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Jesse Read
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2020 – today
- 2024
- [j34]Ekaterina Antonenko, Ander Carreño, Jesse Read:
Autoreplicative random forests with applications to missing value imputation. Mach. Learn. 113(10): 7617-7643 (2024) - [c44]Ayman Chaouki, Jesse Read, Albert Bifet:
Online Learning of Decision Trees with Thompson Sampling. AISTATS 2024: 2944-2952 - [c43]Ekaterina Antonenko
, Michael Mechenich
Backward Inference in Probabilistic Regressor Chains with Distributional Constraints. IDA (2) 2024: 43-55 - [i33]Ayman Chaouki, Jesse Read, Albert Bifet:
Online Learning of Decision Trees with Thompson Sampling. CoRR abs/2404.06403 (2024) - [i32]Ayman Chaouki, Jesse Read, Albert Bifet:
Branches: A Fast Dynamic Programming and Branch & Bound Algorithm for Optimal Decision Trees. CoRR abs/2406.02175 (2024) - [i31]Elaine Cecília Gatto, Felipe Kenji Nakano, Jesse Read, Mauri Ferrandin, Ricardo Cerri, Celine Vens:
Label Cluster Chains for Multi-Label Classification. CoRR abs/2411.00514 (2024) - 2023
- [j33]Jesse Read
From multi-label learning to cross-domain transfer: a model-agnostic approach. Appl. Intell. 53(21): 25135-25153 (2023) - [j32]Heitor Murilo Gomes
A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams. ACM Comput. Surv. 55(4): 75:1-75:42 (2023) - [j31]Eran Zvuloni
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG. IEEE Trans. Biomed. Eng. 70(7): 2227-2236 (2023) - [c42]Mohamed Alami Chehboune, Rim Kaddah, Jesse Read:
Transferable Deep Metric Learning for Clustering. IDA 2023: 15-28 - [c41]Célia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read, Sonali Parbhoo:
Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk. MLHC 2023: 31-49 - [i30]Ekaterina Antonenko, Jesse Read:
Chains of Autoreplicative Random Forests for missing value imputation in high-dimensional datasets. CoRR abs/2301.00595 (2023) - [i29]Simo Alami C, Rim Kaddah, Jesse Read:
Transferable Deep Metric Learning for Clustering. CoRR abs/2302.06523 (2023) - [i28]Célia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read:
Shapley Chains: Extending Shapley Values to Classifier Chains. CoRR abs/2303.17243 (2023) - [i27]Alban Puech, Jesse Read:
An Improved Yaw Control Algorithm for Wind Turbines via Reinforcement Learning. CoRR abs/2305.01299 (2023) - [i26]Alban Puech, Jesse Read:
Uncovering the Spatial and Temporal Variability of Wind Resources in Europe: A Web-Based Data-Mining Tool. CoRR abs/2305.01343 (2023) - [i25]Indre Zliobaite, Jesse Read:
A Historical Context for Data Streams. CoRR abs/2310.19811 (2023) - 2022
- [j30]Rita Beigaite
Multi-output regression with structurally incomplete target labels: A case study of modelling global vegetation cover. Ecol. Informatics 72: 101849 (2022) - [j29]Fernando Llorente
Optimality in noisy importance sampling. Signal Process. 194: 108455 (2022) - [c40]Célia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read:
Shapley Chains: Extending Shapley Values to Classifier Chains. DS 2022: 541-555 - [c39]Mohamed Alami Chehboune, Rim Kaddah, Luca Martino, Fernando Llorente, Jesse Read:
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies. EUSIPCO 2022: 1482-1486 - [c38]Ekaterina Antonenko, Jesse Read:
Multi-modal Ensembles of Regressor Chains for Multi-output Prediction. IDA 2022: 1-13 - [c37]Peng Yu, Albert Bifet, Jesse Read, Chao Xu:
Linear tree shap. NeurIPS 2022 - [c36]Mohamed Alami Chehboune
Conv-NILM-Net, a Causal and Multi-appliance Model for Energy Source Separation. PKDD/ECML Workshops (2) 2022: 207-222 - [c35]Alban Puech
An Improved Yaw Control Algorithm for Wind Turbines via Reinforcement Learning. ECML/PKDD (5) 2022: 614-630 - [c34]Sonal Sannigrahi, Jesse Read:
Isomorphic Cross-lingual Embeddings for Low-Resource Languages. RepL4NLP@ACL 2022: 133-142 - [i24]Fernando Llorente, Luca Martino, Jesse Read, David Delgado-Gómez:
Optimality in Noisy Importance Sampling. CoRR abs/2201.02432 (2022) - [i23]Sonal Sannigrahi, Jesse Read:
Isomorphic Cross-lingual Embeddings for Low-Resource Languages. CoRR abs/2203.14632 (2022) - [i22]Mohamed Alami Chehboune, Fernando Llorente, Rim Kaddah, Luca Martino, Jesse Read:
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies. CoRR abs/2205.09433 (2022) - [i21]Eran Zvuloni, Jesse Read, Antônio H. Ribeiro, Antônio Luiz P. Ribeiro, Joachim A. Behar:
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG. CoRR abs/2207.06096 (2022) - [i20]Jesse Read:
From Multi-label Learning to Cross-Domain Transfer: A Model-Agnostic Approach. CoRR abs/2207.11742 (2022) - [i19]Mohamed Alami Chehboune, Jérémie Decock, Rim Kaddah, Jesse Read:
Conv-NILM-Net, a causal and multi-appliance model for energy source separation. CoRR abs/2208.02173 (2022) - [i18]Laurence A. F. Park, Jesse Read:
Estimating Multi-label Accuracy using Labelset Distributions. CoRR abs/2209.04163 (2022) - [i17]Peng Yu, Chao Xu, Albert Bifet, Jesse Read:
Linear TreeShap. CoRR abs/2209.08192 (2022) - [i16]Jesse Read, Indre Zliobaite:
Learning from Data Streams: An Overview and Update. CoRR abs/2212.14720 (2022) - 2021
- [j28]Sammy Khalife
Structure and influence in a global capital-ownership network. Appl. Netw. Sci. 6(1): 16 (2021) - [j27]Luca Martino
A joint introduction to Gaussian Processes and Relevance Vector Machines with connections to Kalman filtering and other kernel smoothers. Inf. Fusion 74: 17-38 (2021) - [j26]Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank:
Classifier Chains: A Review and Perspectives. J. Artif. Intell. Res. 70: 683-718 (2021) - [j25]Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphaël Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet:
River: machine learning for streaming data in Python. J. Mach. Learn. Res. 22: 110:1-110:8 (2021) - [j24]Heitor Murilo Gomes
Learning from evolving data streams through ensembles of random patches. Knowl. Inf. Syst. 63(7): 1597-1625 (2021) - [e6]Nuria Oliver
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12975, Springer 2021, ISBN 978-3-030-86485-9 [contents] - [e5]Nuria Oliver
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12976, Springer 2021, ISBN 978-3-030-86519-1 [contents] - [e4]Nuria Oliver
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12977, Springer 2021, ISBN 978-3-030-86522-1 [contents] - [i15]Heitor Murilo Gomes
A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams. CoRR abs/2106.09170 (2021) - 2020
- [j23]Jesse Read, Luca Martino
Probabilistic regressor chains with Monte Carlo methods. Neurocomputing 413: 471-486 (2020) - [j22]Adriano Rivolli
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. Mach. Learn. 109(8): 1509-1563 (2020) - [c33]Jesse Read
Data Streams Are Time Series: Challenging Assumptions. BRACIS (2) 2020: 529-543 - [c32]Kayo Yin, Jesse Read:
Better Sign Language Translation with STMC-Transformer. COLING 2020: 5975-5989 - [e3]Albert Bifet, Michele Berlingerio, João Gama, Jesse Read, Ana Rita Nogueira
Proceedings of the 8th International Workshop on Big Data, IoT Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications co-located with 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August 4-8, 2019. CEUR Workshop Proceedings 2579, CEUR-WS.org 2020 [contents] - [i14]Luca Martino, Jesse Read:
Joint introduction to Gaussian Processes and Relevance Vector Machines with Connections to Kalman filtering and other Kernel Smoothers. CoRR abs/2009.09217 (2020) - [i13]Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphaël Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes
River: machine learning for streaming data in Python. CoRR abs/2012.04740 (2020)
2010 – 2019
- 2019
- [j21]Jesse Read, Albert Bifet
Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining. Int. J. Data Sci. Anal. 8(3): 221-222 (2019) - [j20]Heitor Murilo Gomes
Correction to: Adaptive random forests for evolving data stream classification. Mach. Learn. 108(10): 1877-1878 (2019) - [j19]Jesse Read
Error-space representations for multi-dimensional data streams with temporal dependence. Pattern Anal. Appl. 22(3): 1211-1220 (2019) - [j18]Heitor Murilo Gomes
Machine learning for streaming data: state of the art, challenges, and opportunities. SIGKDD Explor. 21(2): 6-22 (2019) - [c31]Antoine J.-P. Tixier, Maria-Evgenia G. Rossi
Perturb and combine to identify influential spreaders in real-world networks. ASONAM 2019: 73-80 - [c30]Sammy Khalife
Empirical Analysis of a Global Capital-Ownership Network. COMPLEX NETWORKS (2) 2019: 656-667 - [c29]Heitor Murilo Gomes
Streaming Random Patches for Evolving Data Stream Classification. ICDM 2019: 240-249 - [c28]Heitor Murilo Gomes
Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles. ICONIP (1) 2019: 704-716 - [c27]Laurence A. F. Park, Yi Guo, Jesse Read:
Assessing the Multi-labelness of Multi-label Data. ECML/PKDD (2) 2019: 164-179 - [i12]Jesse Read, Luca Martino:
Probabilistic Regressor Chains with Monte Carlo Methods. CoRR abs/1907.08087 (2019) - [i11]Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank:
Classifier Chains: A Review and Perspectives. CoRR abs/1912.13405 (2019) - 2018
- [j17]Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem:
Scikit-Multiflow: A Multi-output Streaming Framework. J. Mach. Learn. Res. 19: 72:1-72:5 (2018) - [j16]Roelant A. Stegmann, Indre Zliobaite
A survey of evaluation methods for personal route and destination prediction from mobility traces. WIREs Data Mining Knowl. Discov. 8(2) (2018) - [c26]Olivier Pallanca, Sammy Khalife
Detection of sleep spindles in NREM 2 sleep stages: Preliminary study & benchmarking of algorithms. BIBM 2018: 2652-2655 - [c25]Jacob Montiel
Learning Fast and Slow: A Unified Batch/Stream Framework. IEEE BigData 2018: 1065-1072 - [c24]Albert Bifet
Ubiquitous Artificial Intelligence and Dynamic Data Streams. DEBS 2018: 1-6 - [c23]Fei Song, Yanlei Diao, Jesse Read, Arnaud Stiegler, Albert Bifet
EXAD: A System for Explainable Anomaly Detection on Big Data Traces. ICDM Workshops 2018: 1435-1440 - [c22]Ngurah Agus Sanjaya
Set Labelling using Multi-label Classification. iiWAS 2018: 216-220 - [c21]Jacob Montiel
Scalable Model-Based Cascaded Imputation of Missing Data. PAKDD (3) 2018: 64-76 - [c20]Laurence A. F. Park, Jesse Read:
A Blended Metric for Multi-label Optimisation and Evaluation. ECML/PKDD (1) 2018: 719-734 - [i10]Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem:
Scikit-Multiflow: A Multi-output Streaming Framework. CoRR abs/1807.04662 (2018) - [i9]Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, Michalis Vazirgiannis:
Perturb and Combine to Identify Influential Spreaders in Real-World Networks. CoRR abs/1807.09586 (2018) - [i8]Jesse Read:
Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation. CoRR abs/1810.02266 (2018) - 2017
- [j15]Luca Martino
Cooperative parallel particle filters for online model selection and applications to urban mobility. Digit. Signal Process. 60: 172-185 (2017) - [j14]Diego Marron, Jesse Read, Albert Bifet
Data stream classification using random feature functions and novel method combinations. J. Syst. Softw. 127: 195-204 (2017) - [j13]Heitor Murilo Gomes
Adaptive random forests for evolving data stream classification. Mach. Learn. 106(9-10): 1469-1495 (2017) - [j12]Jesse Read, Luca Martino
Multi-label methods for prediction with sequential data. Pattern Recognit. 63: 45-55 (2017) - [c19]Diego Marron, Eduard Ayguadé, José R. Herrero, Jesse Read, Albert Bifet
Low-latency multi-threaded ensemble learning for dynamic big data streams. IEEE BigData 2017: 223-232 - [e2]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - 2016
- [j11]Jesse Read, Indre Zliobaite
Labeling sensing data for mobility modeling. Inf. Syst. 57: 207-222 (2016) - [j10]Jesse Read, Peter Reutemann, Bernhard Pfahringer, Geoff Holmes:
MEKA: A Multi-label/Multi-target Extension to WEKA. J. Mach. Learn. Res. 17: 21:1-21:5 (2016) - [c18]Diego Marron, Jesse Read, Albert Bifet, Talel Abdessalem, Eduard Ayguadé, José R. Herrero:
Echo State Hoeffding Tree Learning. ACML 2016: 382-397 - [e1]Wei Fan, Albert Bifet, Jesse Read, Qiang Yang, Philip S. Yu:
Proceedings of the 5th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, BigMine 2016, San Francisco, CA, USA, August 14, 2016. JMLR Workshop and Conference Proceedings 53, JMLR.org 2016 [contents] - [i7]Jesse Read, Luca Martino, Jaakko Hollmén:
Multi-label Methods for Prediction with Sequential Data. CoRR abs/1609.08349 (2016) - 2015
- [j9]Indre Zliobaite
Evaluation methods and decision theory for classification of streaming data with temporal dependence. Mach. Learn. 98(3): 455-482 (2015) - [j8]Jesse Read, Luca Martino, Pablo M. Olmos
Scalable multi-output label prediction: From classifier chains to classifier trellises. Pattern Recognit. 48(6): 2096-2109 (2015) - [j7]Luca Martino
Independent Doubly Adaptive Rejection Metropolis Sampling Within Gibbs Sampling. IEEE Trans. Signal Process. 63(12): 3123-3138 (2015) - [c17]Albert Bifet
Efficient Online Evaluation of Big Data Stream Classifiers. KDD 2015: 59-68 - [c16]Jesse Read, Fernando Pérez-Cruz
Deep learning in partially-labeled data streams. SAC 2015: 954-959 - [c15]Jesse Read, Albert Bifet
Data Stream Classification Using Random Feature Functions and Novel Method Combinations. TrustCom/BigDataSE/ISPA (2) 2015: 211-216 - [i6]Jesse Read, Luca Martino, Pablo M. Olmos, David Luengo:
Scalable Multi-Output Label Prediction: From Classifier Chains to Classifier Trellises. CoRR abs/1501.04870 (2015) - [i5]Jesse Read, Fernando Pérez-Cruz:
Deep Learning for Multi-label Classification. CoRR abs/1502.05988 (2015) - [i4]Jesse Read, Jaakko Hollmén:
Multi-label Classification using Labels as Hidden Nodes. CoRR abs/1503.09022 (2015) - [i3]Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro:
Data Stream Classification using Random Feature Functions and Novel Method Combinations. CoRR abs/1511.00971 (2015) - 2014
- [j6]Jesse Read, Luca Martino
Efficient monte carlo methods for multi-dimensional learning with classifier chains. Pattern Recognit. 47(3): 1535-1546 (2014) - [j5]Jesse Read, Katrin Achutegui, Joaquín Míguez
A distributed particle filter for nonlinear tracking in wireless sensor networks. Signal Process. 98: 121-134 (2014) - [j4]Jesse Read, Concha Bielza
Multi-Dimensional Classification with Super-Classes. IEEE Trans. Knowl. Data Eng. 26(7): 1720-1733 (2014) - [c14]Luca Martino
Independent doubly Adaptive Rejection Metropolis Sampling. ICASSP 2014: 7998-8002 - [c13]Jesse Read, Antti Puurula, Albert Bifet
Multi-label Classification with Meta-Labels. ICDM 2014: 941-946 - [c12]Jesse Read, Jaakko Hollmén:
A Deep Interpretation of Classifier Chains. IDA 2014: 251-262 - [c11]Grigorios Tsoumakas, Apostolos Papadopoulos, Weining Qian, Stavros Vologiannidis, Alexander D'yakonov, Antti Puurula, Jesse Read, Jan Svec, Stanislav Semenov:
WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics. WISE (2) 2014: 541-548 - [i2]Antti Puurula, Jesse Read, Albert Bifet:
Kaggle LSHTC4 Winning Solution. CoRR abs/1405.0546 (2014) - 2013
- [j3]Luca Martino
On the flexibility of the design of multiple try Metropolis schemes. Comput. Stat. 28(6): 2797-2823 (2013) - [c10]Jesse Read, Luca Martino
Efficient monte carlo optimization for multi-label classifier chains. ICASSP 2013: 3457-3461 - [c9]Albert Bifet
CD-MOA: Change Detection Framework for Massive Online Analysis. IDA 2013: 92-103 - [c8]Albert Bifet
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them. ECML/PKDD (1) 2013: 465-479 - [c7]Albert Bifet
Efficient data stream classification via probabilistic adaptive windows. SAC 2013: 801-806 - 2012
- [j2]Jesse Read, Albert Bifet
Scalable and efficient multi-label classification for evolving data streams. Mach. Learn. 88(1-2): 243-272 (2012) - [c6]Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl
Stream Data Mining Using the MOA Framework. DASFAA (2) 2012: 309-313 - [c5]Jesse Read, Albert Bifet
Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data. IDA 2012: 313-323 - [i1]Jesse Read, Luca Martino, David Luengo:
Efficient Monte Carlo Optimization for Multi-label Classifier Chains. CoRR abs/1211.2190 (2012) - 2011
- [j1]Jesse Read, Bernhard Pfahringer, Geoff Holmes
Classifier chains for multi-label classification. Mach. Learn. 85(3): 333-359 (2011) - [c4]Albert Bifet
MOA: A Real-Time Analytics Open Source Framework. ECML/PKDD (3) 2011: 617-620 - [c3]Jesse Read, Albert Bifet, Geoff Holmes, Bernhard Pfahringer:
Streaming Multi-label Classification. WAPA 2011: 19-25
2000 – 2009
- 2009
- [c2]Jesse Read, Bernhard Pfahringer, Geoffrey Holmes
Classifier Chains for Multi-label Classification. ECML/PKDD (2) 2009: 254-269 - 2008
- [c1]Jesse Read, Bernhard Pfahringer, Geoffrey Holmes
Multi-label Classification Using Ensembles of Pruned Sets. ICDM 2008: 995-1000
Coauthor Index
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