Guest editors’ introduction: special issue of selected papers from ECML PKDD 2011

The 2011 edition of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) was held in Athens, Greece, during September 5–9, 2011. Ten years after the first edition of this joint conference, ECML PKDD 2011 continued to provide a common forum for the closely related fields of machine learning and data mining. Apart from six plenary invited talks, four invited talks for the industrial session, a demo session, six tutorials and eleven co-located workshops, the main technical sessions comprised the presentation of 121 peer-reviewed papers selected by the program committee from 599 full-paper submissions. ECML PKDD 2011 was a highly selective conference and the proceedings were published in three volumes of the Springer’s Lecture Notes in Artificial Intelligence series (Gunopulos et al. 2011a, 2011b, 2011c). Authors of the best ten machine learning papers presented at the conference were invited to submit a significantly extended version of their paper to this special issue. The selection was made by the Program Chairs on the basis of their exceptional scientific quality and high impact on the field, as indicated by conference reviewers. In this special issue you will find seven papers which have been accepted after two or three rounds of peer-reviewing according to the journal criteria. The diversity of topics addressed in these papers reflects the significant progress being made by the machine learning community in the theoretical understanding of the principles underlying knowledge discov-

[1]  Thomas Seidl,et al.  Finding density-based subspace clusters in graphs with feature vectors , 2012, Data Mining and Knowledge Discovery.

[2]  Samuel Kaski,et al.  Focused multi-task learning in a Gaussian process framework , 2012, Machine Learning.

[3]  Suvrit Sra,et al.  Fast projections onto mixed-norm balls with applications , 2012, Data Mining and Knowledge Discovery.

[4]  Michelangelo Ceci,et al.  Network regression with predictive clustering trees , 2011, Data Mining and Knowledge Discovery.

[5]  Arno J. Knobbe,et al.  Diverse subgroup set discovery , 2012, Data Mining and Knowledge Discovery.

[6]  Johannes Fürnkranz,et al.  Towards Preference-Based Reinforcement Learning , 2012 .

[7]  Marc Sebban,et al.  Good edit similarity learning by loss minimization , 2012, Machine Learning.

[8]  Jilles Vreeken,et al.  Comparing apples and oranges: measuring differences between exploratory data mining results , 2012, Data Mining and Knowledge Discovery.

[9]  Eyke Hüllermeier,et al.  Learning monotone nonlinear models using the Choquet integral , 2011, Machine Learning.

[10]  Patrick Gallinari,et al.  Sequential approaches for learning datum-wise sparse representations , 2012, Machine Learning.

[11]  Alessandro Rozza,et al.  Novel high intrinsic dimensionality estimators , 2012, Machine Learning.

[12]  Hisashi Kashima,et al.  Tensor factorization using auxiliary information , 2011, Data Mining and Knowledge Discovery.

[13]  Klaus Obermayer,et al.  Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis , 2012, Machine Learning.

[14]  Alessandro Moschitti,et al.  Fast support vector machines for convolution tree kernels , 2012, Data Mining and Knowledge Discovery.

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[16]  Xia Wang,et al.  Actively learning to infer social ties , 2012, Data Mining and Knowledge Discovery.