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Publications Related to: Anytime Algorithms

By Shaul Markovitch

  1. Erez Karpas, Michael Katz and Shaul Markovitch. When Optimal is Just Not Good Enough: Fast Near-Optimal Action Cost-Partitioning. In Proceedings of the 21st International Conference on Automated Planning and Scheduling, 122-129 Freiburg, Germany, 2011.[abstract][pdf]
  2. Saher Esmeir and Shaul Markovitch. Anytime Learning of Anycost Classifiers. Machine Learning, 82:445-473 2011.[abstract][pdf]
  3. Carmel Domshlak, Erez Karpas and Shaul Markovitch. Learning to Combine Admissible Heuristics Under Bounded Time. In Proceedings of the ICAPS 2009 Workshop on Planning and Learning, Thessaloniki, Greece, 2009.[abstract][pdf]
  4. Saher Esmeir and Shaul Markovitch. Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. Journal of Artificial Intelligence Research, 33:1-31 2008.[abstract][pdf]
  5. Saher Esmeir and Shaul Markovitch. Anytime Induction of Cost-sensitive Trees. In Proceedings of The 21st Conference on Neural Information Processing Systems (NIPS-2007), Vancouver, Canada, 2007.[abstract][pdf]
  6. Saher Esmeir and Shaul Markovitch. Anytime Learning of Decision Trees. Journal of Machine Learning Research, 8:891-933 2007.[abstract][pdf]
  7. Dmitry Davidov and Shaul Markovitch. Multiple-goal Heuristic Search. Journal of Artificial Intelligence Research, 26:417-451 2006.[abstract][pdf]