Miro Dudík
Dissertation
  • Maximum entropy density estimation and modeling geographic distributions of species, PhD thesis, Department of Computer Science, Princeton University, 2007, [pdf] [tech report link]
Peer-reviewed conferences and journals
  • First-order mixed integer linear programming, with G. J. Gordon and S. A. Hong, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, 2009, [pdf]
  • A sampling-based approach to computing equilibria in succinct extensive-form games, with G. J. Gordon, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, 2009, [pdf]
  • Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data, with S. J. Phillips, J. Elith et al., Ecological Applications 19:1, 2009, 181-197, [pdf]
  • Generative and discriminative learning with unknown labeling bias, with S. J. Phillips, Advances in Neural Information Processing Systems 21, 2009, [ps] [pdf]
  • Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation, with S. J. Phillips, Ecography 31:2, 2008, 161-175, [pdf]
  • Maximum entropy density estimation with generalized regularization and an application to species distribution modeling, with S. J. Phillips and R. E. Schapire, Journal of Machine Learning Research 8, 2007, 1217-1260, [journal]
  • Hierarchical maximum entropy density estimation, with D. M. Blei and R. E. Schapire, Proceedings of the 24th International Conference on Machine Learning, 2007, [pdf] [video]
  • Maximum entropy distribution estimation with generalized regularization, with R. E. Schapire, Proceedings of the 19th Annual Conference on Learning Theory, 2006, 123-138, [pdf]
  • Novel methods improve prediction of species' distributions from occurrence data, with J. Elith, C. Graham et al., Ecography 29:2, 2006, 129-151, [pdf]
  • Correcting sample selection bias in maximum entropy density estimation, with R. E. Schapire and S. J. Phillips, Advances in Neural Information Processing Systems 18, 2006, [ps] [pdf]
  • Performance guarantees for regularized maximum entropy density estimation, with S. J. Phillips and R. E. Schapire, Proceedings of the 17th Annual Conference on Learning Theory, 2004, 472-486, [ps] [pdf]
  • A maximum entropy approach to species distribution modeling, with S. J. Phillips and R. E. Schapire, Proceedings of the 21st International Conference on Machine Learning, 2004, 655-662, [ps] [pdf]
  • Reconstruction from subsequences, with L. J. Schulman, J. Combinatorial Theory Series A 103, 2003, 337-348, [journal]
Last modified: Aug 1st, 2009