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Peer-reviewed conferences and journals
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- Maximizing revenue in symmetric resource allocation systems
when user utilities exhibit diminishing returns,
with R. Zivan, P. Paruchuri and K. Sycara,
Proceedings of the 10th International Conference on
Autonomous Agents and Multiagent Systems, 2011,
[pdf]
- A statistical explanation of MaxEnt for ecologists,
with J. Elith, S. J. Phillips et al., Diversity and Distributions 17,
2011, 43-57,
[journal]
- Reducing untruthful manipulation in envy-free Pareto optimal
resource allocation,
with R. Zivan, S. Okamoto and K. Sycara,
Proceedings of the 2010 IEEE/WIC/ACM International Conference
on Intelligent Agent Technology, 2010,
[pdf]
- 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]
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