The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

Self-supervised reinforcement learning is a technique where agents learn useful representations and skills from the environment through self-generated tasks, such as predicting next states or learning ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-consumptive ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

In this talk, I will present a series of new results in supervised learning from contaminated datasets, based on a general outlier removal algorithm inspired by recent work on learning with ...