ML - 2018 - volume 107 论文列表 |
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Volume 107, Number 12, December 2018
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.Volume 107, Number 11, November 2018
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. 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. Introduction to the special issue on discovery science.Volume 107, Numbers 8-10, September 2018
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.Volume 107, Number 7, July 2018
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. 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.Volume 107, Number 6, June 2018
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. On better training the infinite restricted Boltzmann machines.Volume 107, Number 5, May 2018
Sophie Burkhardt Stefan Kramer
Consensus-based modeling using distributed feature construction with ILP. Learning with rationales for document classification.Volume 107, Number 4, April 2018
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. 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. Foreword: special issue for the journal track of the 9th Asian Conference on Machine Learning (ACML 2017).Volume 107, Number 3, March 2018
Colin Bellinger Christopher Drummond Nathalie Japkowicz
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation. 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. Analysis of classifiers' robustness to adversarial perturbations.Volume 107, Number 2, February 2018
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. LPiTrack: Eye movement pattern recognition algorithm and application to biometric identification.Volume 107, Number 1, January 2018
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.