This article studies the estimation of state space models whose parameters are switching endogenously between two regimes, depending on whether an autoregressive latent factor crosses some threshold level. Endogeneity stems from the sustained impacts of transition innovations on the latent...

We are interested in the analysis of the concept of interpretability associated with a ML algorithm. We distinguish between the “How”, i.e., how a black box or a very complex algorithm works, and the “Why”, i.e. why an algorithm produces such a result. These questions appeal to many...

Prediction is a forecast of an event which may happen in future. Predictions are not necessary based upon the prior knowledge or experience for an event of interest. Every person does predictions but the quality of the predictions differs from person to person and that classifies them as a...

Why do consumers embrace some algorithms and find others objectionable? The moral relevance of the domain in which an algorithm operates plays a role. The authors find that consumers believe that algorithms are more likely to use maximization (i.e. attempting to maximize some measured outcome)...

Leading recommender systems may recommend only a small fraction of users on the dating platform since the algorithms often exploit popularity and similarity that reinforce preference homogeneity and assortative mating in the marriage market. We apply a stylized matching model in economics to the...

Classification is one of the methods used in identifying the accuracy of the dataset of multiple classes. This paper has proposed a method named FHSM ( Fuzzy Heterogeneous Node Splitting Measure ) for building decision tree which used Gaussian membership function in assigning fuzzy membership...

An Algorithm to extend sensor lifetime and energy is implemented for different scenarios of ad hoc and wireless sensor networks. The goal is to prolong the lifetimes of sensors, covering a number of targeted zones by creating subsets of sensors, in which each subset covers entirely the targeted...

This paper studies how algorithms use variables to maximize predictive power at the cost of group equity. Group inequity arises if variables enlarge disparities in risk scores across groups. I develop a framework to examine a recidivism risk assessment tool using risk score and novel pretrial...

During the past decades, societies have been greatly impacted by the impressive technological progress made in computer science. However, Artificial Intelligence and Machine Learning have not only become an indispensable part of our everyday lives, they also found their way into legal research:...

Artificial intelligence (“Al") is a comprehensive field of computer science that enables machines to learn from experience and ultimately take difficult actions without human intervention. Al has been one of the highly populartopics overthe last decade, as it has become a more effective tool...