|
|
|
⇣
|
Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams,
Maroua Bahri, Bernhard Pfahringer, Albert Bifet, Silviu Maniu,
IDA 2020
|
|
|
|
⇣
|
Survey on Feature Transformation Techniques for Data Streams,
Maroua Bahri, Albert Bifet, Silviu Maniu, Heitor Murilo Gomes,
IJCAI 2020
|
|
|
|
⇣
|
confStream - Automated Algorithm Selection and Configuration of Stream Clustering Algorithms,
Matthias Carnein, Heike Trautmann, Albert Bifet, Bernhard Pfahringer,
LION 2020
|
|
|
⇣
|
⇣
|
Network of Experts - Learning from Evolving Data Streams Through Network-Based Ensembles,
Heitor Murilo Gomes, Albert Bifet ■, Philippe Fournier Viger, Jones Granatyr, Jesse Read,
ICONIP 2019
|
|
|
⇣
|
⇣
|
Adaptive Algorithms for Estimating Betweenness and k-path Centralities,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
CIKM 2019, Beijing, France
|
|
|
⇣
|
⇣
|
Continuous Analytics of Web Streams,
Riccardo Tommasini, Robin Keskisarkka, Jean Paul Calbimonte, Eva Blomqvist, Emanuele Della Valle, Albert Bifet ■,
WWW 2019, San Francisco, United States
|
|
|
⇣
|
⇣
|
ORSUM 2019 2nd workshop on online recommender systems and user modeling,
João Vinagre, Alipio Mario Jorge, Albert Bifet ■, Marie Al Ghossein,
RecSys 2019, Copenhagen, France
|
|
|
⇣
|
|
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality Talel Abdessalem,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet ■,
22nd International Conference on Extending Database Technology EDBT 2019 2019, Lisbon, Portugal
|
|
|
⇣
|
⇣
|
Adaptive Random Forests with Resampling for Imbalanced data Streams,
Luis Eduardo Boiko Ferreira, Heitor Murilo Gomes, Albert Bifet ■, Luiz Oliveira,
IJCNN 2019, Budapest, France
|
|
|
|
⇣
|
Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams,
Dihia Boulegane, Albert Bifet ■, Giyyarpuram Madhusudan,
BigData 2019
|
|
|
|
⇣
|
Real-Time Machine Learning Competition on Data Streams at the IEEE Big Data 2019,
Dihia Boulegane, Nedeljko Radulovic, Albert Bifet ■, Ghislain Fievet, Jimin Sohn, Yeonwoo Nam, Seojeong Yu, Dong Wan Choi,
BigData 2019
|
|
|
|
⇣
|
Feature Scoring using Tree-Based Ensembles for Evolving Data Streams,
Heitor Murilo Gomes, Rodrigo Fernandes De Mello, Bernhard Pfahringer, Albert Bifet ■,
BigData 2019
|
|
|
|
⇣
|
Semi-supervised Learning over Streaming Data using MOA,
Minh Huong Le Nguyen, Heitor Murilo Gomes, Albert Bifet ■,
BigData 2019
|
|
|
|
⇣
|
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet ■,
EDBT 2019
|
|
|
|
⇣
|
Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets,
Albert Bifet ■, Barbara Hammer, Frank Michael Schleif,
ESANN 2019
|
|
|
|
⇣
|
Streaming Random Patches for Evolving Data Stream Classification,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■,
ICDM 2019
|
|
|
|
⇣
|
IDSA-IoT - An Intrusion Detection System Architecture for IoT Networks,
Guilherme Weigert Cassales, Hermes Senger, Elaine Ribeiro De Faria, Albert Bifet ■,
ISCC 2019
|
|
|
|
⇣
|
Towards Automated Configuration of Stream Clustering Algorithms,
Matthias Carnein, Heike Trautmann, Albert Bifet ■, Bernhard Pfahringer,
PKDD/ECML Workshops 2019
|
|
|
⇣
|
⇣
|
DyBED - An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
BigData 2018, Seattle, United States
|
|
|
⇣
|
⇣
|
An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
BigData 2018, Seattle, United States
|
|
|
⇣
|
⇣
|
Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data,
Andrian Putina ■, Steven Barth, Albert Bifet ■, Drew Pletcher, Cristina Precup, Patrice Nivaggioli, Dario Rossi ■,
INFOCOM Workshops 2018, Honolulu, United States
|
|
|
⇣
|
⇣
|
Adaptive random forests for data stream regression,
Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet ■,
ESANN 2018, Bruges, Belgium
|
|
|
⇣
|
⇣
|
Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
PAKDD 2018, Melbourne, Australia
|
|
|
⇣
|
⇣
|
Scalable Model-Based Cascaded Imputation of Missing Data,
Jacob Montiel, Jesse Read, Albert Bifet ■, Talel Abdessalem,
PAKDD 2018, Melbourne, Australia
|
|
|
⇣
|
⇣
|
Ubiquitous Artificial Intelligence and Dynamic Data Streams,
Albert Bifet ■, Jesse Read,
DEBS 2018, Hamilton, New Zealand
|
|
|
⇣
|
⇣
|
Telemetry-based stream-learning of BGP anomalies,
Andrian Putina ■, Dario Rossi ■, Albert Bifet ■, Steven Barth, Drew Pletcher, Cristina Precup, Patrice Nivaggioli,
Big-DAMA@SIGCOMM 2018, Budapest, Hungary
|
|
|
⇣
|
⇣
|
EXAD - A System for Explainable Anomaly Detection on Big Data Traces,
Fei Song, Yanlei Diao, Jesse Read, Arnaud Stiegler, Albert Bifet ■,
ICDM Workshops 2018, Singapore, Singapore
|
|
|
|
⇣
|
A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams,
Maroua Bahri, Silviu Maniu, Albert Bifet ■,
BigData 2018
|
|
|
|
⇣
|
Learning Fast and Slow - A Unified Batch/Stream Framework,
Jacob Montiel, Albert Bifet ■, Viktor Losing, Jesse Read, Talel Abdessalem,
BigData 2018
|
|
|
|
⇣
|
Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders,
Tian Guo, Albert Bifet ■, Nino Antulov Fantulin,
ICDM 2018
|
|
|
⇣
|
|
Internet of Things (IoT) Analytics,
Albert Bifet ■,
The 16th International Conference on Artificial Intelligence and Soft Computing ICAISC 2017 2017, Zakopane, Poland
|
|
|
⇣
|
⇣
|
Low-latency multi-threaded ensemble learning for dynamic big data streams,
Diego Marron, Eduard Ayguade, Jose Herrero, Jesse Read, Albert Bifet ■,
BigData 2017, Boston, France
|
|
|
⇣
|
|
Droplets Ensemble Learning on Drifting Data Streams,
Pierre-Xavier Loeffel, Albert Bifet ■, Christophe Marsala, Marcin Detyniecki,
16th International Symposium on Intelligent Data Analysis (IDA'2017) 2017, London, United Kingdom
|
|
|
|
⇣
|
Predicting over-indebtedness on batch and streaming data,
Jacob Montiel, Albert Bifet ■, Talel Abdessalem,
BigData 2017
|
|
|
|
⇣
|
Droplet Ensemble Learning on Drifting Data Streams,
Pierre Xavier Loeffel, Albert Bifet ■, Christophe Marsala, Marcin Detyniecki,
IDA 2017
|
|
|
|
⇣
|
Extremely Fast Decision Tree Mining for Evolving Data Streams,
Albert Bifet ■, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer,
KDD 2017
|
|
|
|
⇣
|
Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories,
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet ■,
WWW 2017
|
|
|
⇣
|
|
Massive Online Analytics for the Internet of Things (IoT),
Albert Bifet,
The 8th Asian Conference on Machine Learning 2016, Hamilton, New Zealand
|
|
|
|
⇣
|
Echo State Hoeffding Tree Learning,
Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguade, Jose Herrero,
ACML 2016
|
|
|
|
⇣
|
VHT - Vertical hoeffding tree,
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet, Arinto Murdopo,
BigData 2016
|
|
|
|
⇣
|
IoT Big Data Stream Mining,
Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan,
KDD 2016
|
|
|
|
⇣
|
On Dynamic Feature Weighting for Feature Drifting Data Streams,
Jean Paul Barddal, Heitor Murilo Gomes, Fabricio Enembreck, Bernhard Pfahringer, Albert Bifet,
ECML/PKDD 2016
|
|
|
|
⇣
|
Deferral classification of evolving temporal dependent data streams,
Michael Mayo, Albert Bifet,
SAC 2016
|
|
|
|
⇣
|
Analyzing Big Data Streams with Apache SAMOA,
Nicolas Kourtellis, Gianmarco De Francisci Morales, Albert Bifet,
MSM@WWW,MUSE@PKDD/ECML 2016
|
|
|
⇣
|
⇣
|
StreamDM - Advanced Data Mining in Spark Streaming,
Albert Bifet, Silviu Maniu, Jianfeng Qian, Guangjian Tian, Cheng He, Wei Fan,
ICDM Workshops 2015, Atlantic City, NJ, United States
|
|
|
|
⇣
|
Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams,
Sripirakas Sakthithasan, Russel Pears, Albert Bifet, Bernhard Pfahringer,
IJCNN 2015
|
|
|
|
⇣
|
Efficient Online Evaluation of Big Data Stream Classifiers,
Albert Bifet, Gianmarco De Francisci Morales, Jesse Read, Geoff Holmes, Bernhard Pfahringer,
KDD 2015
|
|
|
|
⇣
|
Preface,
Wei Fan, Albert Bifet, Qiang Yang, Philip Yu,
BigMine 2015
|
|
|
|
⇣
|
Drift Detection Using Stream Volatility,
David Tse Jung Huang, Yun Sing Koh, Gillian Dobbie, Albert Bifet,
ECML/PKDD 2015
|
|
|
|
⇣
|
Deep learning in partially-labeled data streams,
Jesse Read, Fernando Perez Cruz, Albert Bifet,
SAC 2015
|
|
|
|
⇣
|
Distributed Adaptive Model Rules for mining big data streams,
Anh Thu Vu, Gianmarco De Francisci Morales, João Gama, Albert Bifet,
BigData 2014
|
|
|
|
⇣
|
Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams,
Diego Marron, Albert Bifet, Gianmarco De Francisci Morales,
ECAI 2014
|
|
|
|
⇣
|
Détection de changements dans des flots de données qualitatives,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
EGC 2014
|
|
|
|
⇣
|
Big Data Stream Learning with SAMOA,
Albert Bifet, Gianmarco De Francisci Morales,
ICDM Workshops 2014
|
|
|
|
⇣
|
Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams,
Brandon Parker, Latifur Khan, Albert Bifet,
ICDM Workshops 2014
|
|
|
|
⇣
|
Multi-label Classification with Meta-Labels,
Jesse Read, Antti Puurula, Albert Bifet,
ICDM 2014
|
|
|
|
⇣
|
Change detection in categorical evolving data streams,
Dino Ienco, Albert Bifet, Bernhard Pfahringer, Pascal Poncelet,
SAC 2014
|
|
|
|
⇣
|
Clustering Based Active Learning for Evolving Data Streams,
Dino Ienco, Albert Bifet, Indre Zliobaite, Bernhard Pfahringer,
Discovery Science 2013
|
|
|
|
⇣
|
CD-MOA - Change Detection Framework for Massive Online Analysis,
Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indre Zliobaite,
IDA 2013
|
|
|
|
⇣
|
STRIP - stream learning of influence probabilities,
Konstantin Kutzkov, Albert Bifet, Francesco Bonchi, Aristides Gionis,
KDD 2013
|
|
|
|
⇣
|
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them,
Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes,
ECML/PKDD 2013
|
|
|
|
⇣
|
Efficient data stream classification via probabilistic adaptive windows,
Albert Bifet, Bernhard Pfahringer, Jesse Read, Geoff Holmes,
SAC 2013
|
|
|
|
⇣
|
Stream Data Mining Using the MOA Framework,
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read,
DASFAA 2012
|
|
|
|
⇣
|
Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data,
Jesse Read, Albert Bifet, Bernhard Pfahringer, Geoff Holmes,
IDA 2012
|
|
|
|
⇣
|
MOA-TweetReader - Real-Time Analysis in Twitter Streaming Data,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer,
Discovery Science 2011
|
|
|
|
⇣
|
Online Evaluation of Email Streaming Classifiers Using GNUsmail,
Jose Carmona Cejudo, Manuel Baena Garcia, Jose Del Campo Avila, Albert Bifet, João Gama, Rafael Morales Bueno,
IDA 2011
|
|
|
|
⇣
|
Mining frequent closed graphs on evolving data streams,
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Ricard Gavalda,
KDD 2011
|
|
|
|
⇣
|
An effective evaluation measure for clustering on evolving data streams,
Hardy Kremer, Philipp Kranen, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
KDD 2011
|
|
|
|
⇣
|
MOA - A Real-Time Analytics Open Source Framework,
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl,
ECML/PKDD 2011
|
|
|
|
⇣
|
Active Learning with Evolving Streaming Data,
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoff Holmes,
ECML/PKDD 2011
|
|
|
|
⇣
|
Detecting Sentiment Change in Twitter Streaming Data,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavalda,
WAPA 2011
|
|
|
|
⇣
|
Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification,
Jose Carmona Cejudo, Manuel Baena Garcia, Rafael Morales Bueno, João Gama, Albert Bifet,
WAPA 2011
|
|
|
|
⇣
|
Streaming Multi-label Classification,
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
WAPA 2011
|
|
|
|
⇣
|
MOA Concept Drift Active Learning Strategies for Streaming Data,
Indre Zliobaite, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
WAPA 2011
|
|
|
|
⇣
|
Sentiment Knowledge Discovery in Twitter Streaming Data,
Albert Bifet, Eibe Frank,
Discovery Science 2010
|
|
|
|
⇣
|
GNUsmail - Open Framework for On-line Email Classification,
Jose Carmona Cejudo, Manuel Baena Garcia, Jose Del Campo Avila, Rafael Morales Bueno, Albert Bifet,
ECAI 2010
|
|
|
|
⇣
|
Clustering Performance on Evolving Data Streams - Assessing Algorithms and Evaluation Measures within MOA,
Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
ICDM Workshops 2010
|
|
|
|
⇣
|
Fast Perceptron Decision Tree Learning from Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank,
PAKDD 2010
|
|
|
|
⇣
|
Leveraging Bagging for Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer,
ECML/PKDD 2010
|
|
|
|
⇣
|
Accurate Ensembles for Data Streams - Combining Restricted Hoeffding Trees using Stacking,
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer,
ACML 2010
|
|
|
|
⇣
|
MOA - Massive Online Analysis, a Framework for Stream Classification and Clustering,
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl,
WAPA 2010
|
|
|
|
⇣
|
Improving Adaptive Bagging Methods for Evolving Data Streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavalda,
ACML 2009
|
|
|
|
⇣
|
Adaptive Learning from Evolving Data Streams,
Albert Bifet, Ricard Gavalda,
IDA 2009
|
|
|
|
⇣
|
New ensemble methods for evolving data streams,
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Ricard Gavalda,
KDD 2009
|
|
|
|
⇣
|
Adaptive XML Tree Classification on Evolving Data Streams,
Albert Bifet, Ricard Gavalda,
ECML/PKDD 2009
|
|
|
|
⇣
|
Mining Implications from Lattices of Closed Trees,
Jose Balcazar, Albert Bifet, Antoni Lozano,
EGC 2008
|
|
|
|
⇣
|
Mining adaptively frequent closed unlabeled rooted trees in data streams,
Albert Bifet, Ricard Gavalda,
KDD 2008
|
|
|
|
⇣
|
Subtree Testing and Closed Tree Mining Through Natural Representations,
Jose Balcazar, Albert Bifet, Antoni Lozano,
DEXA Workshops 2007
|
|
|
|
⇣
|
Mining Frequent Closed Unordered Trees Through Natural Representations,
Jose Balcazar, Albert Bifet, Antoni Lozano,
ICCS 2007
|
|
|
|
⇣
|
Learning from Time-Changing Data with Adaptive Windowing,
Albert Bifet, Ricard Gavalda,
SDM 2007
|
|
|
|
⇣
|
Kalman Filters and Adaptive Windows for Learning in Data Streams,
Albert Bifet, Ricard Gavalda,
Discovery Science 2006
|
|
|
|
⇣
|
An Analysis of Factors Used in Search Engine Ranking,
Albert Bifet, Carlos Castillo, Paul Alexandru Chirita, Ingmar Weber,
AIRWeb 2005
|
|
|
⇣
|
⇣
|
Spiking Neural Networks and online learning - An overview and perspectives,
Jesus Lobo, Javier Del Ser, Albert Bifet, Nikola Kasabov,
Neural Networks 2020
|
|
|
|
⇣
|
Sampling informative patterns from large single networks,
Mostafa Haghir Chehreghani, Talel Abdessalem, Albert Bifet, Meriem Bouzbila,
Future Gener. Comput. Syst. 2020
|
|
|
|
⇣
|
Discriminative Streaming Network Embedding,
Yiyan Qi, Jiefeng Cheng, Xiaojun Chen, Reynold Cheng, Albert Bifet, Pinghui Wang,
Knowl. Based Syst. 2020
|
|
|
|
⇣
|
Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning,
Jesus Lobo, Izaskun Oregi, Albert Bifet, Javier Del Ser,
Neural Networks 2020
|
|
|
⇣
|
⇣
|
Recurring concept meta-learning for evolving data streams,
Robert Anderson, Yun Sing Koh, Gillian Dobbie, Albert Bifet ■,
Expert Systems with Applications 2019
|
|
|
⇣
|
|
Machine learning for streaming data,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■, Jean Paul Barddal, João Gama,
ACM SIGKDD Explorations Newsletter (ACM Digital Library) 2019
|
|
|
⇣
|
⇣
|
Boosting decision stumps for dynamic feature selection on data streams,
Jean Paul Barddal, Fabricio Enembreck, Heitor Murilo Gomes, Albert Bifet ■, Bernhard Pfahringer,
Information Systems 2019
|
|
|
⇣
|
⇣
|
Efficient frequent subgraph mining on large streaming graphs,
Abhik Ray, Lawrence Holder, Albert Bifet ■,
Intelligent Data Analysis 2019
|
|
|
⇣
|
⇣
|
Measuring the Shattering coefficient of Decision Tree models,
Rodrigo Fernandes De Mello, Chaitanya Manapragada, Albert Bifet ■,
Expert Systems with Applications 2019
|
|
|
⇣
|
⇣
|
On learning guarantees to unsupervised concept drift detection on data streams,
Rodrigo Fernandes De Mello, Yule Vaz, Carlos Henrique Grossi Ferreira, Albert Bifet ■,
Expert Systems with Applications 2019
|
|
|
⇣
|
⇣
|
Merit-guided dynamic feature selection filter for data streams,
Jean Paul Barddal, Fabricio Enembreck, Heitor Murilo Gomes, Albert Bifet ■, Bernhard Pfahringer,
Expert Syst. Appl. 2019
|
|
|
|
⇣
|
Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining,
Jesse Read, Albert Bifet ■, Wei Fan, Qiang Yang, Philip Yu,
Int. J. Data Sci. Anal. 2019
|
|
|
|
⇣
|
Correction to - Adaptive random forests for evolving data stream classification,
Heitor Murilo Gomes, Albert Bifet ■, Jesse Read, Jean Paul Barddal, Fabricio Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem,
Mach. Learn. 2019
|
|
|
|
⇣
|
Machine learning for streaming data - state of the art, challenges, and opportunities,
Heitor Murilo Gomes, Jesse Read, Albert Bifet ■, Jean Paul Barddal, João Gama,
SIGKDD Explorations 2019
|
|
|
⇣
|
⇣
|
Scikit-Multiflow - A Multi-output Streaming Framework,
Jacob Montiel, Jesse Read, Albert Bifet ■, Talel Abdessalem,
Journal of Machine Learning Research 2018
|
|
|
⇣
|
⇣
|
Discriminative Distance-Based Network Indices with Application to Link Prediction,
Mostafa Haghir Chehreghani, Albert Bifet ■, Talel Abdessalem,
The Computer Journal 2018
|
|
|
|
⇣
|
Predicting attributes and friends of mobile users from AP-Trajectories,
Pinghui Wang, Feiyang Sun, Di Wang, Jing Tao, Xiaohong Guan, Albert Bifet ■,
Inf. Sci. 2018
|
|
|
⇣
|
⇣
|
Adaptive random forests for evolving data stream classification,
Heitor Murilo Gomes, Albert Bifet ■, Jesse Read, Jean Paul Barddal, Fabricio Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem,
Machine Learning 2017
|
|
|
⇣
|
⇣
|
Data stream classification using random feature functions and novel method combinations,
Diego Marron, Jesse Read, Albert Bifet ■, Nacho Navarro,
Journal of Systems and Software 2017
|
|
|
⇣
|
⇣
|
A Survey on Ensemble Learning for Data Stream Classification,
Heitor Murilo Gomes, Jean Paul Barddal, Fabricio Enembreck, Albert Bifet ■,
ACM Computing Surveys 2017
|
|
|
|
⇣
|
A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic,
Valentin Carela Español, Pere Barlet Ros, Albert Bifet, Kensuke Fukuda,
Telecommun. Syst. 2016
|
|
|
|
⇣
|
Adaptive Model Rules From High-Speed Data Streams,
João Duarte, João Gama, Albert Bifet,
ACM Trans. Knowl. Discov. Data 2016
|
|
|
|
⇣
|
An efficient closed frequent itemset miner for the MOA stream mining system,
Massimo Quadrana, Albert Bifet, Ricard Gavalda,
AI Commun. 2015
|
|
|
|
⇣
|
SAMOA - scalable advanced massive online analysis,
Gianmarco De Francisci Morales, Albert Bifet,
J. Mach. Learn. Res. 2015
|
|
|
|
⇣
|
Evaluation methods and decision theory for classification of streaming data with temporal dependence,
Indre Zliobaite, Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes,
Mach. Learn. 2015
|
|
|
|
⇣
|
A survey on concept drift adaptation,
João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia,
ACM Comput. Surv. 2014
|
|
|
|
⇣
|
Active Learning With Drifting Streaming Data,
Indre Zliobaite, Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes,
IEEE Trans. Neural Networks Learn. Syst. 2014
|
|
|
|
⇣
|
Scalable and efficient multi-label classification for evolving data streams,
Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer,
Mach. Learn. 2012
|
|
|
|
⇣
|
Mining big data - current status, and forecast to the future,
Wei Fan, Albert Bifet,
SIGKDD Explorations 2012
|
|
|
|
⇣
|
Next challenges for adaptive learning systems,
Indre Zliobaite, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, João Gama, Leandro Minku, Katarzyna Musial,
SIGKDD Explorations 2012
|
|
|
|
⇣
|
Ensembles of Restricted Hoeffding Trees,
Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer,
ACM Trans. Intell. Syst. Technol. 2012
|
|
|
|
⇣
|
Mining frequent closed trees in evolving data streams,
Albert Bifet, Ricard Gavalda,
Intell. Data Anal. 2011
|
|
|
|
⇣
|
MOA - Massive Online Analysis,
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer,
J. Mach. Learn. Res. 2010
|
|
|
|
⇣
|
Mining frequent closed rooted trees,
Jose Balcazar, Albert Bifet, Antoni Lozano,
Mach. Learn. 2010
|