In this paper, we propose a user-friendly estimator to implement the method of difference-in-differences with ordinal ...
Cisco Talos Researcher Reveals Method That Causes LLMs to Expose Training Data Your email has been sent In this TechRepublic interview, Cisco researcher Amy Chang details the decomposition method and ...
Abstract: This paper introduces a novel framework for Archetypal Analysis (AA) tailored to ordinal data, particularly from questionnaires. Unlike existing methods, the proposed method, Ordinal ...
A research team has developed a novel method for estimating the predictability of complex dynamical systems. Their work, "Time-lagged recurrence: A data-driven method to estimate the predictability of ...
ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL, USA. Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional ...
An intelligent inversion framework for soil parameters in deep excavations is established by using BIM technology, finite difference method (FDM), and nondominated sorting genetic algorithm II ...
Test-time Adaptive Optimization can be used to increase the efficiency of inexpensive models, such as Llama, the company said. Data lakehouse provider Databricks has unveiled a new large language ...
Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback