Special Issue: Foundations of Data Science

Guest Editors: João Gama, Alípio Jorge, Salvador García

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

João Gama

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Alípio Jorge

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Salvador García

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Showing 1-29 of 29 articles

Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment
Théo Verhelst
Denis Mercier
Gianluca Bontempi
OriginalPaper 14 March 2023 Pages: 1043 - 1067
PAC-learning with approximate predictors
Andrew J. Turner
Ata Kabán
OriginalPaper Open access 08 February 2023 Pages: 1693 - 1732
Reconciling privacy and utility: an unscented Kalman filter-based framework for differentially private machine learning
Kunsheng Tang
Ping Li
Tian Luo
OriginalPaper 07 December 2022 Pages: 311 - 351
Attacking neural machine translations via hybrid attention learning
Mingze Ni
Ce Wang
Wei Liu
OriginalPaper Open access 20 October 2022 Pages: 3977 - 4002
Scaling up stochastic gradient descent for non-convex optimisation
Saad Mohamad
Hamad Alamri
Abdelhamid Bouchachia
OriginalPaper Open access 07 October 2022 Pages: 4039 - 4079
Machine learning in corporate credit rating assessment using the expanded audit report
Nora Muñoz-Izquierdo
María Jesús Segovia-Vargas
Yolanda Pérez-Pérez
OriginalPaper 30 September 2022 Pages: 4183 - 4215
A unified framework for online trip destination prediction
Victor Eberstein
Jonas Sjöblom
Morteza Haghir Chehreghani
OriginalPaper Open access 05 July 2022 Pages: 3839 - 3865
Robust reputation independence in ranking systems for multiple sensitive attributes
Guilherme Ramos
Ludovico Boratto
Mirko Marras
OriginalPaper Open access 10 June 2022 Pages: 3769 - 3796
Traditional and context-specific spam detection in low resource settings
Kornraphop Kawintiranon
Lisa Singh
Ceren Budak
OriginalPaper 09 June 2022 Pages: 2515 - 2536
Semi-parametric Bayes regression with network-valued covariates
Xin Ma
Suprateek Kundu
Jennifer Stevens
OriginalPaper 02 June 2022 Pages: 3733 - 3767
InfoGram and admissible machine learning
Subhadeep Mukhopadhyay
OriginalPaper 10 January 2022 Pages: 205 - 242
Efficient fair principal component analysis
Mohammad Mahdi Kamani
Farzin Haddadpour
Mehrdad Mahdavi
OriginalPaper 06 January 2022 Pages: 3671 - 3702
SAMBA: safe model-based & active reinforcement learning
Alexander I. Cowen-Rivers
Daniel Palenicek
Haitham Bou-Ammar
OriginalPaper 04 January 2022 Pages: 173 - 203
A network-based positive and unlabeled learning approach for fake news detection
Mariana Caravanti de Souza
Bruno Magalhães Nogueira
Solange Oliveira Rezende
OriginalPaper 18 November 2021 Pages: 3549 - 3592
ZipLine: an optimized algorithm for the elastic bulk synchronous parallel model
Xing Zhao
Manos Papagelis
Yonggang Hu
OriginalPaper 19 October 2021 Pages: 2867 - 2903
MLife: a lite framework for machine learning lifecycle initialization
Cong Yang
Wenfeng Wang
John See
OriginalPaper 14 October 2021 Pages: 2993 - 3013
RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification
Michał Koziarski
Colin Bellinger
Michał Woźniak
OriginalPaper Open access 14 October 2021 Pages: 3059 - 3093
Deep learning and multivariate time series for cheat detection in video games
José Pedro Pinto
André Pimenta
Paulo Novais
OriginalPaper 14 October 2021 Pages: 3037 - 3057
Large-scale pinball twin support vector machines
M. Tanveer
A. Tiwari
M. A. Ganaie
OriginalPaper 04 October 2021 Pages: 3525 - 3548
Non-technical losses detection in energy consumption focusing on energy recovery and explainability
Bernat Coma-Puig
Josep Carmona
OriginalPaper Open access 29 September 2021 Pages: 487 - 517
Time-aware tensor decomposition for sparse tensors
Dawon Ahn
Jun-Gi Jang
U Kang
OriginalPaper 27 September 2021 Pages: 1409 - 1430
Tensor decision trees for continual learning from drifting data streams
Bartosz Krawczyk
OriginalPaper 24 September 2021 Pages: 3015 - 3035
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes
Alessio Benavoli
Dario Azzimonti
Dario Piga
OriginalPaper Open access 13 September 2021 Pages: 3095 - 3133
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks
Yulong Pei
Tianjin Huang
Mykola Pechenizkiy
OriginalPaper Open access 03 September 2021 Pages: 519 - 541
Ordinal regression with explainable distance metric learning based on ordered sequences
Juan Luis Suárez
Salvador García
Francisco Herrera
OriginalPaper 07 July 2021 Pages: 2729 - 2762
Embed2Detect: temporally clustered embedded words for event detection in social media
Hansi Hettiarachchi
Mariam Adedoyin-Olowe
Mohamed Medhat Gaber
OriginalPaper Open access 24 May 2021 Pages: 49 - 87
Analyzing and repairing concept drift adaptation in data stream classification
Ben Halstead
Yun Sing Koh
Guy Coulson
OriginalPaper 24 May 2021 Pages: 3489 - 3523
Misalignment problem in matrix decomposition with missing values
Sofia Fernandes
Mário Antunes
Rui L. Aguiar
OriginalPaper 28 April 2021 Pages: 3157 - 3175
Conditional t-SNE: more informative t-SNE embeddings
Bo Kang
Darío García García
Tijl De Bie
OriginalPaper Open access 06 December 2020 Pages: 2905 - 2940

Special Issue: Foundations of Data Science

Participating journal

Machine Learning

Editors

João Gama

Alípio Jorge

Salvador García

Articles

Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment

PAC-learning with approximate predictors

Reconciling privacy and utility: an unscented Kalman filter-based framework for differentially private machine learning

Attacking neural machine translations via hybrid attention learning

Scaling up stochastic gradient descent for non-convex optimisation

Machine learning in corporate credit rating assessment using the expanded audit report

A unified framework for online trip destination prediction

Robust reputation independence in ranking systems for multiple sensitive attributes

Traditional and context-specific spam detection in low resource settings

Semi-parametric Bayes regression with network-valued covariates

InfoGram and admissible machine learning

Efficient fair principal component analysis

SAMBA: safe model-based & active reinforcement learning

A network-based positive and unlabeled learning approach for fake news detection

ZipLine: an optimized algorithm for the elastic bulk synchronous parallel model

MLife: a lite framework for machine learning lifecycle initialization

RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification

Deep learning and multivariate time series for cheat detection in video games

Large-scale pinball twin support vector machines

Non-technical losses detection in energy consumption focusing on energy recovery and explainability

Time-aware tensor decomposition for sparse tensors

Tensor decision trees for continual learning from drifting data streams

A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes

ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks

Ordinal regression with explainable distance metric learning based on ordered sequences

Embed2Detect: temporally clustered embedded words for event detection in social media

Analyzing and repairing concept drift adaptation in data stream classification

Misalignment problem in matrix decomposition with missing values

Conditional t-SNE: more informative t-SNE embeddings