Fairness

Changing criteria weights to achieve fair VIKOR ranking: a postprocessing reranking approach
Ranking is a prerequisite for making decisions, and therefore it is a very responsible and frequently applied activity. This study …
Zorica Dodevska, Andrija Petrović, Sandro Radovanović, Boris Delibašić
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Do we Reach Desired Disparate Impact with In-Processing Fairness Techniques?
Using machine learning algorithms in social environments and systems requires stricter and more detailed control. More specifically, …
Sandro Radovanović, Boris Delibašić, Milija Suknović
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Achieving MAX-MIN Fair Cross-efficiency scores in Data Envelopment Analysis
Algorithmic decision making is gaining popularity in today’s business. The need for fast, accurate, and complex decisions forces …
Sandro Radovanović, Boris Delibašić, Aleksandar Marković, Milija Suknović
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FAIR: Fair Adversarial Instance Re-weighting
With growing awareness of societal impact of artificial intelligence, fairness has become an important aspect of machine learning …
Andrija Petrović, Mladen Nikolić, Sandro Radovanović, Boris Delibašić, Miloš Jovanović
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FairDEA - Removing Disparate Impact from Efficiency Scores
Achieving fairness in algorithmic decision-making tools is an issue constantly gaining in need and popularity. Today, unfair decisions …
Sandro Radovanović, Gordana Savić, Boris Delibašić, Milija Suknović
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Eliminating Disparate Impact in MCDM: The case of TOPSIS
In today’s business, decision-making is heavily dependent on algorithms. Algorithms may originate from operational research, machine …
Sandro Radovanović, Andrija Petrović, Boris Delibašić, Milija Suknović
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A fair classifier chain for multi-label bank marketing strategy classification
Recently, the usage of machine learning algorithms is subject to discussion from a legal and ethical point of view. Unwanted …
Sandro Radovanović, Andrija Petrović, Boris Delibašić, Milija Suknović
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Investigating Oversampling Techniques for Fair Machine Learning Models
Applying machine learning in real-world applications may have various implications on companies, but individuals as well. Besides …
Sanja Rančić, Sandro Radovanović, Boris Delibašić
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Enabling Equal Opportunity in Logistic Regression Algorithm
Research Question - This paper aims at adjusting the logistic regression algorithm to mitigate unwanted discrimination shown towards …
Sandro Radovanović, Marko Ivić
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Enforcing fairness in logistic regression algorithm
Machine learning has been subject to discussion from the legal and ethical points of view in recent years. Automation of the …
Sandro Radovanović, Andrija Petrović, Boris Delibašić, Milija Suknović
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