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20192025
most citedA Survey on AI Assurance

113 citations · 238 across the 20 of their papers we have counts for

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Showing 2021Show all

9 papers · 1 filter

cs.AI2021

AI Assurance using Causal Inference: Application to Public Policy

Andrei Svetovidov, Abdul Rahman, Feras A. Batarseh

Developing and implementing AI-based solutions help state and federal government agencies, research institutions, and commercial companies enhance decision-making processes, automa…

cs.LG2021

Outlier Detection using AI: A Survey

Md Nazmul Kabir Sikder, Feras A. Batarseh

An outlier is an event or observation that is defined as an unusual activity, intrusion, or a suspicious data point that lies at an irregular distance from a population. The defini…

cs.LG2021★ 19 cited

Public Policymaking for International Agricultural Trade using Association Rules and Ensemble Machine Learning

Feras A. Batarseh, Munisamy Gopinath, Anderson Monken +1

International economics has a long history of improving our understanding of factors causing trade, and the consequences of free flow of goods and services across countries. The re…

cs.AI2021★ 113 cited

A Survey on AI Assurance

Feras A. Batarseh, Laura Freeman

Artificial Intelligence (AI) algorithms are increasingly providing decision making and operational support across multiple domains. AI includes a wide library of algorithms for dif…

cs.AI2021★ 13 cited

Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Management

Chih-Hao Huang, Feras A. Batarseh, Adel Boueiz +3

The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e. Covid-19) and natural disasters (such as hurricanes and earthquakes). In mos…

cs.LG2021★ 1 cited

DeepAg: Deep Learning Approach for Measuring the Effects of Outlier Events on Agricultural Production and Policy

Sai Gurrapu, Feras A. Batarseh, Pei Wang +3

Quantitative metrics that measure the global economy's equilibrium have strong and interdependent relationships with the agricultural supply chain and international trade flows. Su…

cs.SI2021

The history and future prospects of open data and open source software

Feras A. Batarseh, Abhinav Kumar, Sam Eisenberg

Open data for all New Yorkers is the tagline on New York City's open data website. Open government is being promoted at most countries of the western world. Government transparency…

cs.SE2021★ 2 cited

The application of artificial intelligence in software engineering: a review challenging conventional wisdom

Feras A. Batarseh, Rasika Mohod, Abhinav Kumar +1

The field of artificial intelligence (AI) is witnessing a recent upsurge in research, tools development, and deployment of applications. Multiple software companies are shifting th…

cs.LG2021★ 4 cited

Foundations of data imbalance and solutions for a data democracy

Ajay Kulkarni, Deri Chong, Feras A. Batarseh

Dealing with imbalanced data is a prevalent problem while performing classification on the datasets. Many times, this problem contributes to bias while making decisions or implemen…