Automated machine learning (AutoML) is recognized for its efficiency in facilitating model
development due to its ability to perform tasks autonomously, without constant human …

As machine learning continues to establish its presence on mobile platforms, there arises a
need to evaluate model resource usage across a variety of devices and frameworks. In this …

In recent years, advancements in Artificial Intelligence (AI) have accelerated, edging us
closer to achieving Artificial General Intelligence (AGI). However, alongside these …

Deep Learning (DL) frameworks such as PyTorch and TensorFlow include runtime
infrastructures responsible for executing trained models on target hardware, managing …

Deep learning (dl) models are being widely deployed in real-world applications, but their
usage remains computationally intensive and energy-hungry. While prior work has …