Titlebook: ECML PKDD 2018 Workshops; MIDAS 2018 and PAP 2 Carlos Alzate,Anna Monreale,Tiziano Squartini Conference proceedings 2019 Springer Nature Sw

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Lipohypertrophy

Exploring Students Eating Habits Through Individual Profiling and Clustering Analysise importance of a healthy and balanced diet. To this end, understanding the real eating habits of people becomes fundamental for a better and more effective intervention to improve the students’ diet. In this paper we present two exploratory analyses based on centroid-based clustering that have the

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Naresh Kumar Thakur,Sanjeev Rajputntities of interests, accounting for interdependencies among them. In finance, several of this quantities of interests (stock valuations, return, volatility) have been shown to be mutually influencing each other, making the prediction of such quantities a difficult task, especially while dealing wit

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BAN

Human Complement Receptor 1 Polymorphismsnear relationship. Although deep learning performs quite well, it has significant disadvantages such as a lack of transparency and limitations to the interpretability of the prediction. This is prone to practical problems in terms of accountability. Thus, we construct a multifactor model by using in

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Lei Yang,Shumin Liang,Binjie Zhunce of this task for financial institutions, models being used still lack high accuracy. Also, most of these models are not built specifically on stock market data. Therefore, there is still a need for a highly accurate model of sentiment classification that is specifically tuned and trained for sto

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J. Hanasz,V. I. Aksenov,G. P. Komrakovake a Bayesian approach to inference and model comparison in self-exciting processes. We discuss strategies to compute marginal likelihood estimates for the univariate Hawkes process, and describe a Bayesian model comparison scheme. We demonstrate on currency, cryptocurrency and equity limit order b

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