Results 21 to 30 of about 289,279 (277)
Application of Bayesian optimized XGBoost in seismic interpretation of small-scale faults
Meitan xuebao, 2023 In order to further improve the identification accuracy of small-scale faults in seismic interpretation, Bayesian optimized extreme gradient boosting (XGBoost) model was constructed to recognize small-scale faults across coalbeds using reduced seismic ...
Changwei DING +3 more
doaj +1 more source
Unscented Bayesian Optimization for Safe Robot Grasping [PDF]
, 2016 We address the robot grasp optimization problem of unknown objects considering uncertainty in the input space. Grasping unknown objects can be achieved by using a trial and error exploration strategy.
Bernardino, Alexandre +3 more
core +2 more sources
Bayesian Optimization for Conformer Generation [PDF]
Journal of Cheminformatics, 2018 Generating low-energy molecular conformers is a key task for many areas of computational chemistry, molecular modeling and cheminformatics. Most current conformer generation methods primarily focus on generating geometrically diverse conformers rather than finding the most probable or energetically lowest minima.
Lucian Chan +2 more
openaire +4 more sources
Application of Improved LightGBM Model in Blood Glucose Prediction
Applied Sciences, 2020 In recent years, with increasing social pressure and irregular schedules, many people have developed unhealthy eating habits, which has resulted in an increasing number of patients with diabetes, a disease that cannot be cured under the current medical ...
Yan Wang, Tao Wang
doaj +1 more source
A Bayesian approach to constrained single- and multi-objective optimization [PDF]
, 2016 This article addresses the problem of derivative-free (single- or multi-objective) optimization subject to multiple inequality constraints. Both the objective and constraint functions are assumed to be smooth, non-linear and expensive to evaluate.
A Bayesian +7 more
core +5 more sources
Applied Sciences, 2022 The 3D body scan technology has recently innovated the way of measuring human bodies and generated a large volume of body measurements. However, one inherent issue that plagues the use of the resultant database is the missing data usually caused by using
Xuebo Liu, Yingying Wu, Hongyu Wu
doaj +1 more source
Novel Ensemble Tree Solution for Rockburst Prediction Using Deep Forest
Mathematics, 2022 The occurrence of rockburst can cause significant disasters in underground rock engineering. It is crucial to predict and prevent rockburst in deep tunnels and mines. In this paper, the deficiencies of ensemble learning algorithms in rockburst prediction
Diyuan Li +4 more
doaj +1 more source
Bayesian optimization in ab initio nuclear physics [PDF]
, 2019 Theoretical models of the strong nuclear interaction contain unknown coupling constants (parameters) that must be determined using a pool of calibration data.
Dimitrakakis, C. +7 more
core +3 more sources
Fair Bayesian Optimization [PDF]
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 2021 Given the increasing importance of machine learning (ML) in our lives, several algorithmic fairness techniques have been proposed to mitigate biases in the outcomes of the ML models. However, most of these techniques are specialized to cater to a single family of ML models and a specific definition of fairness, limiting their adaptibility in practice ...
Perrone, Valerio +5 more
openaire +2 more sources
Exploration of outliers in strength–ductility relationship of dual-phase steels
Science and Technology of Advanced Materials: Methods, 2022 To overcome the trade-off relationship between tensile strength and elongation of dual-phase steels, three exploratory techniques were utilized: Bayesian optimization (BO), BoundLess Objective-free eXploration (BLOX), and one-class support vector machine
Takayuki Shiraiwa +3 more
doaj +1 more source