Machine Learning, Volume 83

Volume 83, Number 1, April 2011

• Chiaki Sakama, Katsumi Inoue:
  Inductive equivalence in clausal logic and nonmonotonic logic programming. 1-29
  
• Stéphan Clémençon, Marine Depecker, Nicolas Vayatis:
  Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree. 31-69
  
• Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile:
  Learning noisy linear classifiers via adaptive and selective sampling. 71-102
  
• Wenjun Zhou, Hui Xiong:
  Checkpoint evolution for volatile correlation computing. 103-131
  

Volume 83, Number 2, May 2011

• Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro Domingos, Kristian Kersting, Xifeng Yan:
  Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. 133-135
  
• Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt:
  Effective feature construction by maximum common subgraph sampling. 137-161
  
• Ondrej Kuzelka, Filip Zelezný:
  Block-wise construction of tree-like relational features with monotone reducibility and redundancy. 163-192
  
• Andreas Maunz, Christoph Helma, Stefan Kramer:
  Efficient mining for structurally diverse subgraph patterns in large molecular databases. 193-218
  
• Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andrea Passerini:
  Relational information gain. 219-239
  
• Taisuke Sato, Masakazu Ishihata, Katsumi Inoue:
  Constraint-based probabilistic modeling for statistical abduction. 241-264
  

Volume 83, Number 3, June 2011

• Justin Guinney, Qiang Wu, Sayan Mukherjee:
  Estimating variable structure and dependence in multitask learning via gradients. 265-287
  
• Steffen Grünewälder, Klaus Obermayer:
  The optimal unbiased value estimator and its relation to LSTD, TD and MC. 289-330
  
• David R. Hardoon, John Shawe-Taylor:
  Sparse canonical correlation analysis. 331-353
  
• Marco Grzegorczyk, Dirk Husmeier:
  Non-homogeneous dynamic Bayesian networks for continuous data. 355-419
  

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