Special Issue of the ECML PKDD 2019 Journal Track

Guest Editors: Karsten Borgwardt, Po-Ling Loh, Evimaria Terzi, and Antti Ukkonen

Journal

Machine Learning

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

Karsten Borgwardt

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Po-Ling Loh

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Evimaria Terzi

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Antti Ukkonen

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Showing 1-22 of 22 articles

Improving latent variable descriptiveness by modelling rather than ad-hoc factors
Alex Mansbridge
Roberto Fierimonte
David Barber
OriginalPaper Open access 22 July 2019 Pages: 1601 - 1611
Introduction to the special issue for the ECML PKDD 2019 journal track
Karsten Borgwardt
Po-Ling Loh
Antti Ukkonen
EditorialNotes 18 July 2019 Pages: 1191 - 1192
Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference
Zhize Li
Tianyi Zhang
Jian Li
OriginalPaper 09 July 2019 Pages: 1701 - 1727
The teaching size: computable teachers and learners for universal languages
Jan Arne Telle
José Hernández-Orallo
Cèsar Ferri
OriginalPaper 02 July 2019 Pages: 1653 - 1675
Distribution-free uncertainty quantification for kernel methods by gradient perturbations
Balázs Cs. Csáji
Krisztián B. Kis
OriginalPaper Open access 27 June 2019 Pages: 1677 - 1699
On the analysis of adaptability in multi-source domain adaptation
Ievgen Redko
Amaury Habrard
Marc Sebban
OriginalPaper 27 June 2019 Pages: 1635 - 1652
CaDET: interpretable parametric conditional density estimation with decision trees and forests
Cyrus Cousins
Matteo Riondato
OriginalPaper 26 June 2019 Pages: 1613 - 1634
Nuclear discrepancy for single-shot batch active learning
Tom J. Viering
Jesse H. Krijthe
Marco Loog
OriginalPaper Open access 26 June 2019 Pages: 1561 - 1599
Efficient learning with robust gradient descent
Matthew J. Holland
Kazushi Ikeda
OriginalPaper 25 June 2019 Pages: 1523 - 1560
Temporal pattern attention for multivariate time series forecasting
Shun-Yao Shih
Fan-Keng Sun
Hung-yi Lee
OriginalPaper 11 June 2019 Pages: 1421 - 1441
A flexible probabilistic framework for large-margin mixture of experts
Archit Sharma
Siddhartha Saxena
Piyush Rai
OriginalPaper 05 June 2019 Pages: 1369 - 1393
LSALSA: accelerated source separation via learned sparse coding
Benjamin Cowen
Apoorva Nandini Saridena
Anna Choromanska
OriginalPaper 21 May 2019 Pages: 1307 - 1327
Compatible natural gradient policy search
Joni Pajarinen
Hong Linh Thai
Gerhard Neumann
OriginalPaper Open access 20 May 2019 Pages: 1443 - 1466
Deep collective matrix factorization for augmented multi-view learning
Ragunathan Mariappan
Vaibhav Rajan
OriginalPaper 17 May 2019 Pages: 1395 - 1420
Grouped Gaussian processes for solar power prediction
Astrid Dahl
Edwin V. Bonilla
OriginalPaper 16 May 2019 Pages: 1287 - 1306
On PAC-Bayesian bounds for random forests
Stephan S. Lorenzen
Christian Igel
Yevgeny Seldin
OriginalPaper 13 May 2019 Pages: 1503 - 1522
Efficient feature selection using shrinkage estimators
Konstantinos Sechidis
Laura Azzimonti
Gavin Brown
OriginalPaper Open access 09 May 2019 Pages: 1261 - 1286
Data scarcity, robustness and extreme multi-label classification
Rohit Babbar
Bernhard Schölkopf
OriginalPaper Open access 18 March 2019 Pages: 1329 - 1351
Joint detection of malicious domains and infected clients
Paul Prasse
René Knaebel
Tobias Scheffer
OriginalPaper 25 February 2019 Pages: 1353 - 1368
TD-regularized actor-critic methods
Simone Parisi
Voot Tangkaratt
Mohammad Emtiyaz Khan
OriginalPaper Open access 21 February 2019 Pages: 1467 - 1501
Dynamic principal projection for cost-sensitive online multi-label classification
Hong-Min Chu
Kuan-Hao Huang
Hsuan-Tien Lin
OriginalPaper 15 January 2019 Pages: 1193 - 1230
Aggregating Algorithm for prediction of packs
Dmitry Adamskiy
Anthony Bellotti
Yuri Kalnishkan
OriginalPaper Open access 07 January 2019 Pages: 1231 - 1260

Special Issue of the ECML PKDD 2019 Journal Track

Participating journal

Machine Learning

Editors

Karsten Borgwardt

Po-Ling Loh

Evimaria Terzi

Antti Ukkonen

Articles

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

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

Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference

The teaching size: computable teachers and learners for universal languages

Distribution-free uncertainty quantification for kernel methods by gradient perturbations

On the analysis of adaptability in multi-source domain adaptation

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

Nuclear discrepancy for single-shot batch active learning

Efficient learning with robust gradient descent

Temporal pattern attention for multivariate time series forecasting

A flexible probabilistic framework for large-margin mixture of experts

LSALSA: accelerated source separation via learned sparse coding

Compatible natural gradient policy search

Deep collective matrix factorization for augmented multi-view learning

Grouped Gaussian processes for solar power prediction

On PAC-Bayesian bounds for random forests

Efficient feature selection using shrinkage estimators

Data scarcity, robustness and extreme multi-label classification

Joint detection of malicious domains and infected clients

TD-regularized actor-critic methods

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

Aggregating Algorithm for prediction of packs

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Special Issue of the ECML PKDD 2019 Journal Track

Participating journal

Editors

Karsten Borgwardt

Po-Ling Loh

Evimaria Terzi

Antti Ukkonen

Articles

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