עקוב אחר
Indrė Žliobaitė
Indrė Žliobaitė
Professor, University of Helsinki
כתובת אימייל מאומתת בדומיין helsinki.fi - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
A survey on concept drift adaptation‏
J Gama, I Žliobaitė, A Bifet, M Pechenizkiy, A Bouchachia‏
ACM computing surveys (CSUR) 46 (4), 1-37, 2014‏
36442014
Learning under concept drift: an overview‏
I Zliobaite‏
arXiv preprint arXiv:1010.4784, 2009‏
6592009
An overview of concept drift applications‏
I Žliobaitė, M Pechenizkiy, J Gama‏
Big data analysis: new algorithms for a new society, 91-114, 2016‏
5102016
Active learning with drifting streaming data‏
I Žliobaitė, A Bifet, B Pfahringer, G Holmes‏
IEEE transactions on neural networks and learning systems 25 (1), 27-39, 2013‏
4472013
Open challenges for data stream mining research‏
G Krempl, I Žliobaite, D Brzeziński, E Hüllermeier, M Last, V Lemaire, ...‏
ACM SIGKDD explorations newsletter 16 (1), 1-10, 2014‏
4062014
Measuring discrimination in algorithmic decision making‏
I Žliobaitė‏
Data Mining and Knowledge Discovery 31 (4), 1060-1089, 2017‏
3522017
Handling concept drift in process mining‏
RPJC Bose, WMP van der Aalst, I Žliobaitė, M Pechenizkiy‏
Advanced Information Systems Engineering: 23rd International Conference …, 2011‏
3082011
Dealing with concept drifts in process mining‏
RPJC Bose, WMP Van Der Aalst, I Žliobaitė, M Pechenizkiy‏
IEEE transactions on neural networks and learning systems 25 (1), 154-171, 2013‏
2522013
Why unbiased computational processes can lead to discriminative decision procedures‏
T Calders, I Žliobaitė‏
Discrimination and Privacy in the Information Society: Data mining and …, 2013‏
2412013
A survey on measuring indirect discrimination in machine learning‏
I Zliobaite‏
arXiv preprint arXiv:1511.00148, 2015‏
2132015
Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models‏
I Žliobaitė, B Custers‏
Artificial Intelligence and Law 24, 183-201, 2016‏
1982016
Quantifying explainable discrimination and removing illegal discrimination in automated decision making‏
F Kamiran, I Žliobaitė, T Calders‏
Knowledge and information systems 35, 613-644, 2013‏
1812013
Handling conditional discrimination‏
I Žliobaite, F Kamiran, T Calders‏
2011 IEEE 11th international conference on data mining, 992-1001, 2011‏
1802011
On the relation between accuracy and fairness in binary classification‏
I Zliobaite‏
arXiv preprint arXiv:1505.05723, 2015‏
1752015
Evaluation methods and decision theory for classification of streaming data with temporal dependence‏
I Žliobaitė, A Bifet, J Read, B Pfahringer, G Holmes‏
Machine Learning 98, 455-482, 2015‏
1632015
Pitfalls in benchmarking data stream classification and how to avoid them‏
A Bifet, J Read, I Žliobaitė, B Pfahringer, G Holmes‏
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013‏
1232013
Next challenges for adaptive learning systems‏
I Zliobaite, A Bifet, M Gaber, B Gabrys, J Gama, L Minku, K Musial‏
ACM SIGKDD Explorations Newsletter 14 (1), 48-55, 2012‏
1222012
Active learning with evolving streaming data‏
I Žliobaitė, A Bifet, B Pfahringer, G Holmes‏
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011‏
1142011
An ecometric analysis of the fossil mammal record of the Turkana Basin‏
M Fortelius, I Žliobaitė, F Kaya, F Bibi, R Bobe, L Leakey, M Leakey, ...‏
Philosophical Transactions of the Royal Society B: Biological Sciences 371 …, 2016‏
1122016
Change with delayed labeling: When is it detectable?‏
I Žliobaite‏
2010 IEEE international conference on data mining workshops, 843-850, 2010‏
1102010
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מאמרים 1–20