Zobrazeno 1 - 10
of 172
pro vyhledávání: '"Vidal, Juan C."'
Complex survey designs are commonly employed in many medical cohorts. In such scenarios, developing case-specific predictive risk score models that reflect the unique characteristics of the study design is essential. This approach is key to minimizin
Externí odkaz:
http://arxiv.org/abs/2403.19752
In this paper, we introduce a kNN-based regression method that synergizes the scalability and adaptability of traditional non-parametric kNN models with a novel variable selection technique. This method focuses on accurately estimating the conditiona
Externí odkaz:
http://arxiv.org/abs/2402.01635
This paper presents novel prompting techniques to improve the performance of automatic summarization systems for scientific articles. Scientific article summarization is highly challenging due to the length and complexity of these documents. We conce
Externí odkaz:
http://arxiv.org/abs/2312.08282
Predictive monitoring is a subfield of process mining that aims to predict how a running case will unfold in the future. One of its main challenges is forecasting the sequence of activities that will occur from a given point in time -- suffix predict
Externí odkaz:
http://arxiv.org/abs/2211.16106
Changes, planned or unexpected, are common during the execution of real-life processes. Detecting these changes is a must for optimizing the performance of organizations running such processes. Most of the algorithms present in the state-of-the-art f
Externí odkaz:
http://arxiv.org/abs/2207.11007
Predictive monitoring of business processes is a subfield of process mining that aims to predict, among other things, the characteristics of the next event or the sequence of next events. Although multiple approaches based on deep learning have been
Externí odkaz:
http://arxiv.org/abs/2112.09641
Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive monitoring
Externí odkaz:
http://arxiv.org/abs/2009.13251
Biosensor data has the potential ability to improve disease control and detection. However, the analysis of these data under free-living conditions is not feasible with current statistical techniques. To address this challenge, we introduce a new fun
Externí odkaz:
http://arxiv.org/abs/2008.07840
Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are
Externí odkaz:
http://arxiv.org/abs/1907.04276
The fuzzy quantification model FA has been identified as one of the best behaved quantification models in several revisions of the field of fuzzy quantification. This model is, to our knowledge, the unique one fulfilling the strict Determiner Fuzzifi
Externí odkaz:
http://arxiv.org/abs/1902.02132