Zobrazeno 1 - 10
of 245
pro vyhledávání: '"Tax, David"'
Conformal prediction, which makes no distributional assumptions about the data, has emerged as a powerful and reliable approach to uncertainty quantification in practical applications. The nonconformity measure used in conformal prediction quantifies
Externí odkaz:
http://arxiv.org/abs/2410.09894
This study investigates scheduling strategies for the stochastic resource-constrained project scheduling problem with maximal time lags (SRCPSP/max)). Recent advances in Constraint Programming (CP) and Temporal Networks have reinvoked interest in eva
Externí odkaz:
http://arxiv.org/abs/2409.09107
Evaluating anomaly detection algorithms in time series data is critical as inaccuracies can lead to flawed decision-making in various domains where real-time analytics and data-driven strategies are essential. Traditional performance metrics assume i
Externí odkaz:
http://arxiv.org/abs/2405.12096
Anomaly detection in time series data is crucial across various domains. The scarcity of labeled data for such tasks has increased the attention towards unsupervised learning methods. These approaches, often relying solely on reconstruction error, ty
Externí odkaz:
http://arxiv.org/abs/2405.07509
When optimizing problems with uncertain parameter values in a linear objective, decision-focused learning enables end-to-end learning of these values. We are interested in a stochastic scheduling problem, in which processing times are uncertain, whic
Externí odkaz:
http://arxiv.org/abs/2312.03492
Publikováno v:
BNAIC/BENELEARN 2023
Unlike the more commonly analyzed ECG or PPG data for activity classification, heart rate time series data is less detailed, often noisier and can contain missing data points. Using the BigIdeasLab_STEP dataset, which includes heart rate time series
Externí odkaz:
http://arxiv.org/abs/2311.13285
Photoplethysmography (PPG) signals, typically acquired from wearable devices, hold significant potential for continuous fitness-health monitoring. In particular, heart conditions that manifest in rare and subtle deviating heart patterns may be intere
Externí odkaz:
http://arxiv.org/abs/2307.06380
Physics-informed neural networks (PINNs) have recently become a powerful tool for solving partial differential equations (PDEs). However, finding a set of neural network parameters that lead to fulfilling a PDE can be challenging and non-unique due t
Externí odkaz:
http://arxiv.org/abs/2304.04854
With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity
Externí odkaz:
http://arxiv.org/abs/2212.04902
Estimating uncertainty of machine learning models is essential to assess the quality of the predictions that these models provide. However, there are several factors that influence the quality of uncertainty estimates, one of which is the amount of m
Externí odkaz:
http://arxiv.org/abs/2210.16938