Special Issue of the ECML PKDD 2018 Journal Track

Guest Editors: Jesse Davis, Elisa Fromont, Derek Greene, and Bjorn Bringmann

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

Jesse Davis

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Elisa Fromont

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Derek Greene

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Bjorn Bringmann

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Showing 1-18 of 18 articles

Guest editors introduction to the special issue for the ECML PKDD 2018 journal track
Jesse Davis
Bjørn Bringmann
Derek Greene
EditorialNotes 20 July 2018 Pages: 1207 - 1208
High-dimensional penalty selection via minimum description length principle
Kohei Miyaguchi
Kenji Yamanishi
OriginalPaper 20 July 2018 Pages: 1283 - 1302
An online prediction algorithm for reinforcement learning with linear function approximation using cross entropy method
Ajin George Joseph
Shalabh Bhatnagar
OriginalPaper 03 July 2018 Pages: 1385 - 1429
ML-Plan: Automated machine learning via hierarchical planning
Felix Mohr
Marcel Wever
Eyke Hüllermeier
OriginalPaper 03 July 2018 Pages: 1495 - 1515
Optimizing non-decomposable measures with deep networks
Amartya Sanyal
Pawan Kumar
Fabrizio Sebastiani
OriginalPaper 02 July 2018 Pages: 1597 - 1620
Inverse reinforcement learning from summary data
Antti Kangasrääsiö
Samuel Kaski
OriginalPaper 27 June 2018 Pages: 1517 - 1535
On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis
Vitalik Melnikov
Eyke Hüllermeier
OriginalPaper 27 June 2018 Pages: 1537 - 1560
Deep Gaussian Process autoencoders for novelty detection
Rémi Domingues
Pietro Michiardi
Maurizio Filippone
OriginalPaper 14 June 2018 Pages: 1363 - 1383
Similarity encoding for learning with dirty categorical variables
Patricio Cerda
Gaël Varoquaux
Balázs Kégl
OriginalPaper 12 June 2018 Pages: 1477 - 1494
Learning from binary labels with instance-dependent noise
Aditya Krishna Menon
Brendan van Rooyen
Nagarajan Natarajan
OriginalPaper 22 May 2018 Pages: 1561 - 1595
Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes
François Petitjean
Wray Buntine
Nayyar Zaidi
OriginalPaper 22 May 2018 Pages: 1303 - 1331
A new method of moments for latent variable models
Matteo Ruffini
Marta Casanellas
Ricard Gavaldà
OriginalPaper 22 May 2018 Pages: 1431 - 1455
Output Fisher embedding regression
Moussab Djerrab
Alexandre Garcia
Florence d’Alché-Buc
OriginalPaper 17 May 2018 Pages: 1229 - 1256
Stagewise learning for noisy k-ary preferences
Yuangang Pan
Bo Han
Ivor W. Tsang
OriginalPaper 11 May 2018 Pages: 1333 - 1361
A distributed Frank–Wolfe framework for learning low-rank matrices with the trace norm
Wenjie Zheng
Aurélien Bellet
Patrick Gallinari
OriginalPaper 10 May 2018 Pages: 1457 - 1475
Approximate structure learning for large Bayesian networks
Mauro Scanagatta
Giorgio Corani
Marco Zaffalon
OriginalPaper 07 May 2018 Pages: 1209 - 1227
Global multi-output decision trees for interaction prediction
Konstantinos Pliakos
Pierre Geurts
Celine Vens
OriginalPaper 01 May 2018 Pages: 1257 - 1281
Local contrast as an effective means to robust clustering against varying densities
Bo Chen
Kai Ming Ting
Ye Zhu
OriginalPaper 23 January 2018 Pages: 1621 - 1645

Special Issue of the ECML PKDD 2018 Journal Track

Participating journal

Machine Learning

Editors

Jesse Davis

Elisa Fromont

Derek Greene

Bjorn Bringmann

Articles

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

High-dimensional penalty selection via minimum description length principle

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

ML-Plan: Automated machine learning via hierarchical planning

Optimizing non-decomposable measures with deep networks

Inverse reinforcement learning from summary data

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

Deep Gaussian Process autoencoders for novelty detection

Similarity encoding for learning with dirty categorical variables

Learning from binary labels with instance-dependent noise

Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes

A new method of moments for latent variable models

Output Fisher embedding regression

Stagewise learning for noisy k-ary preferences

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

Approximate structure learning for large Bayesian networks

Global multi-output decision trees for interaction prediction

Local contrast as an effective means to robust clustering against varying densities

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Special Issue of the ECML PKDD 2018 Journal Track

Participating journal

Editors

Jesse Davis

Elisa Fromont

Derek Greene

Bjorn Bringmann

Articles

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