EurekAlert!

A review on multi-view learning

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...
Frontiers

Are S.M.A.R.T goals really smart? The psychological effects of goal-setting in a learning task

Aim: Specific, Measurable, Achievable, Realistic, Time-bound (SMART) goals are commonly used in educational settings as a strategy to optimise learning. However, research and theory suggest that such ...

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...

Boston Dynamics' AI-powered humanoid robot is learning to work in a factory

Engineers and computer scientists are developing AI-powered robots that look and act human. Boston Dynamics invited 60 ...
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 ...
IEEE

Self-Supervised Transfer Learning POCS-Net for Seismic Data Interpolation

Abstract: Deep learning has been widely applied to seismic data interpolation. However, most existing methods are based on supervised learning, suffering from limitations such as low generalization ...
IEEE

Dual Task Learning: A Semi-Supervised Approach to Medical Image Joint Segmentation and Registration

Abstract: This work proposes a novel multi-scale attention-enhanced dual-task network, MSA-DTNet, to simultaneously address two critical tasks, segmentation and registration. MSA-DTNet is designed for ...