Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in … the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation … those using the entire untransformed dataset, as well as several other hybrid machine learning algorithms. In addition, the …

remains a challenge. Genetic Algorithms are a global optimization approach which is suitable for addressing complex problems … derivatives-based methods, Genetic Algorithms are robust for addressing highly multi-modal and discontinuous search landscapes. In … proposed approach evolves a sequence of transitions. We also discuss workable starting points for the use of Genetic Algorithms …

pricing algorithms that allow for high-frequency price changes. What are the implications for price competition? We develop a … model of price competition where firms can differ in pricing frequency and choose algorithms that autonomously react to … pricing algorithms lead to meaningful increases in markups, especially for firms with superior pricing technology …

defendants under the age of 23. In the context of contentious public discussions about algorithms, our results highlight the …

As recommendation algorithms have been increasingly applied to content personalization services, scholars are voicing … concern about the negative impacts of these algorithms, for instance filter bubbles and ideological polarization. This … research attempts to analyze the various factors influencing users' continuance intention of recommendation algorithms through …