Special Issue of the ECML PKDD 2018 Journal Track

Articles (18 in this collection)

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

   Authors (first, second and last of 4)

   • Jesse Davis
   • Bjørn Bringmann
   • Derek Greene

   • Content type: EditorialNotes
   • Published: 20 July 2018

   • Pages: 1207 - 1208

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

   Authors

   • Kohei Miyaguchi
   • Kenji Yamanishi

   • Content type: OriginalPaper
   • Published: 20 July 2018

   • Pages: 1283 - 1302

   

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

   Authors

   • Ajin George Joseph
   • Shalabh Bhatnagar

   • Content type: OriginalPaper
   • Published: 03 July 2018

   • Pages: 1385 - 1429

   

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

   Authors

   • Felix Mohr
   • Marcel Wever
   • Eyke Hüllermeier

   • Content type: OriginalPaper
   • Published: 03 July 2018

   • Pages: 1495 - 1515

   

5. Optimizing non-decomposable measures with deep networks

   Authors (first, second and last of 5)

   • Amartya Sanyal
   • Pawan Kumar
   • Fabrizio Sebastiani

   • Content type: OriginalPaper
   • Published: 02 July 2018

   • Pages: 1597 - 1620

   

6. Inverse reinforcement learning from summary data

   Authors

   • Antti Kangasrääsiö
   • Samuel Kaski

   • Content type: OriginalPaper
   • Published: 27 June 2018

   • Pages: 1517 - 1535

   

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

   Authors

   • Vitalik Melnikov
   • Eyke Hüllermeier

   • Content type: OriginalPaper
   • Published: 27 June 2018

   • Pages: 1537 - 1560

   

8. Deep Gaussian Process autoencoders for novelty detection

   Authors (first, second and last of 4)

   • Rémi Domingues
   • Pietro Michiardi
   • Maurizio Filippone

   • Content type: OriginalPaper
   • Published: 14 June 2018

   • Pages: 1363 - 1383

   

9. Similarity encoding for learning with dirty categorical variables

   Authors

   • Patricio Cerda
   • Gaël Varoquaux
   • Balázs Kégl

   • Content type: OriginalPaper
   • Published: 12 June 2018

   • Pages: 1477 - 1494

   

10. Learning from binary labels with instance-dependent noise

    Authors

    • Aditya Krishna Menon
    • Brendan van Rooyen
    • Nagarajan Natarajan

    • Content type: OriginalPaper
    • Published: 22 May 2018

    • Pages: 1561 - 1595

    

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

    Authors (first, second and last of 4)

    • François Petitjean
    • Wray Buntine
    • Nayyar Zaidi

    • Content type: OriginalPaper
    • Published: 22 May 2018

    • Pages: 1303 - 1331

    

12. A new method of moments for latent variable models

    Authors

    • Matteo Ruffini
    • Marta Casanellas
    • Ricard Gavaldà

    • Content type: OriginalPaper
    • Published: 22 May 2018

    • Pages: 1431 - 1455

    

13. Output Fisher embedding regression

    Authors (first, second and last of 4)

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

    • Content type: OriginalPaper
    • Published: 17 May 2018

    • Pages: 1229 - 1256

    

14. Stagewise learning for noisy k-ary preferences

    Authors

    • Yuangang Pan
    • Bo Han
    • Ivor W. Tsang

    • Content type: OriginalPaper
    • Published: 11 May 2018

    • Pages: 1333 - 1361

    

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

    Authors

    • Wenjie Zheng
    • Aurélien Bellet
    • Patrick Gallinari

    • Content type: OriginalPaper
    • Published: 10 May 2018

    • Pages: 1457 - 1475

    

16. Approximate structure learning for large Bayesian networks

    Authors (first, second and last of 4)

    • Mauro Scanagatta
    • Giorgio Corani
    • Marco Zaffalon

    • Content type: OriginalPaper
    • Published: 07 May 2018

    • Pages: 1209 - 1227

    

17. Global multi-output decision trees for interaction prediction

    Authors

    • Konstantinos Pliakos
    • Pierre Geurts
    • Celine Vens

    • Content type: OriginalPaper
    • Published: 01 May 2018

    • Pages: 1257 - 1281

    

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

    Authors (first, second and last of 4)

    • Bo Chen
    • Kai Ming Ting
    • Ye Zhu

    • Content type: OriginalPaper
    • Published: 23 January 2018

    • Pages: 1621 - 1645