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Silvia Di Gregorio - LIPN Research Published Papers Partial optimality in cubic correlation clustering, with D. Stein, B. Andres, Proceedings of ICML 2023, URL On the complexity of binary polynomial optimization over acyclic hypergraphs, with A. Del Pia, Algorithmica, 2023, DOI
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Read Silvia Di Gregorio's latest research, browse their coauthor's research, and play around with their algorithms
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Silvia Di Gregorio Client Director at Persado | Enterprise Generative AI, Personalization, Martech 5mo Edited
Silvia DI GREGORIO Doctor of Philosophy Technische Universität
Friday, December 1, 2023 at 12:00pm ET Silvia Di Gregorio Université Sorbonne Paris Nord A Knowledge Compilation Take on Binary Polynomial Optimization Jan Kronqvist KTH Royal Institute of Technology Building upon linear MIP techniques to solve convex MINLP For questions or suggestions, please contact Aleksandr M. Kazachkov or Elias B. Khalil.
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Silvia Di Gregorio Technische Universität Dresden | TUD · Institute of Artificial Intelligence Doctor of Philosophy Postdoc at TU Dresden Connect with experts in your field Join ResearchGate to.
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Part of Discrete Optimization Talks: https://talks.discreteopt.comSilvia Di Gregorio - Université Sorbonne Paris NordSpeaker webpage: https://www.lipn.univ-p.
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Silvia is currently a Research Associate at TU Dresden. Publications Stein D., Di Gregorio S. and Andres B. Partial Optimality in Cubic Correlation Clustering ICML 2023 (accepted) arXiv • PDF (pre-print) Andres B., Di Gregorio S., Irmai J. and Lange J.-H. A Polyhedral Study of Lifted Multicuts Discrete Optimization 47:100757, 2023
Silvia Di Gregorio (SilviaClo21) Twitter
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Silvia Di Gregorio Associate professor I am an Associate Professor (maîtresse de conférences) at the Sorbonne Paris Nord University , where I teach at the IUT de Villetaneuse. I am part of the Algorithms and Combinatorial Optimization group ( AOC ) at the Northern Paris Computer Science Lab ( LIPN ). Bio
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The thesis is written in English and is available from the author upon request at [email protected]. This work deals with binary polynomial optimization, which is the problem of maximizing a polynomial function under the sole constraint that all the variables must be binary. As this problem subsumes binary quadratic optimization.
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Silvia Di Gregorio. University Sorbonne Paris Nord, LIPN. Verified email at lipn.univ-paris13.fr - Homepage.. B Andres, S Di Gregorio, J Irmai, JH Lange. Discrete Optimization 47, 100757, 2023. 1: 2023: A Knowledge Compilation Take on Binary Polynomial Optimization. F Capelli, A Del Pia, S Di Gregorio.
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Authors: Alberto Del Pia, Silvia Di Gregorio. Download PDF Abstract: In this work we advance the understanding of the fundamental limits of computation for Binary Polynomial Optimization (BPO), which is the problem of maximizing a given polynomial function over all binary points. In our main result we provide a novel class of BPO that can be.
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Silvia Di Gregorio Client Partner at Persado | Enterprise Generative AI, Personalization, Martech Milano, Lombardia, Italia 3323 follower Oltre 500 collegamenti Piacere di rivederti Persado.
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