235 citations · 474 across the 10 of their papers we have counts for
12 papers
What Do Learned Models Measure?
Indrė Žliobaitė
In many scientific and data-driven applications, machine learning models are increasingly used as measurement instruments, rather than merely as predictors of predefined labels. Wh…
Modelling the longevity of complex living systems
Indrė Žliobaitė
This extended abstract was presented at the Nectar Track of ECML PKDD 2024 in Vilnius, Lithuania. The content supplements a recently published paper "Laws of Macroevolutionary Expa…
A Historical Context for Data Streams
Indre Zliobaite, Jesse Read
Machine learning from data streams is an active and growing research area. Research on learning from streaming data typically makes strict assumptions linked to computational resou…
Fairness-aware machine learning: a perspective
Indre Zliobaite
Algorithms learned from data are increasingly used for deciding many aspects in our life: from movies we see, to prices we pay, or medicine we get. Yet there is growing evidence th…
A note on adjusting for using with cross-validation
Indre Zliobaite, Nikolaj Tatti
We show how to adjust the coefficient of determination () when used for measuring predictive accuracy via leave-one-out cross-validation.
A survey on measuring indirect discrimination in machine learning
Indre Zliobaite
Nowadays, many decisions are made using predictive models built on historical data.Predictive models may systematically discriminate groups of people even if the computing process…