ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...
Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...
Abstract: An attributed network is a network in which in addition to the network structure each node is associated with a set of attributes. Community detection in such networks involves recovering ...
Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...
Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...
Adam is widely used in deep learning as an adaptive optimization algorithm, but it struggles with convergence unless the hyperparameter β2 is adjusted based on the specific problem. Attempts to fix ...
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