultaneously. Current efforts concentrate on developing algorithms and model architectures that efficiently handle these constraints, including methods leveraging diffusion models, reinforcement learning, and constraint programming techniques applied to diverse areas like image restoration, robotics, and machine learning. This work is significant because effectively managing multiple constraints is crucial for building robust, reliable, and safe systems across various applications, from improving the accuracy and efficiency of machine learning models to ensuring the safety of human-robot interaction.