IEEE

Breast Cancer Classification using Machine Learning Techniques with Explainable AI

Abstract: All the symptoms have been analyzed using several machine learning algorithms for diagnosing breast cancer. This paper utilizes the Breast Cancer Wisconsin (Diagnostic) data set to show how ...
EurekAlert!

Multimodal learning-based prediction for nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
IEEE

Trend and Order Features for Semi-Supervised Time-Series Classification via Multitask Learning

Abstract: Multitask learning with a pretext task has excelled in time-series classification task lacking labeled data. The key to multitask learning is to build a pretext task and learn the most ...
Tech Xplore

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
GitHub

Scaling Agentic Reinforcement Learning with a Multi-Turn, Multi-Task Framework

For a minimal example of how to use the environment framework, refer to examples/simple-calculator. For the environment and training data used in our paper, see AgentBench FC. For reproducing the ...