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Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization
(Ieee, 2020-01-01)
Restricted Boltzmann Machines (RBM) are stochastic neural networks mainly used for image reconstruction and unsupervised feature learning. An enhanced version, the temperature-based RBM (T-RBM), considers a new temperature ...
A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes
(SPRINGER, 2009)
We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, ...
Towards assessing the electricity demand in Brazil: Data-driven analysis and ensemble learning models
(2020-01-01)
The prediction of electricity generation is one of the most important tasks in the management of modern energy systems. Improving the assertiveness of this prediction can support government agencies, electric companies, ...
Online Sequential Extreme Learning Machine for Vibration-Based Damage Assessment Using Transmissibility Data
(ASCE-Amer Soc Civil Engineers, 2016)
Traditional vibration-based damage assessment approaches include the use of feed-forward neural networks. However, the slow learning speed of these networks and the large number of parameters that need to be tuned have ...
Cutpoint selection for discretizing a continuous covariate for generalized estimating equations
(ELSEVIER SCIENCE BV, 2011)
We consider consider the problem of dichotomizing a continuous covariate when performing a regression analysis based on a generalized estimation approach. The problem involves estimation of the cutpoint for the covariate ...
On-line method for optimal tuning of PID controllers using standard OPC interfaceMétodo on-line para sintonización óptima de controladores PID utilizando interface estándar OPC
(Corporación Universidad de la CostaColombia, 2023)
Tuning of adaptive weight depth map generation algorithms: Exploratory data analysis and design of computer experiments (DOCE)
(SPRINGER, 2013-09-01)
In depth map generation algorithms, parameters settings to yield an accurate disparity map estimation are usually chosen empirically or based on unplanned experiments. Algorithms' performance is measured based on the ...
Gene Expression Complex Networks: Synthesis, Identification, and Analysis
(MARY ANN LIEBERT INC, 2011)
Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays ...