Indre Zliobaite

Affiliations:
  • University of Helsinki, Finland
  • Aalto University, Department of Information and Computer Science
  • Helsinki Institute for Information Technology


According to our database1, Indre Zliobaite authored at least 78 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A Historical Context for Data Streams.
CoRR, 2023

2022
Hierarchical classification of pollinating flying insects under changing environments.
Ecol. Informatics, 2022

Multi-output regression with structurally incomplete target labels: A case study of modelling global vegetation cover.
Ecol. Informatics, 2022

Learning from Data Streams: An Overview and Update.
CoRR, 2022

Spatial Cross-Validation for Globally Distributed Data.
Proceedings of the Discovery Science - 25th International Conference, 2022

2021
Redescription mining for analyzing local limiting conditions: A case study on the biogeography of large mammals in China and southern Asia.
Ecol. Informatics, 2021

Recommender Systems Meet Species Distribution Modelling.
Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021 co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021), 2021

2019
AI minds need to think about energy constraints.
Nat. Mach. Intell., 2019

Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record.
Data Min. Knowl. Discov., 2019

2018
A survey of evaluation methods for personal route and destination prediction from mobility traces.
WIREs Data Mining Knowl. Discov., 2018

2017
A 5.3 pJ/op approximate TTA VLIW tailored for machine learning.
Microelectron. J., 2017

Measuring discrimination in algorithmic decision making.
Data Min. Knowl. Discov., 2017

Fairness-aware machine learning: a perspective.
CoRR, 2017

BLPA: Bayesian learn-predict-adjust method for online detection of recurrent changepoints.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Labeling sensing data for mobility modeling.
Inf. Syst., 2016

Optimal estimates for short horizon travel time prediction in urban areas.
Intell. Data Anal., 2016

A note on adjusting $R^2$ for using with cross-validation.
CoRR, 2016

Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models.
Artif. Intell. Law, 2016

Modelling Recurrent Events for Improving Online Change Detection.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Predicting Respiratory Motion for Real-Time Tumour Tracking in Radiotherapy.
Proceedings of the 29th IEEE International Symposium on Computer-Based Medical Systems, 2016

2015
Optimizing regression models for data streams with missing values.
Mach. Learn., 2015

Evaluation methods and decision theory for classification of streaming data with temporal dependence.
Mach. Learn., 2015

Towards cost-sensitive adaptation: When is it worth updating your predictive model?
Neurocomputing, 2015

Guest editors introduction: special issue of the ECMLPKDD 2015 journal track.
Data Min. Knowl. Discov., 2015

A survey on measuring indirect discrimination in machine learning.
CoRR, 2015

On the relation between accuracy and fairness in binary classification.
CoRR, 2015

Accessibility by Public Transport Predicts Residential Real Estate Prices: A Case Study in Helsinki Region.
Proceedings of the 2nd International Workshop on Mining Urban Data co-located with 32nd International Conference on Machine Learning (ICML 2015), 2015

2014
Active Learning With Drifting Streaming Data.
IEEE Trans. Neural Networks Learn. Syst., 2014

Dealing With Concept Drifts in Process Mining.
IEEE Trans. Neural Networks Learn. Syst., 2014

Adaptive Preprocessing for Streaming Data.
IEEE Trans. Knowl. Data Eng., 2014

Towards Hardware-driven Design of Low-energy Algorithms for Data Analysis.
SIGMOD Rec., 2014

Open challenges for data stream mining research.
SIGKDD Explor., 2014

Controlled permutations for testing adaptive learning models.
Knowl. Inf. Syst., 2014

A survey on concept drift adaptation.
ACM Comput. Surv., 2014

Online Detection of Shutdown Periods in Chemical Plants: A Case Study.
Proceedings of the 18th International Conference in Knowledge Based and Intelligent Information and Engineering Systems, 2014

High density-focused uncertainty sampling for active learning over evolving stream data.
Proceedings of the 3rd International Workshop on Big Data, 2014

From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors.
Proceedings of the Advances in Intelligent Data Analysis XIII, 2014

Mobile Sensing Data for Urban Mobility Analysis: A Case Study in Preprocessing.
Proceedings of the Workshops of the EDBT/ICDT 2014 Joint Conference (EDBT/ICDT 2014), 2014

2013
Explainable and Non-explainable Discrimination in Classification.
Proceedings of the Discrimination and Privacy in the Information Society, 2013

Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures.
Proceedings of the Discrimination and Privacy in the Information Society, 2013

Predictive Handling of Asynchronous Concept Drifts in Distributed Environments.
IEEE Trans. Knowl. Data Eng., 2013

Quantifying explainable discrimination and removing illegal discrimination in automated decision making.
Knowl. Inf. Syst., 2013

Introduction to the special issue on handling concept drift in adaptive information systems.
Evol. Syst., 2013

How good is the Electricity benchmark for evaluating concept drift adaptation
CoRR, 2013

Predictive User Modeling with Actionable Attributes.
CoRR, 2013

Fault Tolerant Regression for Sensor Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

CD-MOA: Change Detection Framework for Massive Online Analysis.
Proceedings of the Advances in Intelligent Data Analysis XII, 2013

Clustering Based Active Learning for Evolving Data Streams.
Proceedings of the Discovery Science - 16th International Conference, 2013

2012
Next challenges for adaptive learning systems.
SIGKDD Explor., 2012

Beating the baseline prediction in food sales: How intelligent an intelligent predictor is?
Expert Syst. Appl., 2012

Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales.
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012

2011
Three Data Partitioning Strategies for Building Local Classifiers.
Proceedings of the Ensembles in Machine Learning Applications, 2011

MOA Concept Drift Active Learning Strategies for Streaming Data.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Combining similarity in time and space for training set formation under concept drift.
Intell. Data Anal., 2011

Active Learning with Evolving Streaming Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Identifying Hidden Contexts in Classification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Handling Conditional Discrimination.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Controlled Permutations for Testing Adaptive Classifiers.
Proceedings of the Discovery Science - 14th International Conference, 2011

Context-Aware Personal Route Recognition.
Proceedings of the Discovery Science - 14th International Conference, 2011

Handling Concept Drift in Process Mining.
Proceedings of the Advanced Information Systems Engineering, 2011

2010
Learning under Concept Drift: an Overview
CoRR, 2010

Learning with Actionable Attributes: Attention -- Boundary Cases!
Proceedings of the ICDMW 2010, 2010

Change with Delayed Labeling: When is it Detectable?
Proceedings of the ICDMW 2010, 2010

Handling concept drift in medical applications: Importance, challenges and solutions.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

Heart failure hospitalization prediction in remote patient management systems.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

2009
Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift.
SIGKDD Explor., 2009

On the window size for classification in changing environments.
Intell. Data Anal., 2009

Handling outliers and concept drift in online mass flow prediction in CFB boilers.
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, 2009

Combining Time and Space Similarity for Small Size Learning under Concept Drift.
Proceedings of the Foundations of Intelligent Systems, 18th International Symposium, 2009

Towards Context Aware Food Sales Prediction.
Proceedings of the ICDM Workshops 2009, 2009

Determining the Training Window for Small Sample Size Classification with Concept Drift.
Proceedings of the ICDM Workshops 2009, 2009

OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers.
Proceedings of the Discovery Science, 12th International Conference, 2009

2008
Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift.
Proceedings of the Structural, 2008

Expected Classification Error of the Euclidean Linear Classifier under Sudden Concept Drift.
Proceedings of the Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008

2007
Ensemble Learning for Concept Drift Handling - the Role of New Expert.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2007

2006
The Multi-Agent System for Prediction of Financial Time Series.
Proceedings of the Artificial Intelligence and Soft Computing, 2006

2005
Prediction of Commodity Prices in Rapidly Changing Environments.
Proceedings of the Pattern Recognition and Data Mining, 2005


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