Výsledky vyhľadávania - Computational Learning Theory and Optimization

An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory

Autori: Niklas Pirnay Vincent Ulitzsch Frederik Wilde a ďalší

Zdroj: Science Advances. 10

Predmety: FOS: Computer and information sciences, Quantum Physics, 500 Naturwissenschaften und Mathematik::530 Physik::530 Physik, FOS: Physical sciences, 0102 computer and information sciences, Computational Complexity (cs.CC), 01 natural sciences, Condensed Matter - Other Condensed Matter, Computer Science - Computational Complexity, classical algorithms, 0103 physical sciences, Quantum Physics (quant-ph), quantum algorithms, problems of combinatorial optimization, Other Condensed Matter (cond-mat.other)

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38489369
http://arxiv.org/abs/2212.08678
https://refubium.fu-berlin.de/handle/fub188/43564
https://doi.org/10.17169/refubium-43280
https://doi.org/10.1126/sciadv.adj5170

Quantum-classical hybrid algorithm for solving the learning-with-errors problem on NISQ devices.

Autori: Zheng, Muxi Zeng, Jinfeng Yang, Wentao a ďalší

Zdroj: Communications Physics. 5/20/2025, Vol. 8, p1-8. 8p.

Predmety: *COMPUTATIONAL learning theory, *OPTIMIZATION algorithms, *TIME complexity, *HEURISTIC algorithms, *QUANTUM theory, *QUANTUM cryptography

The Price Equation Reveals a Universal Force–Metric–Bias Law of Algorithmic Learning and Natural Selection.

Autori: Frank, Steven A.

Zdroj: Entropy; Nov2025, Vol. 27 Issue 11, p1129, 45p

Predmety: NATURAL selection, MACHINE learning, COMPUTATIONAL learning theory, INFORMATION geometry, MATHEMATICAL optimization, BAYESIAN analysis

An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory

Autori: Pirnay, Niklas Ulitzsch, Vincent Wilde, Frederik a ďalší

Témy: Quantum Physics, Condensed Matter - Other Condensed Matter, Computer Science - Computational Complexity, text

URL: http://arxiv.org/abs/2212.08678

EFFICIENT PDE-CONSTRAINED OPTIMIZATION UNDER HIGH-DIMENSIONAL UNCERTAINTY USING DERIVATIVE-INFORMED NEURAL OPERATORS.

Autori: DINGCHENG LUO O'LEARY-ROSEBERRY, THOMAS PENG CHEN a ďalší

Zdroj: SIAM Journal on Scientific Computing; 2025, Vol. 47 Issue 4, pC899-C931, 33p

Predmety: UNCERTAINTY (Information theory), OPTIMIZATION algorithms, COMPUTATIONAL learning theory, PREDICTION models, ARTIFICIAL intelligence, PROBABILITY measures

Machine learning-accelerated density functional theory optimization of PtPd-based high-entropy alloys for hydrogen evolution catalysis

Autori: Khajondetchairit, Patcharaporn Somdee, Siriwimol Saelee, Tinnakorn a ďalší

Zdroj: International Journal of Minerals, Metallurgy and Materials. 32(11):2777-2785

Predmety: catalyst screening, supervised regression model, multi-element alloys, hydrogen evolution reaction

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-219810

ENHANCING PROBLEM-SOLVING SKILLS IN ENGINEERING STUDENTS THROUGH COMPUTATIONAL AND EXPERIMENTAL LEARNING.

Autori: Reddy, A. Brahmananda Mathias, Regina Dhillon, Manju a ďalší

Zdroj: Lex Localis: Journal of Local Self-Government; 2025 Supplement, Vol. 23 Issue S4, p391-400, 10p

Predmety: PROBLEM solving, ENGINEERING education, MIXED methods research, CONTEXTUAL learning, EDUCATION methodology, STUDENT engagement, CRITICAL thinking, COMPUTATIONAL learning theory

Deep mixed residual method for solving PDE-constrained optimization problems

Autori: Jinjun Yong Xianbing Luo Shuyu Sun a ďalší

Zdroj: Computers & Mathematics with Applications. 176:510-524

Predmety: Numerical methods for partial differential equations, boundary value problems, physics-informed neural network, mixed residual method, Computational learning theory, PDE constrained optimization (numerical aspects), Artificial neural networks and deep learning, PDE constrained optimization

Popis súboru: application/xml

Reinforcement learning in large state action spaces

Autori: Mahajan, Anuj Whiteson, Shimon

Prispievatelia: Mahajan, Anuj Whiteson, Shimon

Predmety: Computational learning theory, Mathematical optimization, Reinforcement learning, Machine learning, Multiagent systems, Artificial intelligence

Prístupová URL adresa: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.886905

Deep Reinforcement Learning in a Search-Matching Model of Labor Market Fluctuations.

Autori: Chen, Ruxin

Zdroj: Economies; Oct2025, Vol. 13 Issue 10, p302, 16p

Predmety: REINFORCEMENT learning, LABOR market, BOUNDED rationality, MATCHING theory, JOB postings, ECONOMIC models, COMPUTATIONAL learning theory

Leveraging Reinforcement Learning and Koopman Theory for Enhanced Model Predictive Control Performance

Autori: Dony, Md Nur-A-Adam

Predmety: 93A30 (Mathematical Systems Theory), 68T05 (Learning and Adaptive Systems), 68Q32 (Computational Learning Theory), FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control

Prístupová URL adresa: http://arxiv.org/abs/2505.08122

Understanding Machine Learning Principles: Learning, Inference, Generalization, and Computational Learning Theory.

Autori: Du, Ke-Lin Zhang, Rengong Jiang, Bingchun a ďalší

Zdroj: Mathematics (2227-7390); Feb2025, Vol. 13 Issue 3, p451, 57p

Predmety: COMPUTATIONAL learning theory, CONCEPT learning, MACHINE theory, RESEARCH personnel, GENERALIZATION

Bayesian continual learning and forgetting in neural networks.

Autori: Bonnet, Djohan Cottart, Kellian Hirtzlin, Tifenn a ďalší

Zdroj: Nature Communications; 10/30/2025, Vol. 16 Issue 1, p1-14, 14p

Predmety: ARTIFICIAL neural networks, MACHINE learning, BAYESIAN analysis, OUTLIER detection, MEMORY loss, COMPUTATIONAL learning theory

Dimensionless learning based on information.

Autori: Yuan, Yuan Lozano-Durán, Adrián

Zdroj: Nature Communications; 10/16/2025, Vol. 16 Issue 1, p1-15, 15p

Predmety: DIMENSIONAL analysis, DIMENSIONLESS numbers, COMPUTATIONAL learning theory, DIMENSIONAL reduction algorithms, STATISTICAL models, INFORMATION theory, FORECASTING

Using computational learning strategies as a tool for combinatorial optimization

Autori: Andreas Birkendorf Hans Ulrich Simon

Zdroj: Annals of Mathematics and Artificial Intelligence. 22:237-257

Predmety: computational learning theory, Learning and adaptive systems in artificial intelligence, NP-hard combinatorial optimization problems, 0202 electrical engineering, electronic engineering, information engineering, Mathematical programming, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences

Popis súboru: application/xml

Prístupová URL adresa: https://zbmath.org/1210278
https://doi.org/10.1023/a:1018991519323
https://dblp.uni-trier.de/db/journals/amai/amai22.html#BirkendorfS98
https://link.springer.com/article/10.1023/A%3A1018991519323

Fractional-Order Deterministic Learning for Fast and Robust Detection of Sub-Synchronous Oscillations in Wind Power Systems.

Autori: Kahouli, Omar El Amraoui, Lilia Ayari, Mohamed a ďalší

Zdroj: Mathematics (2227-7390); Nov2025, Vol. 13 Issue 22, p3705, 21p

Predmety: WIND power plants, DETECTION algorithms, REAL-time computing, FREQUENCIES of oscillating systems, COMPUTATIONAL learning theory, FRACTIONAL calculus

Learning Time-Scales in Two-Layers Neural Networks.

Autori: Berthier, Raphaël Montanari, Andrea Zhou, Kangjie

Zdroj: Foundations of Computational Mathematics; Oct2025, Vol. 25 Issue 5, p1627-1710, 84p

Predmety: ARTIFICIAL neural networks, DYNAMICAL systems, BACK propagation, CONTINUOUS time models, COMPUTATIONAL learning theory

Machine learning approach to predict the dot gain of flexographic prints.

Autori: Basak, Soumen P. C., Saritha Maity, Alenrex a ďalší

Zdroj: Acta Graphica; Apr2025, Vol. 33 Issue 1, p34-43, 10p

Predmety: COMPUTATIONAL learning theory, SUPERVISED learning, MACHINE learning, RANDOM forest algorithms, DECISION trees

From computational to data-driven strategies for single-atom catalysis

Autori: Ruiz Ferrando, Andrea

Prispievatelia: University/Department: Universitat Rovira i Virgili. Departament de Química Física i Inorgànica

Thesis Advisors: López Alonso, Núria

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Modelatge, Catàlisi single-atom, Impulsat per dades, Modelaje, Catálisis single-atom, Impulsado por datos, Modelling, Single-atom catalysis, Data-driven, Ciències

Time: 538.9

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/692335

A note on different covering numbers in learning theory: A note on different covering numbers in learning theory.

Autori: Massimiliano Pontil

Zdroj: Journal of Complexity. 19:665-671

Predmety: Statistics and Probability, Numerical Analysis, Algebra and Number Theory, Control and Optimization, Applied Mathematics, Computational learning theory, 0101 mathematics, 01 natural sciences

Popis súboru: application/xml

Prístupová URL adresa: https://zbmath.org/2056485
https://doi.org/10.1016/s0885-064x(03)00033-5
https://www.sciencedirect.com/science/article/abs/pii/S0885064X03000335
https://doi.org/10.1016/S0885-064X(03)00033-5
https://dblp.uni-trier.de/db/journals/jc/jc19.html#Pontil03
https://www.sciencedirect.com/science/article/pii/S0885064X03000335