Federated learning for internet of things: Recent advances, taxonomy, and open challenges
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …
algorithm for both network and application management. However, given the presence of …
A survey on evolutionary neural architecture search
Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …
architectures of DNNs play a crucial role in their performance, which is usually manually …
Symbolic discovery of optimization algorithms
We present a method to formulate algorithm discovery as program search, and apply it to
discover optimization algorithms for deep neural network training. We leverage efficient …
discover optimization algorithms for deep neural network training. We leverage efficient …
Dataset condensation with distribution matching
Computational cost of training state-of-the-art deep models in many learning problems is
rapidly increasing due to more sophisticated models and larger datasets. A recent promising …
rapidly increasing due to more sophisticated models and larger datasets. A recent promising …
Meta-learning in neural networks: A survey
The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent
years. Contrary to conventional approaches to AI where tasks are solved from scratch using …
years. Contrary to conventional approaches to AI where tasks are solved from scratch using …
A comprehensive survey of neural architecture search: Challenges and solutions
Deep learning has made substantial breakthroughs in many fields due to its powerful
automatic representation capabilities. It has been proven that neural architecture design is …
automatic representation capabilities. It has been proven that neural architecture design is …
AutoML: A survey of the state-of-the-art
Deep learning (DL) techniques have obtained remarkable achievements on various tasks,
such as image recognition, object detection, and language modeling. However, building a …
such as image recognition, object detection, and language modeling. However, building a …
MFDNet: Collaborative poses perception and matrix Fisher distribution for head pose estimation
Head pose estimation suffers from several problems, including low pose tolerance under
different disturbances and ambiguity arising from common head pose representation. In this …
different disturbances and ambiguity arising from common head pose representation. In this …
Zero-cost proxies for lightweight nas
Neural Architecture Search (NAS) is quickly becoming the standard methodology to design
neural network models. However, NAS is typically compute-intensive because multiple …
neural network models. However, NAS is typically compute-intensive because multiple …
Neural architecture search without training
The time and effort involved in hand-designing deep neural networks is immense. This has
prompted the development of Neural Architecture Search (NAS) techniques to automate this …
prompted the development of Neural Architecture Search (NAS) techniques to automate this …