Volume 108, Number 12, December 2019
Covariance-based dissimilarity measures applied to clustering wide-sense stationary ergodic processes.

Qidi Peng Nan Rao Ran Zhao

The kernel Kalman rule - Efficient nonparametric inference by recursive least-squares and subspace projections.

Gregor H. W. Gebhardt Andras Gabor Kupcsik Gerhard Neumann

Speculate-correct error bounds for k-nearest neighbor classifiers.

Eric Bax Lingjie Weng Xu Tian

A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data.

Kshitij Khare Sang-Yun Oh Syed Rahman Bala Rajaratnam

2D compressed learning: support matrix machine with bilinear random projections.

Di Ma Songcan Chen

Volume 108, Number 11, November 2019
A distributed feature selection scheme with partial information sharing.

Aida Brankovic Luigi Piroddi

Risk bound of transfer learning using parametric feature mapping and its application to sparse coding.

Wataru Kumagai Takafumi Kanamori

Boosting as a kernel-based method.

Aleksandr Y. Aravkin Giulio Bottegal Gianluigi Pillonetto

Asymptotically optimal algorithms for budgeted multiple play bandits.

Alexander Luedtke Emilie Kaufmann Antoine Chambaz

Engineering fast multilevel support vector machines.

Ehsan Sadrfaridpour Talayeh Razzaghi Ilya Safro

Volume 108, Number 10, October 2019
Correction to: Adaptive random forests for evolving data stream classification.

Heitor Murilo Gomes Albert Bifet Jesse Read Jean Paul Barddal Fabrício Enembreck Bernhard Pfahringer Geoff Holmes Talel Abdessalem

Dynamic attention-integrated neural network for session-based news recommendation.

Lemei Zhang Peng Liu Jon Atle Gulla

Collaborative topic regression for predicting topic-based social influence.

Asso Hamzehei Raymond K. Wong Danai Koutra Fang Chen

Distributed Bayesian matrix factorization with limited communication.

Xiangju Qin Paul Blomstedt Eemeli Leppäaho Pekka Parviainen Samuel Kaski

A Riemannian gossip approach to subspace learning on Grassmann manifold.

Bamdev Mishra Hiroyuki Kasai Pratik Jawanpuria Atul Saroop

Attentional multilabel learning over graphs: a message passing approach.

Kien Do Truyen Tran Thin Nguyen Svetha Venkatesh

RankMerging: a supervised learning-to-rank framework to predict links in large social networks.

Lionel Tabourier Daniel Faria Bernardes Anne-Sophie Libert Renaud Lambiotte

Volume 108, Numbers 8-9, September 2019
Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference.

Zhize Li Tianyi Zhang Shuyu Cheng Jun Zhu Jian Li

Distribution-free uncertainty quantification for kernel methods by gradient perturbations.

Balázs Csanád Csáji Krisztián Balázs Kis

The teaching size: computable teachers and learners for universal languages.

Jan Arne Telle José Hernández-Orallo Cèsar Ferri

On the analysis of adaptability in multi-source domain adaptation.

Ievgen Redko Amaury Habrard Marc Sebban

CaDET: interpretable parametric conditional density estimation with decision trees and forests.

Cyrus Cousins Matteo Riondato

Improving latent variable descriptiveness by modelling rather than ad-hoc factors.

Alex Mansbridge Roberto Fierimonte Ilya Feige David Barber

Nuclear discrepancy for single-shot batch active learning.

Tom J. Viering Jesse H. Krijthe Marco Loog

Efficient learning with robust gradient descent.

Matthew J. Holland Kazushi Ikeda

On PAC-Bayesian bounds for random forests.

Stephan Sloth Lorenzen Christian Igel Yevgeny Seldin

TD-regularized actor-critic methods.

Simone Parisi Voot Tangkaratt Jan Peters Mohammad Emtiyaz Khan

Compatible natural gradient policy search.

Joni Pajarinen Hong Linh Thai Riad Akrour Jan Peters Gerhard Neumann

Temporal pattern attention for multivariate time series forecasting.

Shun-Yao Shih Fan-Keng Sun Hung-Yi Lee

Deep collective matrix factorization for augmented multi-view learning.

Ragunathan Mariappan Vaibhav Rajan

A flexible probabilistic framework for large-margin mixture of experts.

Archit Sharma Siddhartha Saxena Piyush Rai

Joint detection of malicious domains and infected clients.

Paul Prasse René Knaebel Lukás Machlica Tomás Pevný Tobias Scheffer

Data scarcity, robustness and extreme multi-label classification.

Rohit Babbar Bernhard Schölkopf

LSALSA: accelerated source separation via learned sparse coding.

Benjamin Cowen Apoorva Nandini Saridena Anna Choromanska

Grouped Gaussian processes for solar power prediction.

Astrid Dahl Edwin V. Bonilla

Efficient feature selection using shrinkage estimators.

Konstantinos Sechidis Laura Azzimonti Adam Craig Pocock Giorgio Corani James Weatherall Gavin Brown

Aggregating Algorithm for prediction of packs.

Dmitry Adamskiy Anthony Bellotti Raisa Dzhamtyrova Yuri Kalnishkan

Dynamic principal projection for cost-sensitive online multi-label classification.

Hong-Min Chu Kuan-Hao Huang Hsuan-Tien Lin

Introduction to the special issue for the ECML PKDD 2019 journal track.

Karsten M. Borgwardt Po-Ling Loh Evimaria Terzi Antti Ukkonen

Volume 108, Number 7, July 2019
Online probabilistic theory revision from examples with ProPPR.

Victor Guimarães Aline Paes Gerson Zaverucha

Probabilistic and exact frequent subtree mining in graphs beyond forests.

Pascal Welke Tamás Horváth Stefan Wrobel

Lifted discriminative learning of probabilistic logic programs.

Arnaud Nguembang Fadja Fabrizio Riguzzi

Semi-supervised online structure learning for composite event recognition.

Evangelos Michelioudakis Alexander Artikis Georgios Paliouras

Learning efficient logic programs.

Andrew Cropper Stephen H. Muggleton

Guest editors' note.

Preface to special issue on Inductive Logic Programming, ILP 2017 and 2018.

Nicolas Lachiche Christel Vrain Fabrizio Riguzzi Elena Bellodi Riccardo Zese

Volume 108, Number 6, June 2019
A simple homotopy proximal mapping algorithm for compressive sensing.

Tianbao Yang Lijun Zhang Rong Jin Shenghuo Zhu Zhi-Hua Zhou

Efficient and robust TWSVM classification via a minimum L1-norm distance metric criterion.

He Yan Qiaolin Ye Dong-Jun Yu

Accelerated gradient boosting.

Gérard Biau Benoît Cadre Laurent Rouvìère

Constructing effective personalized policies using counterfactual inference from biased data sets with many features.

Onur Atan William R. Zame Qiaojun Feng Mihaela van der Schaar

Arbitrage of forecasting experts.

Vítor Cerqueira Luís Torgo Fábio Pinto Carlos Soares

Algorithms for learning parsimonious context trees.

Ralf Eggeling Ivo Grosse Mikko Koivisto

Volume 108, Number 3, March 2019
Efficient Venn predictors using random forests.

Ulf Johansson Tuve Löfström Henrik Linusson Henrik Boström

Automatic face recognition with well-calibrated confidence measures.

Charalambos Eliades Ladislav Lenc Pavel Král Harris Papadopoulos

Combination of inductive mondrian conformal predictors.

Paolo Toccaceli Alexander Gammerman

Majority vote ensembles of conformal predictors.

Giovanni Cherubin

Nonparametric predictive distributions based on conformal prediction.

Vladimir Vovk Jieli Shen Valery Manokhin Min-ge Xie

Online aggregation of unbounded losses using shifting experts with confidence.

Vladimir V'yugin Vladimir G. Trunov

Rethinking statistical learning theory: learning using statistical invariants.

Vladimir Vapnik Rauf Izmailov

Conformal and probabilistic prediction with applications: editorial.

Alexander Gammerman Vladimir Vovk Henrik Boström Lars Carlsson

Volume 108, Number 2, February 2019
Correction to: Modeling outcomes of soccer matches.

Alkeos Tsokos Santhosh Narayanan Ioannis Kosmidis Gianluca Baio Mihai Cucuringu Gavin Whitaker Franz J. Király

Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms.

Kai Ming Ting Ye Zhu Mark J. Carman Yue Zhu Takashi Washio Zhi-Hua Zhou

Extreme value correction: a method for correcting optimistic estimations in rule learning.

Martin Mozina Janez Demsar Ivan Bratko Jure Zabkar

Fast generalization rates for distance metric learning.

Han-Jia Ye De-Chuan Zhan Yuan Jiang

A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data.

Marc Boullé Clément Charnay Nicolas Lachiche

Learning rates for kernel-based expectile regression.

Muhammad Farooq Ingo Steinwart

A greedy feature selection algorithm for Big Data of high dimensionality.

Ioannis Tsamardinos Giorgos Borboudakis Pavlos Katsogridakis Polyvios Pratikakis Vassilis Christophides

Volume 108, Number 1, January 2019
Probabilistic movement models and zones of control.

Ulf Brefeld Jan Lasek Sebastian Mair

Incorporating domain knowledge in machine learning for soccer outcome prediction.

Daniel Berrar Philippe Lopes Werner Dubitzky

Modeling outcomes of soccer matches.

Alkeos Tsokos Santhosh Narayanan Ioannis Kosmidis Gianluca Baio Mihai Cucuringu Gavin Whitaker Franz J. Király

Dolores: a model that predicts football match outcomes from all over the world.

Anthony C. Constantinou

Learning to predict soccer results from relational data with gradient boosted trees.

Ondrej Hubácek Gustav Sourek Filip Zelezný

The Open International Soccer Database for machine learning.

Werner Dubitzky Philippe Lopes Jesse Davis Daniel Berrar

Guest editorial: special issue on machine learning for soccer.

Daniel Berrar Philippe Lopes Jesse Davis Werner Dubitzky