Volume 110, Number 11, December 2021
Loss aware post-training quantization.

Yury Nahshan Brian Chmiel Chaim Baskin Evgenii Zheltonozhskii Ron Banner Alex M. Bronstein Avi Mendelson

HIVE-COTE 2.0: a new meta ensemble for time series classification.

Matthew Middlehurst James Large Michael Flynn Jason Lines Aaron Bostrom Anthony J. Bagnall

Sparse classification: a scalable discrete optimization perspective.

Dimitris Bertsimas Jean Pauphilet Bart P. G. Van Parys

Misalignment problem in matrix decomposition with missing values.

Sofia Fernandes Mário Antunes Diogo Gomes Rui L. Aguiar

Data driven conditional optimal transport.

Esteban G. Tabak Giulio Trigila Wenjun Zhao

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

Alessio Benavoli Dario Azzimonti Dario Piga

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

Michal Koziarski Colin Bellinger Michal Wozniak

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

José Pedro Pinto André Pimenta Paulo Novais

Tensor decision trees for continual learning from drifting data streams.

Bartosz Krawczyk

MLife: a lite framework for machine learning lifecycle initialization.

Cong Yang Wenfeng Wang Yunhui Zhang Zhikai Zhang Lina Shen Yipeng Li John See

Volume 110, Number 10, October 2021
Introduction to the special issue of the ECML PKDD 2021 journal track.

Annalisa Appice Sergio Escalera José A. Gámez Heike Trautmann

Robust non-parametric regression via incoherent subspace projections.

Bhaskar Mukhoty Subhajit Dutta Purushottam Kar

Conditional t-SNE: more informative t-SNE embeddings.

Bo Kang Dario García-García Jefrey Lijffijt Raúl Santos-Rodríguez Tijl De Bie

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

Xing Zhao Manos Papagelis Aijun An Bao Xin Chen Junfeng Liu Yonggang Hu

RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods.

Shay Vargaftik Isaac Keslassy Ariel Orda Yaniv Ben-Itzhak

Provable training set debugging for linear regression.

Xiaomin Zhang Xiaojin Zhu Po-Ling Loh

Ordinal regression with explainable distance metric learning based on ordered sequences.

Juan-Luis Suárez Salvador García Francisco Herrera

Volume 110, Number 9, September 2021
IntelligentPooling: practical Thompson sampling for mHealth.

Sabina Tomkins Peng Liao Predrag V. Klasnja Susan A. Murphy

Automatic discovery of interpretable planning strategies.

Julian Skirzynski Frederic Becker Falk Lieder

Partially observable environment estimation with uplift inference for reinforcement learning based recommendation.

Wenjie Shang Qingyang Li Zhiwei (Tony) Qin Yang Yu Yiping Meng Jieping Ye

Lessons on off-policy methods from a notification component of a chatbot.

Scott Rome Tianwen Chen Michael Kreisel Ding Zhou

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems.

Amarildo Likmeta Alberto Maria Metelli Giorgia Ramponi Andrea Tirinzoni Matteo Giuliani Marcello Restelli

Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation.

Srivatsan Krishnan Behzad Boroujerdian William Fu Aleksandra Faust Vijay Janapa Reddi

Grounded action transformation for sim-to-real reinforcement learning.

Josiah P. Hanna Siddharth Desai Haresh Karnan Garrett Warnell Peter Stone

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis.

Gabriel Dulac-Arnold Nir Levine Daniel J. Mankowitz Jerry Li Cosmin Paduraru Sven Gowal Todd Hester

Bandit algorithms to personalize educational chatbots.

William Cai Josh Grossman Zhiyuan (Jerry) Lin Hao Sheng Johnny Tian-Zheng Wei Joseph Jay Williams Sharad Goel

A deep reinforcement learning framework for continuous intraday market bidding.

Ioannis Boukas Damien Ernst Thibaut Théate Adrien Bolland Alexandre Huynen Martin Buchwald Christelle Wynants Bertrand Cornélusse

Inverse reinforcement learning in contextual MDPs.

Stav Belogolovsky Philip Korsunsky Shie Mannor Chen Tessler Tom Zahavy

Guest editorial: special issue on reinforcement learning for real life.

Yuxi Li Alborz Geramifard Lihong Li Csaba Szepesvári Tao Wang

Volume 110, Number 8, August 2021
Convex optimization with an interpolation-based projection and its application to deep learning.

Riad Akrour Asma Atamna Jan Peters

Information-theoretic regularization for learning global features by sequential VAE.

Kei Akuzawa Yusuke Iwasawa Yutaka Matsuo

Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting.

Kai Chen Twan van Laarhoven Elena Marchiori

Density-based weighting for imbalanced regression.

Michael Steininger Konstantin Kobs Padraig Davidson Anna Krause Andreas Hotho

Sampled Gromov Wasserstein.

Tanguy Kerdoncuff Rémi Emonet Marc Sebban

AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow.

Haiyan Jiang Haoyi Xiong Dongrui Wu Ji Liu Dejing Dou

Testing conditional independence in supervised learning algorithms.

David S. Watson Marvin N. Wright

Variational learning from implicit bandit feedback.

Quoc-Tuan Truong Hady W. Lauw

On testing transitivity in online preference learning.

Björn Haddenhorst Viktor Bengs Eyke Hüllermeier

TRU-NET: a deep learning approach to high resolution prediction of rainfall.

Rilwan A. Adewoyin Peter Dueben Peter Watson Yulan He Ritabrata Dutta

Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification.

Wanli Shi Bin Gu Xiang Li Cheng Deng Heng Huang

An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations.

Avgoustinos Vouros Stephen Langdell Mike Croucher Eleni Vasilaki

Volume 110, Number 7, July 2021
Linear support vector regression with linear constraints.

Quentin Klopfenstein Samuel Vaiter

Joint optimization of an autoencoder for clustering and embedding.

Ahcène Boubekki Michael Kampffmeyer Ulf Brefeld Robert Jenssen

Tensor Q-rank: new data dependent definition of tensor rank.

Hao Kong Canyi Lu Zhouchen Lin

A comparison of statistical relational learning and graph neural networks for aggregate graph queries.

Varun Embar Sriram Srinivasan Lise Getoor

OWL2Vec*: embedding of OWL ontologies.

Jiaoyan Chen Pan Hu Ernesto Jiménez-Ruiz Ole Magnus Holter Denvar Antonyrajah Ian Horrocks

Distance metric learning for graph structured data.

Tomoki Yoshida Ichiro Takeuchi Masayuki Karasuyama

Inductive learning of answer set programs for autonomous surgical task planning.

Daniele Meli Mohan Sridharan Paolo Fiorini

Beyond graph neural networks with lifted relational neural networks.

Gustav Sourek Filip Zelezný Ondrej Kuzelka

Learning hierarchical probabilistic logic programs.

Arnaud Nguembang Fadja Fabrizio Riguzzi Evelina Lamma

Incorporating symbolic domain knowledge into graph neural networks.

Tirtharaj Dash Ashwin Srinivasan Lovekesh Vig

Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels.

Dai Hai Nguyen Canh Hao Nguyen Hiroshi Mamitsuka

Optimal data collection design in machine learning: the case of the fixed effects generalized least squares panel data model.

Giorgio Gnecco Federico Nutarelli Daniela Selvi

Volume 110, Number 6, June 2021
MODES: model-based optimization on distributed embedded systems.

Junjie Shi Jiang Bian Jakob Richter Kuan-Hsun Chen Jörg Rahnenführer Haoyi Xiong Jian-Jia Chen

Multiple clusterings of heterogeneous information networks.

Shaowei Wei Guoxian Yu Jun Wang Carlotta Domeniconi Xiangliang Zhang

Early classification of time series.

Youssef Achenchabe Alexis Bondu Antoine Cornuéjols Asma Dachraoui

Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders.

Geoffrey A. Converse Mariana Curi Suely Oliveira Jonathan Templin

Automated adaptation strategies for stream learning.

Rashid Bakirov Damien Fay Bogdan Gabrys

A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions.

Javier Fernández Luke Bornn Daniel Cervone

Graph-based semi-supervised learning via improving the quality of the graph dynamically.

Jiye Liang Junbiao Cui Jie Wang Wei Wei

Efficient Weingarten map and curvature estimation on manifolds.

Yueqi Cao Didong Li Huafei Sun Amir H. Assadi Shiqiang Zhang

Importance sampling in reinforcement learning with an estimated behavior policy.

Josiah P. Hanna Scott Niekum Peter Stone

Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives.

Alihan Hüyük Cem Tekin

Toward optimal probabilistic active learning using a Bayesian approach.

Daniel Kottke Marek Herde Christoph Sandrock Denis Huseljic Georg Krempl Bernhard Sick

Reachable sets of classifiers and regression models: (non-)robustness analysis and robust training.

Anna-Kathrin Kopetzki Stephan Günnemann

Analysis of regularized least-squares in reproducing kernel Kreĭn spaces.

Fanghui Liu Lei Shi Xiaolin Huang Jie Yang Johan A. K. Suykens

Pseudo-marginal Bayesian inference for Gaussian process latent variable models.

Charles W. L. Gadd Sara Wade A. A. Shah

Volume 110, Number 5, May 2021
Adaptive covariate acquisition for minimizing total cost of classification.

Daniel Andrade Yuzuru Okajima

Topic extraction from extremely short texts with variational manifold regularization.

Ximing Li Yang Wang Jihong Ouyang Meng Wang

autoBOT: evolving neuro-symbolic representations for explainable low resource text classification.

Blaz Skrlj Matej Martinc Nada Lavrac Senja Pollak

Large scale multi-label learning using Gaussian processes.

Aristeidis Panos Petros Dellaportas Michalis K. Titsias

Convex programming based spectral clustering.

Tomohiko Mizutani

Robust supervised topic models under label noise.

Wei Wang Bing Guo Yan Shen Han Yang Yaosen Chen Xinhua Suo

QuicK-means: accelerating inference for K-means by learning fast transforms.

Luc Giffon Valentin Emiya Hachem Kadri Liva Ralaivola

Bayesian optimization with approximate set kernels.

Jungtaek Kim Michael McCourt Tackgeun You Saehoon Kim Seungjin Choi

Volume 110, Number 3, March 2021
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach.

Jinhong Jung Lee Sael

Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling.

Prashanth L. A. Nathaniel Korda Rémi Munos

Coupling matrix manifolds assisted optimization for optimal transport problems.

Dai Shi Junbin Gao Xia Hong S. T. Boris Choy Zhiyong Wang

Reshaped tensor nuclear norms for higher order tensor completion.

Kishan Wimalawarne Hiroshi Mamitsuka

Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods.

Eyke Hüllermeier Willem Waegeman

F*: an interpretable transformation of the F-measure.

David J. Hand Peter Christen Nishadi Kirielle

Volume 110, Number 2, February 2021
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach.

Jinhong Jung Lee Sael

Global optimization based on active preference learning with radial basis functions.

Alberto Bemporad Dario Piga

Regularisation of neural networks by enforcing Lipschitz continuity.

Henry Gouk Eibe Frank Bernhard Pfahringer Michael J. Cree

Kernel machines for current status data.

Yael Travis-Lumer Yair Goldberg

Conditional variance penalties and domain shift robustness.

Christina Heinze-Deml Nicolai Meinshausen

LoRAS: an oversampling approach for imbalanced datasets.

Saptarshi Bej Narek Davtyan Markus Wolfien Mariam Nassar Olaf Wolkenhauer

The voice of optimization.

Dimitris Bertsimas Bartolomeo Stellato

Volume 110, Number 1, January 2021
Imputation of clinical covariates in time series.

Dimitris Bertsimas Agni Orfanoudaki Colin Pawlowski

Statistical hierarchical clustering algorithm for outlier detection in evolving data streams.

Dalibor Krleza Boris Vrdoljak Mario Brcic

Interpretable clustering: an optimization approach.

Dimitris Bertsimas Agni Orfanoudaki Holly M. Wiberg

Node classification over bipartite graphs through projection.

Marija Stankova Stiene Praet David Martens Foster J. Provost

CPAS: the UK's national machine learning-based hospital capacity planning system for COVID-19.

Zhaozhi Qian Ahmed M. Alaa Mihaela van der Schaar

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19.

Mihaela van der Schaar Ahmed M. Alaa R. Andres Floto Alexander Gimson Stefan Scholtes Angela M. Wood Eoin F. McKinney Daniel Jarrett Pietro Lió Ari Ercole