|
|
|
|
|
Alexander Robitzsch
This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non-d...
ver más
|
|
|
|
|
|
|
|
|
Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed. A new type of soft decision trees is considered, which is similar to the w...
ver más
|
|
|
|
|
|
|
|
|
Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ...
ver más
|
|
|
|
|
|
|
|
|
Heng Liu and Veronica Eliasson
Geometrical shock dynamics (GSD) is a model capable of efficiently predicting the position, shape, and strength of a shock wave. Compared to the traditional Euler method that solves the inviscid Euler equations, GSD is a reduced-order model derived from ...
ver más
|
|
|
|
|
|
|
|
|
Dimitris C. Tsamatsoulis, Christos A. Korologos and Dimitris V. Tsiftsoglou
This study aims to approximate the optimum sulfate content of cement, applying maximization of compressive strength as a criterion for cement produced in industrial mills. The design includes tests on four types of cement containing up to three main comp...
ver más
|
|
|
|