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The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.

M. Gasse, Q. Cappart, J. Charfreitag, L. Charlin, D. Chételat, A. Chmiela, J. Dumouchelle, A. Gleixner, A. Kazachkov, E. Khalil, P. Lichocki, A. Lodi, M. Lubin, C. Maddison, C. Morris, D. Papageorgiou, A. Parjadis, S. Pokutta, A. Prouvost, L. Scavuzzo, G. Zarpellon, L. Yang, S. Lai, A. Wang, X. Luo, X. Zhou, H. Huang, S. Shao, Y. Zhu, D. Zhang, T. Quan, Z. Cao, Y. Xu, Z. Huang, S. Zhou, B. Chen, M. He, H. Hao, Z. Zhang, Z. An, and K. Mao. CoRR, (2022)

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Giulia Agostini

Giulia Calenda

Giulia Zancolli

Giulia Morra

Giulia Vannoni

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Learning a Classification of Mixed-Integer Quadratic Programming Problems.P. Bonami, A. Lodi, and G. Zarpellon. CPAIOR, volume 10848 of Lecture Notes in Computer Science, page 595-604. Springer, (2018)Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies.G. Zarpellon, J. Jo, A. Lodi, and Y. Bengio. CoRR, (2020)Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies.G. Zarpellon, J. Jo, A. Lodi, and Y. Bengio. AAAI, page 3931-3939. AAAI Press, (2021)A Classifier to Decide on the Linearization of Mixed-Integer Quadratic Problems in CPLEX.P. Bonami, A. Lodi, and G. Zarpellon. Oper. Res., 70 (6): 3303-3320 (November 2022)Pyafscgap.org: Open source multi-modal Python-based tools for NOAA AFSC RACE GAP.A. Pottinger, and G. Zarpellon. J. Open Source Softw., 8 (87): 5593 (July 2023)Learning MILP Resolution Outcomes Before Reaching Time-Limit.M. Fischetti, A. Lodi, and G. Zarpellon. CPAIOR, volume 11494 of Lecture Notes in Computer Science, page 275-291. Springer, (2019)The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.M. Gasse, S. Bowly, Q. Cappart, J. Charfreitag, L. Charlin, D. Chételat, A. Chmiela, J. Dumouchelle, A. Gleixner, A. Kazachkov and 32 other author(s). NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 220-231. PMLR, (2021)The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.M. Gasse, Q. Cappart, J. Charfreitag, L. Charlin, D. Chételat, A. Chmiela, J. Dumouchelle, A. Gleixner, A. Kazachkov, E. Khalil and 31 other author(s). CoRR, (2022)Biohybrid soft robots with self-stimulating skeletons.M. Guix, R. Mestre, T. Patiño, M. Corato, J. Fuentes, G. Zarpellon, and S. Sánchez. Sci. Robotics, 6 (53): 7577 (2021)Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning.M. Paulus, G. Zarpellon, A. Krause, L. Charlin, and C. Maddison. ICML, volume 162 of Proceedings of Machine Learning Research, page 17584-17600. PMLR, (2022)

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Disambiguation of "Zarpellon, Giulia"

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The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.

Please choose a person to relate this publication to

Giulia Agostini

Giulia Calenda

Giulia Zancolli

Giulia Morra

Giulia Vannoni

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Zarpellon, Giulia"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.

Please choose a person to relate this publication to

Giulia Agostini

Giulia Calenda

Giulia Zancolli

Giulia Morra

Giulia Vannoni

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.