Machine Learning, Volume 69, 2007

Volume 69, Number 1, October 2007

• Zhihua Zhang, James T. Kwok, Dit-Yan Yeung:
  Surrogate maximization/minimization algorithms and extensions. 1-33
  Electronic Edition (link) BibTeX
• Ying Yang, Geoffrey I. Webb, Kevin B. Korb, Kai Ming Ting:
  Classifying under computational resource constraints: anytime classification using probabilistic estimators. 35-53
  Electronic Edition (link) BibTeX
• Gokhan Tur:
  Extending boosting for large scale spoken language understanding. 55-74
  Electronic Edition (link) BibTeX

Volume 69, Numbers 2-3, December 2007

• Avrim Blum, Gábor Lugosi, Hans-Ulrich Simon:
  Introduction to the special issue on COLT 2006. 75-77
  Electronic Edition (link) BibTeX
• Homin K. Lee, Rocco A. Servedio, Andrew Wan:
  DNF are teachable in the average case. 79-96
  Electronic Edition (link) BibTeX
• Adam R. Klivans, Alexander A. Sherstov:
  Unconditional lower bounds for learning intersections of halfspaces. 97-114
  Electronic Edition (link) BibTeX
• Shai Shalev-Shwartz, Yoram Singer:
  A primal-dual perspective of online learning algorithms. 115-142
  Electronic Edition (link) BibTeX
• Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile:
  Tracking the best hyperplane with a simple budget Perceptron. 143-167
  Electronic Edition (link) BibTeX
• Elad Hazan, Amit Agarwal, Satyen Kale:
  Logarithmic regret algorithms for online convex optimization. 169-192
  Electronic Edition (link) BibTeX
• Vladimir Vovk:
  Competing with wild prediction rules. 193-212
  Electronic Edition (link) BibTeX
• Shai Fine, Yishay Mansour:
  Active sampling for multiple output identification. 213-228
  Electronic Edition (link) BibTeX