Researchers use AI to evaluate a systematic framework to describe molecular order in liquid water

Water is the most abundant liquid on Earth's surface, and it is highly anomalous compared with other liquids because it ...
NDTV

Harvard Announces 6 Free Online Courses In AI, Web Development, Programming, Details Here

Harvard Free Online Courses: Harvard University is offering a range of free online courses for learners interested in artificial intelligence, data science, and programming. These self-paced and ...
IEEE

DHS-AE: A Distributed Support Vector Machine With Adaptive Regularization Parameters for Different Data Distributions

Abstract: In distributed machine learning scenarios, the difference in data distribution among different nodes is a key issue that cannot be ignored. However, existing methods make it difficult to ...
Princeton University

Selected Lectures on Statistical Machine Learning

Abstract: The effect of relative entropy asymmetry is analyzed in the context of empirical risk minimization (ERM) with relative entropy regularization (ERM-RER). We show that regularization by ...
Scientific Research Publishing

Belkin, M., Niyogi, P. and Sindhwani, V. (2006) Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples. Journal of Machine Learning ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
Quanta Magazine

What Is Machine Learning?

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...