by instadatahelp | Aug 29, 2023 | AI Blogs
The d-Separation Criterion in Categorical Probability Tobias Fritz, Andreas Klingler; 24(46):1−49, 2023. Abstract The d-separation criterion is used to determine the compatibility of a joint probability distribution with a directed acyclic graph by examining certain...
by instadatahelp | Aug 29, 2023 | AI Blogs
The paper titled “Impact of geolocation data on augmented reality usability: A comparative user test” was authored by Julien Mercier (Lab-Sticc_decide, Ubs, Hes-So, Hes-So, Heig-Vd), N. Chabloz (Hes-So, Heig-Vd, Hes-So), G. Dozot (Hes-So, Heig-Vd, Hes-So),...
by instadatahelp | Aug 29, 2023 | AI Blogs
Statistical Comparisons of Classifiers by Generalized Stochastic Dominance Authors: Christoph Jansen, Malte Nalenz, Georg Schollmeyer, Thomas Augustin; 24(231):1−37, 2023. Abstract Comparing classifiers across multiple data sets and criteria is a crucial question in...
by instadatahelp | Aug 29, 2023 | AI Blogs
Collaborative Filtering (CF) has been successfully utilized to assist users in discovering items of interest. However, existing CF methods are hindered by the issue of noisy data, which negatively affects the quality of recommendations. To address this problem,...
by instadatahelp | Aug 29, 2023 | AI Blogs
Contextual Stochastic Block Model: Sharp Thresholds and Contiguity Chen Lu, Subhabrata Sen; 24(54):1−34, 2023. Abstract This study focuses on community detection in the “contextual stochastic block model” (Yan and Sarkar, 2020; Deshpande et al., 2018)....
by instadatahelp | Aug 29, 2023 | AI Blogs
Lifted Bregman Training of Neural Networks Xiaoyu Wang, Martin Benning; 24(232):1−51, 2023. Abstract A new mathematical formulation is introduced for training feed-forward neural networks with potentially non-smooth proximal maps as activation functions. This...
