Miroslav Dudik
Miroslav Dudik
Microsoft Research
Verified email at microsoft.com
TitleCited byYear
Novel methods improve prediction of species’ distributions from occurrence data
J Elith*, C H. Graham*, R P. Anderson, M Dudík, S Ferrier, A Guisan, ...
Ecography 29 (2), 129-151, 2006
63992006
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
SJ Phillips, M Dudík
Ecography 31 (2), 161-175, 2008
43212008
A statistical explanation of MaxEnt for ecologists
J Elith, SJ Phillips, T Hastie, M Dudík, YE Chee, CJ Yates
Diversity and distributions 17 (1), 43-57, 2011
35512011
A maximum entropy approach to species distribution modeling
SJ Phillips, M Dudík, RE Schapire
Proceedings of the twenty-first international conference on Machine learning, 83, 2004
19082004
Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data
SJ Phillips, M Dudík, J Elith, CH Graham, A Lehmann, J Leathwick, ...
Ecological applications 19 (1), 181-197, 2009
15982009
A reliable effective terascale linear learning system
A Agarwal, O Chapelle, M Dudik, J Langford
Arxiv preprint arXiv:1110.4198, 2011
3202011
Opening the black box: An open‐source release of Maxent
SJ Phillips, RP Anderson, M Dudík, RE Schapire, ME Blair
Ecography 40 (7), 887-893, 2017
3032017
Doubly robust policy evaluation and learning
M Dudik, J Langford, L Li
ICML 2011, 2011
2352011
Performance guarantees for regularized maximum entropy density estimation
M Dudik, SJ Phillips, RE Schapire
International Conference on Computational Learning Theory, 472-486, 2004
2082004
Maximum entropy density estimation with generalized regularization and an application to species distribution modeling
M Dudık, SJ Phillips, RE Schapire
Journal of Machine Learning Research 8, 1217-1260, 2007
1912007
Correcting sample selection bias in maximum entropy density estimation
M Dudık, RE Schapire, SJ Phillips
Advances in neural information processing systems 17, 323-330, 2005
1812005
Efficient Optimal Learning for Contextual Bandits
M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang
UAI 2011, 2011
1742011
Maxent software for modeling species niches and distributions v. 3.4. 1
SJ Phillips, M Dudík, RE Schapire
URL: http://biodiversityinformatics. amnh. org/open_source/maxent, 2017
137*2017
A reductions approach to fair classification
A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach
arXiv preprint arXiv:1803.02453, 2018
1292018
Lifted coordinate descent for learning with trace-norm regularization
M Dudík, Z Harchaoui, J Malick
AISTATS 2012, 2012
1082012
Maxent software for species distribution modeling
SJ Phillips, M Dudík, RE Schapire
Á/< w ww. cs. princeton. edu/schapire/maxent, 2005
101*2005
Large-scale image classification with trace-norm regularization
Z Harchaoui, M Douze, M Paulin, M Dudik, J Malick
CVPR 2012, 2012
1002012
Maximum entropy distribution estimation with generalized regularization
M Dudík, RE Schapire
International Conference on Computational Learning Theory, 123-138, 2006
642006
Doubly robust policy evaluation and optimization
M Dudík, D Erhan, J Langford, L Li
Statistical Science 29 (4), 485-511, 2014
612014
Performance guarantees for regularized maximum entropy density estimation
M Dudık, SJ Phillips, RE Schapire
Proceedings of the 17th annual Conference on Learning Theory,(COLT 2004 …, 2004
552004
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Articles 1–20