Machine Learning, Volume 75, 2009 (original) (raw)



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Volume 75, Number 1, April 2009
Special issue on mining and learning with graphs

Thomas Gärtner
, Gemma C. Garriga:
Guest editors' introduction: special issue on mining and learning with graphs. 1-2

Pierre Mahé, Jean-Philippe Vert
:
Graph kernels based on tree patterns for molecules. 3-35

Masashi Shimbo, Takahiko Ito, Daichi Mochihashi, Yuji Matsumoto:
On the properties of von Neumann kernels for link analysis. 37-67

Hiroto Saigo
, Sebastian Nowozin, Tadashi Kadowaki, Taku Kudo, Koji Tsuda:
gBoost: a mathematical programming approach to graph classification and regression. 69-89

Stéphanie Jacquemont, François Jacquenet, Marc Sebban:
Mining probabilistic automata: a statistical view of sequential pattern mining. 91-127

Tapio Pahikkala
, Evgeni Tsivtsivadze, Antti Airola
, Jouni Järvinen
, Jorma Boberg:
An efficient algorithm for learning to rank from preference graphs. 129-165
Volume 75, Number 2, May 2009
Volume 75, Number 3, June 2009

Masashi Sugiyama, Shinichi Nakajima:
Pool-based active learning in approximate linear regression. 249-274

Bin Zou, Luoqing Li, Zongben Xu:
The generalization performance of ERM algorithm with strongly mixing observations. 275-295

Hal Daumé III, John Langford, Daniel Marcu:
Search-based structured prediction. 297-325

Andreas Maurer:
Transfer bounds for linear feature learning. 327-350

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