Search Results - "data-driven algorithm design"
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Authors: et al.
Source: Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing. :919-932
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Machine Learning (stat.ML), 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG)
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Authors:
Source: Communications of the ACM. 63:87-94
Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences
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Source: 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS). :603-614
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, 0102 computer and information sciences, 01 natural sciences, Machine Learning (cs.LG)
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Authors: Maria-Florina Balcan
Source: Beyond the Worst-Case Analysis of Algorithms ISBN: 9781108637435
Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Data Structures and Algorithms, 0202 electrical engineering, electronic engineering, information engineering, Data Structures and Algorithms (cs.DS), 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG)
Access URL: http://arxiv.org/pdf/2011.07177
http://arxiv.org/abs/2011.07177
https://arxiv.org/abs/2011.07177
https://www.cambridge.org/core/books/beyond-the-worstcase-analysis-of-algorithms/datadriven-algorithm -design /E82EB983E99AF747A36047CE982A1A96
https://dblp.uni-trier.de/db/journals/corr/corr2011.html#abs-2011-07177
https://arxiv.org/pdf/2011.07177 -
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Authors: et al.
Index Terms: Computer Science - Machine Learning, Statistics - Machine Learning, text
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Authors: et al.
Source: Journal of the ACM. 71:1-58
Subject Terms: 0301 basic medicine, data-driven algorithm design, 0303 health sciences, 03 medical and health sciences, machine learning, computational biology, General topics in the theory of algorithms, Learning and adaptive systems in artificial intelligence, automated algorithm design, automated algorithm configuration
File Description: application/xml
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Authors: et al.
Contributors: et al.
Subject Terms: FOS: Computer and information sciences, data-driven algorithm design, Computer Science - Data Structures and Algorithms, solution portfolios, Data Structures and Algorithms (cs.DS), ddc:004, matroids
File Description: application/pdf
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Authors:
Source: Communications of the ACM; Jun2020, Vol. 63 Issue 6, p87-94, 8p
Subject Terms: ALGORITHMS, MACHINE learning, MATHEMATICAL optimization, MATHEMATICAL proofs, DECISION theory
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Authors:
Source: Journal of the ACM. Jun2024, Vol. 71 Issue 3, p1-34. 34p.
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Authors: et al.
Subject Terms: data-driven algorithm design, matroids, solution portfolios
Relation: 16th Innovations in Theoretical Computer Science Conference (ITCS 2025); Leibniz International Proceedings in Informatics (LIPIcs); 325; The 16th Annual Innovations in Theoretical Computer Science (ITCS) conference; #PLACEHOLDER_PARENT_METADATA_VALUE#; MB22.00054; https://infoscience.epfl.ch/handle/20.500.14299/247349
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Authors: et al.
Contributors: et al.
Subject Terms: Automated algorithm configuration, integer programming, machine learning theory, tree search, branch-and-bound, branch-and-cut, cutting planes, sample complexity, generalization guarantees, data-driven algorithm design
File Description: application/pdf
Relation: Is Part Of LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022); https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.3
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Authors: et al.
Contributors: et al.
Subject Terms: FOS: Computer and information sciences, sample complexity, data-driven algorithm design, Computer Science - Machine Learning, tree search, Automated algorithm configuration, machine learning theory, Computer Science - Artificial Intelligence, 0211 other engineering and technologies, 02 engineering and technology, cutting planes, Machine Learning (cs.LG), branch-and-cut, Artificial Intelligence (cs.AI), generalization guarantees, Optimization and Control (math.OC), Computer Science - Data Structures and Algorithms, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, branch-and-bound, Data Structures and Algorithms (cs.DS), ddc:004, integer programming, Mathematics - Optimization and Control
File Description: application/pdf
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Authors:
Source: National Science Review. Aug2024, Vol. 11 Issue 8, p1-9. 9p.
Subject Terms: *MACHINE learning, *MACHINE design, *ALGORITHMS
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Authors: et al.
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Authors: et al.
Contributors: et al.
Subject Terms: Learning to search, Data-driven algorithm design, Deep learning, Reinforcement learning, Meta-learning, Graph representation learning, Structured prediction, Robotics applications, AI for drug discovery, Chemistry applications
File Description: application/pdf
Relation: https://hdl.handle.net/1853/72742
Availability: https://hdl.handle.net/1853/72742
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Authors: Ellen Vitercik
Subject Terms: Applied computing not elsewhere classified, automated algorithm design, data-driven algorithm design, automated algorithm configuration, sample complexity, machine learning theory, mechanism design, Applied Computer Science
Relation: https://figshare.com/articles/thesis/Automated_Algorithm_and_Mechanism_Configuration/17207516
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