Learning with Imbalanced Domains: Preface

Luís Torgo, Bartosz Krawczyk, Paula Branco, Nuno Moniz; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:1-6

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Influence of minority class instance types on SMOTE imbalanced data oversampling

Przemysław Skryjomski, Bartosz Krawczyk; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:7-21

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A Network Perspective on Stratification of Multi-Label Data

Piotr Szymański, Tomasz Kajdanowicz; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:22-35

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SMOGN: a Pre-processing Approach for Imbalanced Regression

Paula Branco, Luís Torgo, Rita P. Ribeiro; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:36-50

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Stacked-MLkNN: A stacking based improvement to Multi-Label k-Nearest Neighbours

Arjun Pakrashi, Brian Mac Namee; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:51-63

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Sampling a Longer Life: Binary versus One-class classification Revisited

Colin Bellinger, Shiven Sharma, Osmar R. Zaı̈ane, Nathalie Japkowicz; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:64-78

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Improving Resampling-based Ensemble in Churn Prediction

Bing Zhu, Seppe Broucke, Bart Baesens, Sebastián Maldonado; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:79-91

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Predicting Defective Engines using Convolutional Neural Networks on Temporal Vibration Signals

Nikou Günnemann, Jürgen Pfeffer; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:92-102

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Effect of Data Imbalance on Unsupervised Domain Adaptation of Part-of-Speech Tagging and Pivot Selection Strategies

Xia Cui, Frans Coenen, Danushka Bollegala; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:103-115

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Tunable Plug-In Rules with Reduced Posterior Certainty Loss in Imbalanced Datasets

Emmanouil Krasanakis, Eleftherios Spyromitros-Xioufis, Symeon Papadopoulos, Yiannis Kompatsiaris; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:116-128

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Evaluation of Ensemble Methods in Imbalanced Regression Tasks

Nuno Moniz, Paula Branco, Luís Torgo; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:129-140

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Controlling Imbalanced Error in Deep Learning with the Log Bilinear Loss

Yehezkel S. Resheff, Amit Mandelbom, Daphna Weinshall; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:141-151

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Unsupervised Classification of Speaker Profiles as a Point Anomaly Detection Task

Cedric Fayet, Arnaud Delhay, Damien Lolive, Pierre-François Marteau; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:152-163

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Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers

Paweł Ksieniewicz, Michał Woźniak; Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, PMLR 74:164-175

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