This paper is the first one of a series of 9 lecture notes in Algorithmic and Advanced Programming in Python that are part of the Syllabus of Dauphine PSL's Master in Computer Science, Decision Making & Data. It taught advanced data structure in python with a focus on core and practical details...

Opportunistic Networks (OppNets) is gaining popularity day-by-day due to their various applications in the real-life world. The two major reasons for its popularity are its suitability to be established without any requirement of additional infrastructure and the ability to tolerate long delays...

This paper introduces a new Empirical Mode Decomposition (EMD) Python package called AdvEMDpy that is demonstrably more flexible and which generalises in numerous important ways the existing EMD packages available in Python, R, and MATLAB. The extensions introduced by this AdvEMDpy package both...

This paper develops a multi-objective decision support model for solving the patient bed assignment problem. Assigning inpatients to hospital beds impacts patient satisfaction and the workload of nurses and doctors. The assignment is subject to unknown patient arrivals and lengths of stay, in...

The first moment and second central moments of the portfolio return, a.k.a. mean and variance, have been widely employed to assess the expected profit and risk of the portfolio. Investors pursue higher mean and lower variance when designing the portfolios. The two moments can well describe the...

The evolution of Internet and Communication Technologies (ICTs) has changed the landscape of traditional web. The present scenario of web forms a large network of tools, techniques and people across globe, which turns the existing facet of web in a socially active web that is, social web. The...

This paper undertakes a critical review of the prospect that self-learning pricing algorithms will lead to widespread collusion independently of the intervention and participation of humans. There is no concrete evidence, no example yet, and no antitrust case that self-learning pricing...

The optimization of sales practices in consumer markets through machine learning not only harbours the potential to better match consumer preferences with products, but also risks to facilitate the exploitation of consumer weaknesses discovered via data analysis. More specifically, recent...

This paper provides a general representation of endogenous and threshold-based regime switching models and develops an efficient numerical solution method. The regime-switching is triggered endogenously when some variables cross threshold conditions that can themselves be regime-dependent. We...

The paper presents a Bayes analysis of an autoregressive-moving average model and its components based on exact likelihood and weak priors for the parameters where the priors are defined so that they incorporate stationarity and invertibility restrictions naturally. A Gibbs-Metropolis hybrid...