Fairness

Are we really addressing fairness in machine learning algorithms?
This study explores the effectiveness of neural network regularization functions in measuring fairness, particularly analyzing the …
Sandro Radovanović, Milan Vukićević, Milija Suknović
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FairAW - Additive weighting without discrimination
With growing awareness of the societal impact of decision-making, fairness has become an important issue. More specifically, in many …
Sandro Radovanović, Andrija Petrović, Zorica Dodevska, Boris Delibašić
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When Fairness Meets Consistency in AHP Pairwise Comparisons
We propose introducing fairness constraints to one of the most famous multi-criteria decision-making methods, the analytic hierarchy …
Zorica Dodevska, Sandro Radovanović, Andrija Petrović, Boris Delibašić
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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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Envy-free Fair Student Dropout Prediction
Algorithmic decision-making influences everyday life by proposing and automating decisions. Although these models are in general more …
Sandro Radovanović, Boris Delibašić, Milija Suknović
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Empirical analysis of Information Theory point of view on Equal Odds Fairness Measure
Algorithmic decision-making is facing a rising concern of unwanted discrimination. Biases that exist in decision-making, data …
Sandro Radovanović, Boris Delibašić, Milija Suknović
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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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