Indre Zliobaite

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 32

Top Topics

Evaluation Methods

Top Venues

Ecol. Informatics

Data Min. Knowl. Discov.

Publications

Ekaterina Antonenko, Michael Mechenich, Rita Beigaite, Indre Zliobaite, Jesse Read
Backward Inference in Probabilistic Regressor Chains with Distributional Constraints. IDA (2) (2024)
Ryoko Noda, Michael Mechenich, Juha Saarinen, Aki Vehtari, Indre Zliobaite
Predicting habitat suitability for Asian elephants in non-analog ecosystems with Bayesian models. Ecol. Informatics 82 (2024)
Indre Zliobaite, Jesse Read
A Historical Context for Data Streams. CoRR (2023)
Antonio Rafael Sabino Parmezan, Vinicius M. A. Souza, Arpita Seth, Indre Zliobaite, Gustavo E. A. P. A. Batista
Hierarchical classification of pollinating flying insects under changing environments. Ecol. Informatics 70 (2022)
Jesse Read, Indre Zliobaite
Learning from Data Streams: An Overview and Update. CoRR (2022)
Rita Beigaite, Michael Mechenich, Indre Zliobaite
Spatial Cross-Validation for Globally Distributed Data. DS (2022)
Rita Beigaite, Jesse Read, Indre Zliobaite
Multi-output regression with structurally incomplete target labels: A case study of modelling global vegetation cover. Ecol. Informatics 72 (2022)
Indre Zliobaite
Recommender Systems Meet Species Distribution Modelling. Perspectives@RecSys (2021)
Esther Galbrun, Hui Tang, Anu Kaakinen, Indre Zliobaite
Redescription mining for analyzing local limiting conditions: A case study on the biogeography of large mammals in China and southern Asia. Ecol. Informatics 63 (2021)
Indre Zliobaite
Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record. Data Min. Knowl. Discov. 33 (3) (2019)
Indre Zliobaite
AI minds need to think about energy constraints. Nat. Mach. Intell. 1 (8) (2019)
Roelant A. Stegmann, Indre Zliobaite, Tuukka Tolvanen, Jaakko Hollmén, Jesse Read
A survey of evaluation methods for personal route and destination prediction from mobility traces. WIREs Data Mining Knowl. Discov. 8 (2) (2018)
Alexandr V. Maslov, Mykola Pechenizkiy, Yulong Pei, Indre Zliobaite, Alexander Shklyaev, Tommi Kärkkäinen, Jaakko Hollmén
BLPA: Bayesian learn-predict-adjust method for online detection of recurrent changepoints. IJCNN (2017)
Indre Zliobaite
Measuring discrimination in algorithmic decision making. Data Min. Knowl. Discov. 31 (4) (2017)
Jukka Teittinen, Markus Hiienkari, Indre Zliobaite, Jaakko Hollmén, Heikki Berg, Juha Heiskala, Timo Viitanen, Jesse Simonsson, Lauri Koskinen
A 5.3 pJ/op approximate TTA VLIW tailored for machine learning. Microelectron. J. 61 (2017)
Indre Zliobaite
Fairness-aware machine learning: a perspective. CoRR (2017)
Indre Zliobaite, Bart Custers
Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models. Artif. Intell. Law 24 (2) (2016)
Alexandr V. Maslov, Mykola Pechenizkiy, Indre Zliobaite, Tommi Kärkkäinen
Modelling Recurrent Events for Improving Online Change Detection. SDM (2016)
Jesse Read, Indre Zliobaite, Jaakko Hollmén
Labeling sensing data for mobility modeling. Inf. Syst. 57 (2016)
Indre Zliobaite, Nikolaj Tatti
A note on adjusting $R^2$ for using with cross-validation. CoRR (2016)
Tomas Krilavicius, Indre Zliobaite, Henrikas Simonavicius, Laimonas Jarusevicius
Predicting Respiratory Motion for Real-Time Tumour Tracking in Radiotherapy. CBMS (2016)
Indre Zliobaite, Mikhail Khokhlov
Optimal estimates for short horizon travel time prediction in urban areas. Intell. Data Anal. 20 (6) (2016)
Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes
Evaluation methods and decision theory for classification of streaming data with temporal dependence. Mach. Learn. 98 (3) (2015)
Indre Zliobaite, Mikhail Khokhlov
Optimal estimates for short horizon travel time prediction in urban areas. CoRR (2015)
Indre Zliobaite, Michael Mathioudakis, Tuukka Lehtiniemi, Pekka Parviainen, Tomi Janhunen
Accessibility by Public Transport Predicts Residential Real Estate Prices: A Case Study in Helsinki Region. MUD@ICML (2015)
Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track. Mach. Learn. 100 (2-3) (2015)
Indre Zliobaite
A survey on measuring indirect discrimination in machine learning. CoRR (2015)
Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
Guest editors introduction: special issue of the ECMLPKDD 2015 journal track. Data Min. Knowl. Discov. 29 (5) (2015)
Indre Zliobaite, Marcin Budka, Frederic T. Stahl
Towards cost-sensitive adaptation: When is it worth updating your predictive model? Neurocomputing 150 (2015)
Tomas Krilavicius, Indre Zliobaite, Henrikas Simonavicius, Laimonas Jarusevicius
Predicting respiratory motion for real-time tumour tracking in radiotherapy. CoRR (2015)
Indre Zliobaite
On the relation between accuracy and fairness in binary classification. CoRR (2015)
Indre Zliobaite, Jaakko Hollmén
Optimizing regression models for data streams with missing values. Mach. Learn. 99 (1) (2015)
Indre Zliobaite
Controlled permutations for testing adaptive learning models. Knowl. Inf. Syst. 39 (3) (2014)
João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia
A survey on concept drift adaptation. ACM Comput. Surv. 46 (4) (2014)
Indre Zliobaite, Jaakko Hollmén, Lauri Koskinen, Jukka Teittinen
Towards Hardware-driven Design of Low-energy Algorithms for Data Analysis. SIGMOD Rec. 43 (4) (2014)
Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
Open challenges for data stream mining research. SIGKDD Explor. 16 (1) (2014)
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst, Indre Zliobaite, Mykola Pechenizkiy
Dealing With Concept Drifts in Process Mining. IEEE Trans. Neural Networks Learn. Syst. 25 (1) (2014)
Manuel Martin Salvador, Bogdan Gabrys, Indre Zliobaite
Online Detection of Shutdown Periods in Chemical Plants: A Case Study. KES (2014)
Indre Zliobaite, Jaakko Hollmén
Mobile Sensing Data for Urban Mobility Analysis: A Case Study in Preprocessing. EDBT/ICDT Workshops (2014)
Indre Zliobaite, Bogdan Gabrys
Adaptive Preprocessing for Streaming Data. IEEE Trans. Knowl. Data Eng. 26 (2) (2014)
Dino Ienco, Indre Zliobaite, Bernhard Pfahringer
High density-focused uncertainty sampling for active learning over evolving stream data. BigMine (2014)
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes
Active Learning With Drifting Streaming Data. IEEE Trans. Neural Networks Learn. Syst. 25 (1) (2014)
Marcin Budka, Mark Eastwood, Bogdan Gabrys, Petr Kadlec, Manuel Martin Salvador, Stephanie Schwan, Athanasios Tsakonas, Indre Zliobaite
From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors. IDA (2014)
Indre Zliobaite, Mykola Pechenizkiy
Predictive User Modeling with Actionable Attributes. CoRR (2013)
Indre Zliobaite
How good is the Electricity benchmark for evaluating concept drift adaptation CoRR (2013)
Dino Ienco, Albert Bifet, Indre Zliobaite, Bernhard Pfahringer
Clustering Based Active Learning for Evolving Data Streams. Discovery Science (2013)
Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them. ECML/PKDD (1) (2013)
Mykola Pechenizkiy, Indre Zliobaite
Introduction to the special issue on handling concept drift in adaptive information systems. Evol. Syst. 4 (1) (2013)
Faisal Kamiran, Indre Zliobaite, Toon Calders
Quantifying explainable discrimination and removing illegal discrimination in automated decision making. Knowl. Inf. Syst. 35 (3) (2013)
Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indre Zliobaite
CD-MOA: Change Detection Framework for Massive Online Analysis. IDA (2013)
Indre Zliobaite, Jaakko Hollmén
Fault Tolerant Regression for Sensor Data. ECML/PKDD (1) (2013)
Hock Hee Ang, Vivekanand Gopalkrishnan, Indre Zliobaite, Mykola Pechenizkiy, Steven C. H. Hoi
Predictive Handling of Asynchronous Concept Drifts in Distributed Environments. IEEE Trans. Knowl. Data Eng. 25 (10) (2013)
Indre Zliobaite, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, João Gama, Leandro L. Minku, Katarzyna Musial
Next challenges for adaptive learning systems. SIGKDD Explor. 14 (1) (2012)
Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
Beating the baseline prediction in food sales: How intelligent an intelligent predictor is? Expert Syst. Appl. 39 (1) (2012)
Edward Tersoo Apeh, Indre Zliobaite, Mykola Pechenizkiy, Bogdan Gabrys
Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales. SGAI Conf. (2012)
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoff Holmes
Active Learning with Evolving Streaming Data. ECML/PKDD (3) (2011)
Indre Zliobaite
Combining similarity in time and space for training set formation under concept drift. Intell. Data Anal. 15 (4) (2011)
Indre Zliobaite, Albert Bifet, Geoff Holmes, Bernhard Pfahringer
MOA Concept Drift Active Learning Strategies for Streaming Data. WAPA (2011)
Oleksiy Mazhelis, Indre Zliobaite, Mykola Pechenizkiy
Context-Aware Personal Route Recognition. Discovery Science (2011)
Indre Zliobaite, Faisal Kamiran, Toon Calders
Handling Conditional Discrimination. ICDM (2011)
Indre Zliobaite
Identifying Hidden Contexts in Classification. PAKDD (1) (2011)
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst, Indre Zliobaite, Mykola Pechenizkiy
Handling Concept Drift in Process Mining. CAiSE (2011)
Indre Zliobaite
Controlled Permutations for Testing Adaptive Classifiers. Discovery Science (2011)
Indre Zliobaite
Change with Delayed Labeling: When is it Detectable? ICDM Workshops (2010)
Indre Zliobaite, Mykola Pechenizkiy
Learning with Actionable Attributes: Attention -- Boundary Cases! ICDM Workshops (2010)
Mykola Pechenizkiy, Ekaterina Vasilyeva, Indre Zliobaite, Aleksandra Tesanovic, Goran Manev
Heart failure hospitalization prediction in remote patient management systems. CBMS (2010)
Indre Zliobaite
Learning under Concept Drift: an Overview CoRR (2010)
Mykola Pechenizkiy, Indre Zliobaite
Handling concept drift in medical applications: Importance, challenges and solutions. CBMS (2010)
Indre Zliobaite, Ludmila I. Kuncheva
Determining the Training Window for Small Sample Size Classification with Concept Drift. ICDM Workshops (2009)
Mykola Pechenizkiy, Jorn Bakker, Indre Zliobaite, Andriy Ivannikov, Tommi Kärkkäinen
Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift. SIGKDD Explor. 11 (2) (2009)
Indre Zliobaite
Combining Time and Space Similarity for Small Size Learning under Concept Drift. ISMIS (2009)
Jorn Bakker, Mykola Pechenizkiy, Indre Zliobaite, Andriy Ivannikov, Tommi Kärkkäinen
Handling outliers and concept drift in online mass flow prediction in CFB boilers. KDD Workshop on Knowledge Discovery from Sensor Data (2009)
Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers. Discovery Science (2009)
Ludmila I. Kuncheva, Indre Zliobaite
On the window size for classification in changing environments. Intell. Data Anal. 13 (6) (2009)
Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
Towards Context Aware Food Sales Prediction. ICDM Workshops (2009)
Ludmila I. Kuncheva, Indre Zliobaite
Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift. SSPR/SPR (2008)
Indre Zliobaite
Expected Classification Error of the Euclidean Linear Classifier under Sudden Concept Drift. FSKD (2) (2008)
Indre Zliobaite
Ensemble Learning for Concept Drift Handling - the Role of New Expert. MLDM Posters (2007)
Sarunas Raudys, Indre Zliobaite
The Multi-Agent System for Prediction of Financial Time Series. ICAISC (2006)
Sarunas Raudys, Indre Zliobaite
Prediction of Commodity Prices in Rapidly Changing Environments. ICAPR (1) (2005)