While predicting robot grasps with parallel jaw grippers have been well studied and widely
applied in robot manipulation tasks, the study on natural human grasp generation with a …

In most real world scenarios, a policy trained by reinforcement learning in one environment
needs to be deployed in another, potentially quite different environment. However …

On-device machine learning is becoming a reality thanks to the availability of powerful
hardware and model compression techniques. Typically, these models are pretrained on …

Knowledge distillation (KD) is an effective framework to transfer knowledge from a large-
scale teacher to a compact yet well-performing student. Previous KD practices for pre …

In spite of the great success of deep learning technologies, training and delivery of a
practically serviceable model is still a highly time-consuming process. Furthermore, a …

Abstract Knowledge distillation (KD) is an effective framework to transfer knowledge from a
large-scale teacher to a compact yet well-performing student. Previous KD practices for pre …