Volume 107, Number 12, December 2018
An adaptive heuristic for feature selection based on complementarity.

Sumanta Singha Prakash P. Shenoy

Clustering with missing features: a penalized dissimilarity measure based approach.

Shounak Datta Supritam Bhattacharjee Swagatam Das

Stochastic variational hierarchical mixture of sparse Gaussian processes for regression.

Thi Nhat Anh Nguyen Abdesselam Bouzerdoum Son Lam Phung

Wasserstein discriminant analysis.

Rémi Flamary Marco Cuturi Nicolas Courty Alain Rakotomamonjy

Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation.

Ioannis Tsamardinos Elissavet Greasidou Giorgos Borboudakis

Volume 107, Number 11, November 2018
Analyzing business process anomalies using autoencoders.

Timo Nolle Stefan Luettgen Alexander Seeliger Max Mühlhäuser

Probabilistic frequent subtrees for efficient graph classification and retrieval.

Pascal Welke Tamás Horváth Stefan Wrobel

Targeted and contextual redescription set exploration.

Matej Mihelcic Tomislav Smuc

Discovering a taste for the unusual: exceptional models for preference mining.

Cláudio Rebelo de Sá Wouter Duivesteijn Paulo J. Azevedo Alípio Mário Jorge Carlos Soares Arno J. Knobbe

On analyzing user preference dynamics with temporal social networks.

Fabiola S. F. Pereira João Gama Sandra de Amo Gina M. B. Oliveira

Reservoir of diverse adaptive learners and stacking fast hoeffding drift detection methods for evolving data streams.

Ali Pesaranghader Herna L. Viktor Eric Paquet

Ensembles for multi-target regression with random output selections.

Martin Breskvar Dragi Kocev Saso Dzeroski

A comparison of hierarchical multi-output recognition approaches for anuran classification.

Juan Gabriel Colonna João Gama Eduardo Freire Nakamura

Introduction to the special issue on discovery science.

Michelangelo Ceci Toon Calders

Volume 107, Numbers 8-10, September 2018
Local contrast as an effective means to robust clustering against varying densities.

Bo Chen Kai Ming Ting Takashi Washio Ye Zhu

Optimizing non-decomposable measures with deep networks.

Amartya Sanyal Pawan Kumar Purushottam Kar Sanjay Chawla Fabrizio Sebastiani

Learning from binary labels with instance-dependent noise.

Aditya Krishna Menon Brendan van Rooyen Nagarajan Natarajan

On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis.

Vitalik Melnikov Eyke Hüllermeier

Inverse reinforcement learning from summary data.

Antti Kangasrääsiö Samuel Kaski

ML-Plan: Automated machine learning via hierarchical planning.

Felix Mohr Marcel Wever Eyke Hüllermeier

Similarity encoding for learning with dirty categorical variables.

Patricio Cerda Gaël Varoquaux Balázs Kégl

A distributed Frank-Wolfe framework for learning low-rank matrices with the trace norm.

Wenjie Zheng Aurélien Bellet Patrick Gallinari

A new method of moments for latent variable models.

Matteo Ruffini Marta Casanellas Ricard Gavaldà

An online prediction algorithm for reinforcement learning with linear function approximation using cross entropy method.

Ajin George Joseph Shalabh Bhatnagar

Deep Gaussian Process autoencoders for novelty detection.

Remi Domingues Pietro Michiardi Jihane Zouaoui Maurizio Filippone

Stagewise learning for noisy k-ary preferences.

Yuangang Pan Bo Han Ivor W. Tsang

Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes.

François Petitjean Wray L. Buntine Geoffrey I. Webb Nayyar Abbas Zaidi

High-dimensional penalty selection via minimum description length principle.

Kohei Miyaguchi Kenji Yamanishi

Global multi-output decision trees for interaction prediction.

Konstantinos Pliakos Pierre Geurts Celine Vens

Output Fisher embedding regression.

Moussab Djerrab Alexandre Garcia Maxime Sangnier Florence d'Alché-Buc

Approximate structure learning for large Bayesian networks.

Mauro Scanagatta Giorgio Corani Cassio Polpo de Campos Marco Zaffalon

Guest editors introduction to the special issue for the ECML PKDD 2018 journal track.

Jesse Davis Björn Bringmann Élisa Fromont Derek Greene

Volume 107, Number 7, July 2018
Identification of biological transition systems using meta-interpreted logic programs.

Michael Bain Ashwin Srinivasan

Best-effort inductive logic programming via fine-grained cost-based hypothesis generation - The inspire system at the inductive logic programming competition.

Peter Schüller Mishal Benz

Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP.

Stephen H. Muggleton Ute Schmid Christina Zeller Alireza Tamaddoni-Nezhad Tarek R. Besold

Meta-Interpretive Learning from noisy images.

Stephen Muggleton Wang-Zhou Dai Claude Sammut Alireza Tamaddoni-Nezhad Jing Wen Zhi-Hua Zhou

Preface to the special issue on inductive logic programming.

James Cussens Alessandra Russo

Volume 107, Number 6, June 2018
Improved maximum inner product search with better theoretical guarantee using randomized partition trees.

Omid Keivani Kaushik Sinha Parikshit Ram

A scalable preference model for autonomous decision-making.

Markus Peters Maytal Saar-Tsechansky Wolfgang Ketter Sinead A. Williamson Perry Groot Tom Heskes

Wallenius Bayes.

Enric Junqué de Fortuny David Martens Foster J. Provost

An incremental off-policy search in a model-free Markov decision process using a single sample path.

Ajin George Joseph Shalabh Bhatnagar

On better training the infinite restricted Boltzmann machines.

Xuan Peng Xunzhang Gao Xiang Li

Volume 107, Number 5, May 2018
Dyad ranking using Plackett-Luce models based on joint feature representations.

Dirk Schäfer Eyke Hüllermeier

Simpler PAC-Bayesian bounds for hostile data.

Pierre Alquier Benjamin Guedj

Online multi-label dependency topic models for text classification.

Sophie Burkhardt Stefan Kramer

Consensus-based modeling using distributed feature construction with ILP.

Haimonti Dutta Ashwin Srinivasan

Learning with rationales for document classification.

Manali Sharma Mustafa Bilgic

Volume 107, Number 4, April 2018
Correction to: Semi-supervised AUC optimization based on positive-unlabeled learning.

Tomoya Sakai Gang Niu Masashi Sugiyama

Semi-supervised AUC optimization based on positive-unlabeled learning.

Tomoya Sakai Gang Niu Masashi Sugiyama

Crowdsourcing with unsure option.

Yao-Xiang Ding Zhi-Hua Zhou

Distributed multi-task classification: a decentralized online learning approach.

Chi Zhang Peilin Zhao Shuji Hao Yeng Chai Soh Bu-Sung Lee Chunyan Miao Steven C. H. Hoi

Learning safe multi-label prediction for weakly labeled data.

Tong Wei Lan-Zhe Guo Yu-Feng Li Wei Gao

Robust Plackett-Luce model for k-ary crowdsourced preferences.

Bo Han Yuangang Pan Ivor W. Tsang

Efficient preconditioning for noisy separable nonnegative matrix factorization problems by successive projection based low-rank approximations.

Tomohiko Mizutani Mirai Tanaka

Foreword: special issue for the journal track of the 9th Asian Conference on Machine Learning (ACML 2017).

Wee Sun Lee Robert J. Durrant

Volume 107, Number 3, March 2018
Manifold-based synthetic oversampling with manifold conformance estimation.

Colin Bellinger Christopher Drummond Nathalie Japkowicz

1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation.

Vincent Cottet Pierre Alquier

Identifying and tracking topic-level influencers in the microblog streams.

Sen Su Yakun Wang Zhongbao Zhang Cheng Chang Muhammad Azam Zia

The randomized information coefficient: assessing dependencies in noisy data.

Simone Romano Xuan Vinh Nguyen Karin Verspoor James Bailey

Analysis of classifiers' robustness to adversarial perturbations.

Alhussein Fawzi Omar Fawzi Pascal Frossard

Volume 107, Number 2, February 2018
Emotion in reinforcement learning agents and robots: a survey.

Thomas M. Moerland Joost Broekens Catholijn M. Jonker

When is the Naive Bayes approximation not so naive?

Christopher R. Stephens Hugo Flores Huerta Ana Ruiz Linares

Simple strategies for semi-supervised feature selection.

Konstantinos Sechidis Gavin Brown

Learning data discretization via convex optimization.

Vojtech Franc Ondrej Fikar Karel Bartos Michal Sofka

LPiTrack: Eye movement pattern recognition algorithm and application to biometric identification.

Subhadeep Mukhopadhyay Shinjini Nandi

Volume 107, Number 1, January 2018
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery.

Iván Olier Noureddin Sadawi G. Richard J. Bickerton Joaquin Vanschoren Crina Grosan Larisa N. Soldatova Ross D. King

Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction.

Brandon M. Malone Kustaa Kangas Matti Järvisalo Mikko Koivisto Petri Myllymäki

Data complexity meta-features for regression problems.

Ana Carolina Lorena Aron I. Maciel Péricles B. C. de Miranda Ivan G. Costa Ricardo B. C. Prudêncio

Discovering predictive ensembles for transfer learning and meta-learning.

Pavel Kordík Ján Cerný Tomás Frýda

The online performance estimation framework: heterogeneous ensemble learning for data streams.

Jan N. van Rijn Geoffrey Holmes Bernhard Pfahringer Joaquin Vanschoren

Instance spaces for machine learning classification.

Mario A. Muñoz Laura Villanova Davaatseren Baatar Kate Smith-Miles

Speeding up algorithm selection using average ranking and active testing by introducing runtime.

Salisu Mamman Abdulrahman Pavel Brazdil Jan N. van Rijn Joaquin Vanschoren

Scalable Gaussian process-based transfer surrogates for hyperparameter optimization.

Martin Wistuba Nicolas Schilling Lars Schmidt-Thieme

Efficient benchmarking of algorithm configurators via model-based surrogates.

Katharina Eggensperger Marius Lindauer Holger H. Hoos Frank Hutter Kevin Leyton-Brown

Metalearning and Algorithm Selection: progress, state of the art and introduction to the 2018 Special Issue.

Pavel Brazdil Christophe G. Giraud-Carrier