Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to artificial intelligence ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Agnik International, a leading data science company with market-leading analytic products, today announced that they are developing a new distributed machine learning architecture based on decades of ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

A University of Idaho lab received $1.3 million from the Department of Defense to study early detection methods for post-traumatic stress disorder and military family stressors using machine learning ...