1. 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

2. Approximate structure learning for large Bayesian networks

   • Mauro Scanagatta
   • Giorgio Corani
   • Marco Zaffalon

   OriginalPaper 07 May 2018 Pages: 1209 - 1227

   

3. Output Fisher embedding regression

   • Moussab Djerrab
   • Alexandre Garcia
   • Florence d’Alché-Buc

   OriginalPaper 17 May 2018 Pages: 1229 - 1256

   

4. Global multi-output decision trees for interaction prediction

   • Konstantinos Pliakos
   • Pierre Geurts
   • Celine Vens

   OriginalPaper 01 May 2018 Pages: 1257 - 1281

   

5. High-dimensional penalty selection via minimum description length principle

   • Kohei Miyaguchi
   • Kenji Yamanishi

   OriginalPaper 20 July 2018 Pages: 1283 - 1302

   

6. Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes

   • François Petitjean
   • Wray Buntine
   • Nayyar Zaidi

   OriginalPaper 22 May 2018 Pages: 1303 - 1331

   

7. Stagewise learning for noisy k-ary preferences

   • Yuangang Pan
   • Bo Han
   • Ivor W. Tsang

   OriginalPaper 11 May 2018 Pages: 1333 - 1361

   

8. Deep Gaussian Process autoencoders for novelty detection

   • Rémi Domingues
   • Pietro Michiardi
   • Maurizio Filippone

   OriginalPaper 14 June 2018 Pages: 1363 - 1383

   

9. 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

   

10. A new method of moments for latent variable models

    • Matteo Ruffini
    • Marta Casanellas
    • Ricard Gavaldà

    OriginalPaper 22 May 2018 Pages: 1431 - 1455

    

11. 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

    

12. Similarity encoding for learning with dirty categorical variables

    • Patricio Cerda
    • Gaël Varoquaux
    • Balázs Kégl

    OriginalPaper 12 June 2018 Pages: 1477 - 1494

    

13. ML-Plan: Automated machine learning via hierarchical planning

    • Felix Mohr
    • Marcel Wever
    • Eyke Hüllermeier

    OriginalPaper 03 July 2018 Pages: 1495 - 1515

    

14. Inverse reinforcement learning from summary data

    • Antti Kangasrääsiö
    • Samuel Kaski

    OriginalPaper 27 June 2018 Pages: 1517 - 1535

    

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

    • Vitalik Melnikov
    • Eyke Hüllermeier

    OriginalPaper 27 June 2018 Pages: 1537 - 1560

    

16. Learning from binary labels with instance-dependent noise

    • Aditya Krishna Menon
    • Brendan van Rooyen
    • Nagarajan Natarajan

    OriginalPaper 22 May 2018 Pages: 1561 - 1595

    

17. Optimizing non-decomposable measures with deep networks

    • Amartya Sanyal
    • Pawan Kumar
    • Fabrizio Sebastiani

    OriginalPaper 02 July 2018 Pages: 1597 - 1620

    

18. 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