Albert Bifet

Silviu Maniu

Nikolaos Tziortziotis

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier.

[BibT_eX]

[DOI]

Wenbin Zhang

Proceedings of the Discovery Science - 23rd International Conference, 2020

Unsupervised Concept Drift Detection Using a Student-Teacher Approach.

[BibT_eX]

[DOI]

Vítor Cerqueira

Proceedings of the Discovery Science - 23rd International Conference, 2020

Streaming Time Series Forecasting using Multi-Target Regression with Dynamic Ensemble Selection.

[BibT_eX]

[DOI]

Dihia Boulegane

Haytham Elghazel

Giyyarpuram Madhusudan

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

AutoML for Stream k-Nearest Neighbors Classification.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Machine learning for streaming data: state of the art, challenges, and opportunities.

[BibT_eX]

[DOI]

SIGKDD Explor., 2019

Correction to: Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2019

Boosting decision stumps for dynamic feature selection on data streams.

[BibT_eX]

[DOI]

Inf. Syst., 2019

Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining.

[BibT_eX]

[DOI]

Int. J. Data Sci. Anal., 2019

Efficient frequent subgraph mining on large streaming graphs.

[BibT_eX]

[DOI]

Abhik Ray

Lawrence B. Holder

Intell. Data Anal., 2019

On learning guarantees to unsupervised concept drift detection on data streams.

[BibT_eX]

[DOI]

Carlos Henrique Grossi Ferreira

Yule Vaz

Expert Syst. Appl., 2019

Measuring the Shattering coefficient of Decision Tree models.

[BibT_eX]

[DOI]

Chaitanya Manapragada

Expert Syst. Appl., 2019

Merit-guided dynamic feature selection filter for data streams.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2019

Recurring concept meta-learning for evolving data streams.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2019

Rebalancing Learning on Evolving Data Streams.

[BibT_eX]

[DOI]

Alessio Bernardo

Emanuele Della Valle

Guilherme Weigert Cassales

CoRR, 2019

Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Resource-aware Elastic Swap Random Forest for Evolving Data Streams.

[BibT_eX]

[DOI]

CoRR, 2019

Continuous Analytics of Web Streams.

[BibT_eX]

[DOI]

Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

ORSUM 2019 2nd workshop on online recommender systems and user modeling.

[BibT_eX]

[DOI]

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Towards Automated Configuration of Stream Clustering Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

IDSA-IoT: An Intrusion Detection System Architecture for IoT Networks.

[BibT_eX]

[DOI]

Hermes Senger

Elaine Ribeiro de Faria

Luis Eduardo Boiko Ferreira

Proceedings of the 2019 IEEE Symposium on Computers and Communications, 2019

Adaptive Random Forests with Resampling for Imbalanced data Streams.

[BibT_eX]

[DOI]

Luiz S. Oliveira

Proceedings of the International Joint Conference on Neural Networks, 2019

Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles.

[BibT_eX]

[DOI]

Philippe Fournier-Viger

Jones Granatyr

Proceedings of the Neural Information Processing - 26th International Conference, 2019

Streaming Random Patches for Evolving Data Stream Classification.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets.

[BibT_eX]

[DOI]

Barbara Hammer

Frank-Michael Schleif

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Metropolis-Hastings Algorithms for Estimating Betweenness Centrality.

[BibT_eX]

[DOI]

Proceedings of the Advances in Database Technology, 2019

Adaptive Algorithms for Estimating Betweenness and <i>k</i>-path Centralities.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Semi-supervised Learning over Streaming Data using MOA.

[BibT_eX]

[DOI]

Minh-Huong Le Nguyen

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Real-Time Machine Learning Competition on Data Streams at the IEEE Big Data 2019.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams.

[BibT_eX]

[DOI]

Dihia Boulegane

Giyyarpuram Madhusudan

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Scikit-Multiflow: A Multi-output Streaming Framework.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2018

Predicting attributes and friends of mobile users from AP-Trajectories.

[BibT_eX]

[DOI]

Inf. Sci., 2018

Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities.

[BibT_eX]

[DOI]

CoRR, 2018

Large-Scale Learning from Data Streams with Apache SAMOA.

[BibT_eX]

[DOI]

Nicolas Kourtellis

CoRR, 2018

Discriminative Distance-Based Network Indices with Application to Link Prediction.

[BibT_eX]

[DOI]

Comput. J., 2018

Telemetry-based stream-learning of BGP anomalies.

[BibT_eX]

[DOI]

Proceedings of the 2018 Workshop on Big Data Analytics and Machine Learning for Data Communication Networks, 2018

Scalable Model-Based Cascaded Imputation of Missing Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2018, 2018

EXAD: A System for Explainable Anomaly Detection on Big Data Traces.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders.

[BibT_eX]

[DOI]

Tian Guo

Nino Antulov-Fantulin

Proceedings of the IEEE International Conference on Data Mining, 2018

Adaptive random forests for data stream regression.

[BibT_eX]

[DOI]

Luis Eduardo Boiko Ferreira

Jean Paul Barddal

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Ubiquitous Artificial Intelligence and Dynamic Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems, 2018

Learning Fast and Slow: A Unified Batch/Stream Framework.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams.

[BibT_eX]

[DOI]

Maroua Bahri

Silviu Maniu

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2017

Data stream classification using random feature functions and novel method combinations.

[BibT_eX]

[DOI]

J. Syst. Softw., 2017

A Survey on Ensemble Learning for Data Stream Classification.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2017

Discriminative Distance-Based Network Indices and the Tiny-World Property.

[BibT_eX]

[DOI]

CoRR, 2017

Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories.

[BibT_eX]

[DOI]

Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Extremely Fast Decision Tree Mining for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Droplet Ensemble Learning on Drifting Data Streams.

[BibT_eX]

[DOI]

Pierre-Xavier Loeffel

Christophe Marsala

Marcin Detyniecki

Proceedings of the Advances in Intelligent Data Analysis XVI, 2017

Classifier Concept Drift Detection and the Illusion of Progress.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2017

Predicting over-indebtedness on batch and streaming data.

[BibT_eX]

[DOI]

Jacob Montiel

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Low-latency multi-threaded ensemble learning for dynamic big data streams.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

Adaptive Model Rules From High-Speed Data Streams.

[BibT_eX]

[DOI]

João Duarte

João Gama

ACM Trans. Knowl. Discov. Data, 2016

A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic.

[BibT_eX]

[DOI]

Valentín Carela-Español

Pere Barlet-Ros

Kensuke Fukuda

Telecommun. Syst., 2016

Analyzing Big Data Streams with Apache SAMOA.

[BibT_eX]

[DOI]

Nicolas Kourtellis

Proceedings of the Behavioral Analytics in Social and Ubiquitous Environments, 2016

Mining Internet of Things (IoT) Big Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual International Symposium on Information Management and Big Data, 2016

Deferral classification of evolving temporal dependent data streams.

[BibT_eX]

[DOI]

Michael Mayo

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

On Dynamic Feature Weighting for Feature Drifting Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

IoT Big Data Stream Mining.

[BibT_eX]

[DOI]

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

VHT: Vertical hoeffding tree.

[BibT_eX]

[DOI]

Nicolas Kourtellis

Arinto Murdopo

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Echo State Hoeffding Tree Learning.

[BibT_eX]

[DOI]

Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015

Evaluation methods and decision theory for classification of streaming data with temporal dependence.

[BibT_eX]

[DOI]

Mach. Learn., 2015

SAMOA: scalable advanced massive online analysis.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2015

An efficient closed frequent itemset miner for the MOA stream mining system.

[BibT_eX]

[DOI]

Massimo Quadrana

AI Commun., 2015

Data Stream Classification Using Random Feature Functions and Novel Method Combinations.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

Real-Time Big Data Stream Analytics.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual International Symposium on Information Management and Big Data, 2015

Deep learning in partially-labeled data streams.

[BibT_eX]

[DOI]

Fernando Pérez-Cruz

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Drift Detection Using Stream Volatility.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Mining Big Data Streams with Apache SAMOA.

[BibT_eX]

[DOI]

Proceedings of the 6th International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015) co-located with the 26th European Conference on Machine Learning / 19th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), 2015

Efficient Online Evaluation of Big Data Stream Classifiers.

[BibT_eX]

[DOI]

Geoff Holmes

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams.

[BibT_eX]

[DOI]

Sripirakas Sakthithasan

Russel Pears

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

StreamDM: Advanced Data Mining in Spark Streaming.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2014

Active Learning With Drifting Streaming Data.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2014

A survey on concept drift adaptation.

[BibT_eX]

[DOI]

Abdelhamid Bouchachia

ACM Comput. Surv., 2014

Kaggle LSHTC4 Winning Solution.

[BibT_eX]

[DOI]

Antti Puurula

CoRR, 2014

Change detection in categorical evolving data streams.

[BibT_eX]

[DOI]

Proceedings of the Symposium on Applied Computing, 2014

Preface.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Workshop on Big Data, 2014

Multi-label Classification with Meta-Labels.

[BibT_eX]

[DOI]

Antti Puurula

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams.

[BibT_eX]

[DOI]

Brandon Parker

Latifur Khan

Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

Big Data Stream Learning with SAMOA.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

Détection de changements dans des flots de données qualitatives.

[BibT_eX]

[DOI]

Proceedings of the 14èmes Journées Francophones Extraction et Gestion des Connaissances, 2014

Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams.

[BibT_eX]

[DOI]

Diego Marron

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

Distributed Adaptive Model Rules for mining big data streams.

[BibT_eX]

[DOI]

Anh Thu Vu

João Gama

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013

Mining Big Data in Real Time.

[BibT_eX]

[DOI]

Informatica (Slovenia), 2013

Efficient data stream classification via probabilistic adaptive windows.

[BibT_eX]

[DOI]

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

STRIP: stream learning of influence probabilities.

[BibT_eX]

[DOI]

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

CD-MOA: Change Detection Framework for Massive Online Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XII, 2013

Clustering Based Active Learning for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 16th International Conference, 2013

2012

Ensembles of Restricted Hoeffding Trees.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2012

Next challenges for adaptive learning systems.

[BibT_eX]

[DOI]

SIGKDD Explor., 2012

Mining big data: current status, and forecast to the future.

[BibT_eX]

[DOI]

Wei Fan

SIGKDD Explor., 2012

Scalable and efficient multi-label classification for evolving data streams.

[BibT_eX]

[DOI]

Mach. Learn., 2012

Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Stream Data Mining Using the MOA Framework.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2012

2011

MOA Concept Drift Active Learning Strategies for Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Streaming Multi-label Classification.

[BibT_eX]

[DOI]

Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification.

[BibT_eX]

[DOI]

José M. Carmona-Cejudo

Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Detecting Sentiment Change in Twitter Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Mining frequent closed trees in evolving data streams.

[BibT_eX]

[DOI]

Intell. Data Anal., 2011

Active Learning with Evolving Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

MOA: A Real-Time Analytics Open Source Framework.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

An effective evaluation measure for clustering on evolving data streams.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Mining frequent closed graphs on evolving data streams.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Online Evaluation of Email Streaming Classifiers Using GNUsmail.

[BibT_eX]

[DOI]

José M. Carmona-Cejudo

Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data.

[BibT_eX]

[DOI]

Geoffrey Holmes

Proceedings of the Discovery Science - 14th International Conference, 2011

2010

Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams

[BibT_eX]

[DOI]

Frontiers in Artificial Intelligence and Applications 207, IOS Press, ISBN: 978-1-60750-090-2, 2010

Mining frequent closed rooted trees.

[BibT_eX]

[DOI]

Mach. Learn., 2010

MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering.

[BibT_eX]

[DOI]

Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

MOA: Massive Online Analysis.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking.

[BibT_eX]

[DOI]

Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Leveraging Bagging for Evolving Data Streams.

[BibT_eX]

[DOI]

Geoffrey Holmes

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Fast Perceptron Decision Tree Learning from Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA.

[BibT_eX]

[DOI]

Proceedings of the ICDMW 2010, 2010

GNUsmail: Open Framework for On-line Email Classification.

[BibT_eX]

[DOI]

José M. Carmona-Cejudo

Proceedings of the ECAI 2010, 2010

Sentiment Knowledge Discovery in Twitter Streaming Data.

[BibT_eX]

[DOI]

Eibe Frank

Proceedings of the Discovery Science - 13th International Conference, 2010

2009

Adaptive Learning and Mining for Data Streams and Frequent Patterns.

[BibT_eX]

[DOI]

PhD thesis, 2009

Adaptive learning and mining for data streams and frequent patterns.

[BibT_eX]

[DOI]

SIGKDD Explor., 2009

Adaptive XML Tree Classification on Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

New ensemble methods for evolving data streams.

[BibT_eX]

[DOI]

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Adaptive Learning from Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

Improving Adaptive Bagging Methods for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Advances in Machine Learning, 2009

2008

Mining adaptively frequent closed unlabeled rooted trees in data streams.

[BibT_eX]

[DOI]

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Mining Implications from Lattices of Closed Trees.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2008), 2008

2007

Learning from Time-Changing Data with Adaptive Windowing.

[BibT_eX]

[DOI]

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Mining Frequent Closed Unordered Trees Through Natural Representations.

[BibT_eX]

[DOI]

Proceedings of the Conceptual Structures: Knowledge Architectures for Smart Applications, 2007

Subtree Testing and Closed Tree Mining Through Natural Representations.

[BibT_eX]

[DOI]

Proceedings of the 18th International Workshop on Database and Expert Systems Applications (DEXA 2007), 2007

2006

Kalman Filters and Adaptive Windows for Learning in Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science, 9th International Conference, 2006

2005

An Analysis of Factors Used in Search Engine Ranking.

[BibT_eX]

[DOI]