by instadatahelp | Aug 31, 2023 | AI Blogs
Buffered Asynchronous SGD for Byzantine Learning Yi-Rui Yang, Wu-Jun Li; 24(204):1−62, 2023. Abstract Distributed learning has become a popular area of research due to its wide range of applications in cluster-based large-scale learning, federated learning, edge...
by instadatahelp | Aug 31, 2023 | AI Blogs
Expected goal models have become popular in recent years, but their interpretability is often limited, particularly when trained using black-box methods. To address this issue, explainable artificial intelligence tools have been developed to enhance model transparency...
by instadatahelp | Aug 31, 2023 | AI Blogs
Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size Xiaoyu Wang, Ya-xiang Yuan; 24(48):1−49, 2023. Abstract This paper introduces a novel step-size framework for the stochastic gradient descent (SGD) method, called bandwidth-based step sizes....
by instadatahelp | Aug 31, 2023 | AI Blogs
We present the utilization of a reduction property found in the penalty-based formulation of pseudo-Boolean polynomials as a means to reduce dimensionality in cluster analysis procedures. Through our experiments, we demonstrate that multidimensional datasets, such as...
by instadatahelp | Aug 31, 2023 | AI Blogs
L0Learn: A Scalable Package for Sparse Learning using L0 Regularization Hussein Hazimeh, Rahul Mazumder, Tim Nonet; 24(205):1−8, 2023. Abstract This article introduces L0Learn, an open-source package designed for sparse linear regression and classification using L0...
by instadatahelp | Aug 31, 2023 | AI Blogs
In this work, we introduce a new version of the best-arm identification problem called best-arm identification under mediators’ feedback (BAI-MF). In traditional BAI problems, the goal is to find the arm with the highest expected reward. However, this framework...
