This paper addresses the face recognition task for offline mobile applications. Using AutoML
techniques, a novel technological framework is proposed to develop a fast neural network …

In practical decision-making dialogues, reinforcement learning methods face hurdles due to
delays and sparse reward feedback for agents, and in some cases, lack of rewards …

Relying on the availability of massive labeled samples, most neural architecture search
(NAS) methods focus on searching large and complex models; and adopt fixed structures …

Network architecture search (NAS), in particular the differentiable architecture search
(DARTS) method, has shown a great power to learn excellent model architectures on the …

Neural Architecture Search (NAS) has emerged as one of the effective methods to design
the optimal neural network architecture automatically. Although neural architectures have …

Abstract Neural Architecture Search (NAS) aims to automatically produce network
architectures suitable to specific tasks on given datasets. Unlike previous NAS strategies …

Anomaly detection, crucial for identifying issues such as financial fraud or medical
malfunctions, has advanced significantly with machine learning (ML) and deep learning …

A study on the recent trends and progress in the area of Automated Machine Learning
(AutoML) is done in detail in this paper. AutoML deals with the end-to-end automation of …