IEEE

Beyond AutoML: Mindful and Actionable AI and AutoAI With Mind and Action

Abstract: Automated machine learning (AutoML), in particular, neural architecture search (NAS) for deep learning, has ignited the fast-paced development of automating data science (AutoDS) and ...
IEEE

AutoML With Parallel Genetic Algorithm for Fast Hyperparameters Optimization in Efficient IoT Time Series Prediction

Abstract: With the development of artificial intelligence and the improvement of hardware computing power, deep learning models have become widely used in the Internet of Things (IoT) field, ...
GitHub

Jaynam-Panchal/automl-multi-agent

An intelligent AutoML system that uses multiple specialized AI agents to automatically build, optimize, and explain machine learning models. automl/ ├── agents/ # Specialized AI agents │ ├── ...
GitHub

Learning Synthetic Environments and Reward Networks for Reinforcement Learning

We explore meta-learning agent-agnostic neural Synthetic Environments (SEs) and Reward Networks (RNs) for efficiently training Reinforcement Learning (RL) agents. While an SE acts as a full proxy to a ...