Results 61 to 70 of about 56,420 (266)
Functional Causal Bayesian Optimization
CoRR, 2023 We propose functional causal Bayesian optimization (fCBO), a method for finding interventions that optimize a target variable in a known causal graph. fCBO extends the CBO family of methods to enable functional interventions, which set a variable to be a deterministic function of other variables in the graph.
Limor Gultchin +3 more
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A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Компютерні системи та інформаційні технологіїThe performance of machine learning models depends on the selection and tuning of hyperparameters. As a widely used gradient boosting method, XGBoost relies on optimal hyperparameter configurations to balance model complexity, prevent overfitting, and ...
Микола ЗЛОБІН +1 more
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 AlphaGo
CoRR, 2018 During the development of AlphaGo, its many hyper-parameters were tuned with Bayesian optimization multiple times. This automatic tuning process resulted in substantial improvements in playing strength. For example, prior to the match with Lee Sedol, we tuned the latest AlphaGo agent and this improved its win-rate from 50% to 66.5% in self-play games ...
Yutian Chen 0001 +6 more
openaire +2 more sources
Trajectories of Physical Function in Canadian Children With Juvenile Idiopathic Arthritis
Arthritis Care &Research, EarlyView.Objective We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham +81 more
wiley +1 more source
Data-efficient optimization of thermally-activated polymer actuators through machine learning
Materials & DesignFor applications in soft robotics and smart textiles, thermally-activated, twisted, and coiled polymer actuators can offer high mechanical actuation with proper optimization of their processing conditions. However, optimization is often aggravated by the
Yuhao Zhang +10 more
doaj +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Optimizing Bayesian optimization
, 2018 We are concerned primarily with improving the practical applicability of Bayesian optimization. We make contributions in three key areas. We develop an intuitive online stopping criterion, allowing only as many steps as necessary to achieve the desired target to be taken. By combining this with intelligent online switching between acquisition functions
openaire +3 more sources