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_modules/MRCpy/base_mrc.html

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@@ -229,9 +229,9 @@ <h1>Source code for MRCpy.base_mrc</h1><div class="highlight"><pre>
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<span class="sd"> Journal of Machine Learning Research, 24(208), 1-48.</span>
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<span class="sd"> &lt;https://jmlr.org/papers/volume24/22-0339/22-0339.pdf&gt;`_</span>
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<span class="sd"> - `Bondugula, K., Mazuelas, S., &amp; Pérez,</span>
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<span class="sd"> A. (2021). MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> - `Bondugula, K., Álvarez, V., Segovia-Martín, J.I.,</span>
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<span class="sd"> Pérez, A., &amp; Mazuelas, S. (2021). MRCpy: A Library for</span>
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<span class="sd"> Minimax Risk Classifiers. arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2108.01952&gt;`_</span>
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<span class="sd"> Parameters</span>

_modules/MRCpy/phi/base_phi.html

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<span class="sd"> arXiv preprint arXiv:2007.05447.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2007.05447&gt;`_</span>
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<span class="sd"> [3] `Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).</span>
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<span class="sd"> [3] `Bondugula, K., Álvarez, V.,</span>
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<span class="sd"> Segovia-Martín, J.I., Pérez, A., &amp; Mazuelas, S. (2021).</span>
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<span class="sd"> MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2108.01952&gt;`_</span>

_modules/MRCpy/phi/random_fourier_phi.html

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@@ -224,7 +224,8 @@ <h1>Source code for MRCpy.phi.random_fourier_phi</h1><div class="highlight"><pre
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<span class="sd"> arXiv preprint arXiv:2007.05447.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2007.05447&gt;`_</span>
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<span class="sd"> [4] `Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).</span>
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<span class="sd"> [4] `Bondugula, K., Álvarez, V.,</span>
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<span class="sd"> Segovia-Martín, J.I., Pérez, A., &amp; Mazuelas, S. (2021).</span>
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<span class="sd"> MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2108.01952&gt;`_</span>

_modules/MRCpy/phi/random_relu_phi.html

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@@ -224,8 +224,9 @@ <h1>Source code for MRCpy.phi.random_relu_phi</h1><div class="highlight"><pre>
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<span class="sd"> arXiv preprint arXiv:2007.05447.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2007.05447&gt;`_</span>
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<span class="sd"> [4] `Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).</span>
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<span class="sd"> MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> [4] `Bondugula, K., Álvarez, V.,</span>
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<span class="sd"> Segovia-Martín, J.I., Pérez, A., &amp; Mazuelas, S.</span>
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<span class="sd"> (2021). MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2108.01952&gt;`_</span>
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_modules/MRCpy/phi/threshold_phi.html

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<span class="sd"> arXiv preprint arXiv:2007.05447.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2007.05447&gt;`_</span>
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<span class="sd"> - `Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).</span>
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<span class="sd"> - `Bondugula, K., Álvarez, V., Segovia-Martín, J.I.,</span>
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<span class="sd"> Pérez, A., &amp; Mazuelas, S. (2021).</span>
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<span class="sd"> MRCpy: A Library for Minimax Risk Classifiers.</span>
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<span class="sd"> arXiv preprint arXiv:2108.01952.</span>
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<span class="sd"> &lt;https://arxiv.org/abs/2108.01952&gt;`_</span>

_sources/index.rst.txt

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References
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----------
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For more information about the methods available in MRCpy library, one can refer to the following resources:
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For more information about the methods available in MRCpy library, one can refer to the following resources:
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- [1] `Bondugula, K., Mazuelas, S., Pérez, A., & Liu, A. (2026). Minimax Generalized Cross-Entropy. In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS). <https://arxiv.org/abs/2411.07789>`_
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[1] `Bondugula, K., Mazuelas, S., Pérez, A., & Liu, A. (2026). Minimax Generalized Cross-Entropy. In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS). <https://arxiv.org/abs/2411.07789>`_
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::
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::
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@inproceedings{BonMazPerLiu:26,
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title={Minimax Generalized Cross-Entropy},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz and Liu, Anqi},
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booktitle={Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)},
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year={2026}
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}
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- [2] `Bondugula, K., Mazuelas, S., & Pérez, A. (2025). Efficient Large-Scale Learning of Minimax Risk Classifiers. IEEE International Conference on Data Mining (ICDM). <https://arxiv.org/abs/2406.11684>`_
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::
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@inproceedings{BonMazPer:25,
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title={Efficient Large-Scale Learning of Minimax Risk Classifiers},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz},
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booktitle={IEEE International Conference on Data Mining (ICDM)},
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year={2025}
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}
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- [3] `Mazuelas, S., Romero, M., & Grunwald, P. (2023). Minimax Risk Classifiers with 0-1 Loss. Journal of Machine Learning Research, 24(208), 1-48. <https://jmlr.org/papers/volume24/22-0339/22-0339.pdf>`_
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::
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@article{MazRomGrun:23,
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author = {Mazuelas, Santiago and Romero, Mauricio and Grunwald, Peter},
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title = {Minimax Risk Classifiers with 0-1 Loss},
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journal={Journal of Machine Learning Research},
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volume = {24},
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number = {208},
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pages = {1--48},
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year={2023}
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}
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- [4] `Bondugula, K., Mazuelas, S., & Pérez, A. (2023). Efficient Learning of Minimax Risk Classifiers in High Dimensions. The 39th Conference on Uncertainty in Artificial Intelligence (UAI), 206-215. <https://proceedings.mlr.press/v216/bondugula23a.html>`_
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::
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@inproceedings{BonMazPer:23,
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title={Efficient Learning of Minimax Risk Classifiers in High Dimensions},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz},
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booktitle={The 39th Conference on Uncertainty in Artificial Intelligence (UAI)},
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pages={206--215},
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year={2023}
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}
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- [5] `Segovia-Martín, J.I., Mazuelas, S., & Liu, A. (2023). Double-Weighting for Covariate Shift Adaptation. In Proceedings of the 40th International Conference on Machine Learning (ICML), pp. 30439-30457. <https://proceedings.mlr.press/v202/segovia-martin23a.html>`_
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::
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@inproceedings{SegMazLiu:23,
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title={Double-Weighting for Covariate Shift Adaptation},
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author={Segovia-Mart{\'i}n, Jos{\'e} I. and Mazuelas, Santiago and Liu, Anqi},
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booktitle={Proceedings of the 40th International Conference on Machine Learning (ICML)},
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pages={30439--30457},
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year={2023}
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}
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- [6] `Mazuelas, S., Shen, Y., & Pérez, A. (2022). Generalized Maximum Entropy for Supervised Classification. IEEE Transactions on Information Theory, 68(4), 2530-2550. <https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9682746>`_
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::
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@article{MazShePer:22,
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author = {Santiago Mazuelas and Yuan Shen and Aritz P\'{e}rez},
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title = {Generalized Maximum Entropy for Supervised Classification},
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journal={IEEE Transactions on Information Theory},
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volume = {68},
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number = {4},
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pages = {2530-2550},
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year={2022}
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}
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- [7] `Álvarez, V., Mazuelas, S., & Lozano, J.A. (2022). Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees. In Proceedings of the 39th International Conference on Machine Learning (ICML), pp. 486-499. <https://proceedings.mlr.press/v162/alvarez22a.html>`_
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::
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@inproceedings{AlvMazLoz:22,
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title={Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees},
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author={{\'A}lvarez, Ver{\'o}nica and Mazuelas, Santiago and Lozano, Jos{\'e} A.},
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booktitle={Proceedings of the 39th International Conference on Machine Learning (ICML)},
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pages={486--499},
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year={2022}
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}
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- [8] `Bondugula, K., Mazuelas, S., & Pérez, A. (2021). MRCpy: A Library for Minimax Risk Classifiers. arXiv preprint arXiv:2108.01952. <https://arxiv.org/abs/2108.01952>`_
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::
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@article{bondugula2021mrcpy,
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title={MRCpy: A Library for Minimax Risk Classifiers},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz},
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journal={arXiv preprint arXiv:2108.01952},
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year={2021}
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}
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- [9] `Mazuelas, S., Zanoni, A., & Pérez, A. (2020). Minimax Classification with 0-1 Loss and Performance Guarantees. Advances in Neural Information Processing Systems, 33, 302-312. <https://proceedings.neurips.cc/paper_files/paper/2020/file/02f657d55eaf1c4840ce8d66fcdaf90c-Paper.pdf>`_
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::
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@article{mazuelas2020minimax,
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title={Minimax Classification with 0-1 Loss and Performance Guarantees},
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author={Mazuelas, Santiago and Zanoni, Andrea and P{\'e}rez, Aritz},
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journal={Advances in Neural Information Processing Systems},
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volume={33},
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pages={302--312},
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year={2020}
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}
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@inproceedings{BonMazPerLiu:26,
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title={Minimax Generalized Cross-Entropy},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz and Liu, Anqi},
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booktitle={Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)},
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year={2026}
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}
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[2] `Bondugula, K., Mazuelas, S., & Pérez, A. (2025). Efficient Large-Scale Learning of Minimax Risk Classifiers. IEEE International Conference on Data Mining (ICDM). <https://arxiv.org/abs/2511.17626>`_
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::
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@inproceedings{BonMazPer:25,
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title={Efficient Large-Scale Learning of Minimax Risk Classifiers},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz},
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booktitle={IEEE International Conference on Data Mining (ICDM)},
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year={2025}
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}
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[3] `Mazuelas, S., Romero, M., & Grunwald, P. (2023). Minimax Risk Classifiers with 0-1 Loss. Journal of Machine Learning Research, 24(208), 1-48. <https://jmlr.org/papers/volume24/22-0339/22-0339.pdf>`_
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::
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@article{MazRomGrun:23,
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author = {Mazuelas, Santiago and Romero, Mauricio and Grunwald, Peter},
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title = {Minimax Risk Classifiers with 0-1 Loss},
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journal={Journal of Machine Learning Research},
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volume = {24},
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number = {208},
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pages = {1--48},
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year={2023}
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}
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[4] `Bondugula, K., Mazuelas, S., & Pérez, A. (2023). Efficient Learning of Minimax Risk Classifiers in High Dimensions. The 39th Conference on Uncertainty in Artificial Intelligence (UAI), 206-215. <https://proceedings.mlr.press/v216/bondugula23a.html>`_
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::
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@inproceedings{BonMazPer:23,
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title={Efficient Learning of Minimax Risk Classifiers in High Dimensions},
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author={Bondugula, Kartheek and Mazuelas, Santiago and P{\'e}rez, Aritz},
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booktitle={The 39th Conference on Uncertainty in Artificial Intelligence (UAI)},
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pages={206--215},
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year={2023}
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}
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[5] `Segovia-Martín, J.I., Mazuelas, S., & Liu, A. (2023). Double-Weighting for Covariate Shift Adaptation. In Proceedings of the 40th International Conference on Machine Learning (ICML), pp. 30439-30457. <https://proceedings.mlr.press/v202/segovia-martin23a.html>`_
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::
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@inproceedings{SegMazLiu:23,
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title={Double-Weighting for Covariate Shift Adaptation},
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author={Segovia-Mart{\'i}n, Jos{\'e} I. and Mazuelas, Santiago and Liu, Anqi},
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booktitle={Proceedings of the 40th International Conference on Machine Learning (ICML)},
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pages={30439--30457},
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year={2023}
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}
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[6] `Mazuelas, S., Shen, Y., & Pérez, A. (2022). Generalized Maximum Entropy for Supervised Classification. IEEE Transactions on Information Theory, 68(4), 2530-2550. <https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9682746>`_
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::
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@article{MazShePer:22,
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author = {Santiago Mazuelas and Yuan Shen and Aritz P\'{e}rez},
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title = {Generalized Maximum Entropy for Supervised Classification},
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journal={IEEE Transactions on Information Theory},
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volume = {68},
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number = {4},
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pages = {2530-2550},
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year={2022}
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}
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[7] `Álvarez, V., Mazuelas, S., & Lozano, J.A. (2022). Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees. In Proceedings of the 39th International Conference on Machine Learning (ICML), pp. 486-499. <https://proceedings.mlr.press/v162/alvarez22a.html>`_
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::
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@inproceedings{AlvMazLoz:22,
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title={Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees},
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author={{\'A}lvarez, Ver{\'o}nica and Mazuelas, Santiago and Lozano, Jos{\'e} A.},
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booktitle={Proceedings of the 39th International Conference on Machine Learning (ICML)},
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pages={486--499},
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year={2022}
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}
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[8] `Bondugula, K., Álvarez, V., Segovia-Martín, J.I., Pérez, A., & Mazuelas, S. (2021). MRCpy: A Library for Minimax Risk Classifiers. arXiv preprint arXiv:2108.01952. <https://arxiv.org/abs/2108.01952>`_
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::
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@article{bondugula2021mrcpy,
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title={MRCpy: A Library for Minimax Risk Classifiers},
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author={Bondugula, Kartheek and {\'A}lvarez, Ver{\'o}nica and Segovia-Mart{\'i}n, Jos{\'e} I. and P{\'e}rez, Aritz and Mazuelas, Santiago},
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journal={arXiv preprint arXiv:2108.01952},
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year={2021}
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}
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[9] `Mazuelas, S., Zanoni, A., & Pérez, A. (2020). Minimax Classification with 0-1 Loss and Performance Guarantees. Advances in Neural Information Processing Systems, 33, 302-312. <https://proceedings.neurips.cc/paper_files/paper/2020/file/02f657d55eaf1c4840ce8d66fcdaf90c-Paper.pdf>`_
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::
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@article{mazuelas2020minimax,
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title={Minimax Classification with 0-1 Loss and Performance Guarantees},
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author={Mazuelas, Santiago and Zanoni, Andrea and P{\'e}rez, Aritz},
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journal={Advances in Neural Information Processing Systems},
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volume={33},
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pages={302--312},
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year={2020}
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}
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Funding
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^^^^^^^^

_sources/minimax_framework.rst.txt

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Entropy for Supervised Classification. IEEE Transactions on
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Information Theory, 68(4), 2530-2550.
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.. [3] Bondugula, K., Mazuelas, S., & Pérez, A. (2021). MRCpy: A Library
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for Minimax Risk Classifiers. arXiv preprint arXiv:2108.01952.
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.. [3] Bondugula, K., Álvarez, V., Segovia-Martín, J.I., Pérez, A.,
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& Mazuelas, S. (2021). MRCpy: A Library for Minimax Risk Classifiers.
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arXiv preprint arXiv:2108.01952.
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.. [4] Mazuelas, S., Zanoni, A., & Pérez, A. (2020). Minimax Classification
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with 0-1 Loss and Performance Guarantees. Advances in Neural

generated/MRCpy.BaseMRC.html

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<li><p><a class="reference external" href="https://jmlr.org/papers/volume24/22-0339/22-0339.pdf">Mazuelas, S., Romero, M., Grunwald, P. (2023).
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Journal of Machine Learning Research, 24(208), 1-48.</a></p></li>
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<li><p><a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Mazuelas, S., &amp; Pérez,
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A. (2021). MRCpy: A Library for Minimax Risk Classifiers.
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arXiv preprint arXiv:2108.01952.</a></p></li>
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<li><p><a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Álvarez, V., Segovia-Martín, J.I.,
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Pérez, A., &amp; Mazuelas, S. (2021). MRCpy: A Library for
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Minimax Risk Classifiers. arXiv preprint arXiv:2108.01952.</a></p></li>
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<dl class="field-list">

generated/MRCpy.phi.BasePhi.html

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<p>[2] <a class="reference external" href="https://arxiv.org/abs/2007.05447">Mazuelas, S., Shen, Y., &amp; Pérez, A. (2020).
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Generalized Maximum Entropy for Supervised Classification.
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<p>[3] <a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).
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<p>[3] <a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Álvarez, V.,
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Segovia-Martín, J.I., Pérez, A., &amp; Mazuelas, S. (2021).
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MRCpy: A Library for Minimax Risk Classifiers.
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arXiv preprint arXiv:2108.01952.</a></p>
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</div></blockquote>

generated/MRCpy.phi.RandomFourierPhi.html

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<p>[3] <a class="reference external" href="https://arxiv.org/abs/2007.05447">Mazuelas, S., Shen, Y., &amp; Pérez, A. (2020).
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Generalized Maximum Entropy for Supervised Classification.
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arXiv preprint arXiv:2007.05447.</a></p>
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<p>[4] <a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Mazuelas, S., &amp; Pérez, A. (2021).
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<p>[4] <a class="reference external" href="https://arxiv.org/abs/2108.01952">Bondugula, K., Álvarez, V.,
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Segovia-Martín, J.I., Pérez, A., &amp; Mazuelas, S. (2021).
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MRCpy: A Library for Minimax Risk Classifiers.
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arXiv preprint arXiv:2108.01952.</a></p>
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</div></blockquote>

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