by instadatahelp | Sep 5, 2023 | AI Blogs
Bayesian Data Selection Eli N. Weinstein, Jeffrey W. Miller; 24(23):1−72, 2023. Abstract To gain insights into complex, high-dimensional data, it is important to identify features of the data that either match or do not match a given model of interest. In order to...
by instadatahelp | Sep 5, 2023 | AI Blogs
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments Authors: Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu; 24(140):1−92, 2023. Abstract This paper introduces jump interval-learning, a method for developing an individualized...
by instadatahelp | Sep 5, 2023 | AI Blogs
Discrete Variational Calculus for Accelerated Optimization Cédric M. Campos, Alejandro Mahillo, David Martín de Diego; 24(25):1−33, 2023. Abstract The field of machine learning has seen significant advancements in gradient-based optimization methods. A recent approach...
by instadatahelp | Sep 5, 2023 | AI Blogs
Optimal Convergence Rates for Distributed Nystroem Approximation Jian Li, Yong Liu, Weiping Wang; 24(141):1−39, 2023. Abstract The distributed kernel ridge regression (DKRR) has demonstrated significant potential in handling complex tasks. However, DKRR only relies on...
by instadatahelp | Sep 5, 2023 | AI Blogs
The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time Authors: Raj Agrawal, Tamara Broderick; Published in 2023, 24(27):1−60. Abstract Identifying a small set of covariates associated with a target response and...
