Výsledky vyhľadávania - approximate statistics ((dynamic OR dynamika) OR dynamik) programming algorithm*

Establishment and Solution of a Multi-Stage Decision Model Based on Hypothesis Testing and Dynamic Programming Algorithm

Autori: Liu, Ziyang Hu, Yurui Deng, Yihan

Zdroj: 2024 International Conference on Internet of Things, Robotics and Distributed Computing (ICIRDC). :884-889

Predmety: FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, Applications (stat.AP), Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Statistics - Applications

Prístupová URL adresa: http://arxiv.org/abs/2503.05807

Constrained many-to-many point matching in two dimensions

Autori: L.E. Caraballo R. A. Castro José Miguel Díaz-Báñez a ďalší

Prispievatelia: L.E. Caraballo R. A. Castro José Miguel Díaz-Báñez a ďalší

Zdroj: idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)

Predmety: Combinatorics on Words, Linguistics and Language, Artificial intelligence, Automata Theory and Formal Languages, Approximate Matching, Social Sciences, Geometry, 0102 computer and information sciences, 02 engineering and technology, Dynamic programming, 7. Clean energy, 01 natural sciences, Point (geometry), Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Computational intelligence, Melodic similarity, Text Compression and Indexing Algorithms, 4. Education, Statistics, Geometric measure, 16. Peace & justice, Computer science, Computational Theory and Mathematics, Computer Science, Physical Sciences, Matching (statistics), String Matching, Many-to-many matching, Translanguaging Pedagogy in Multilingual Education, Mathematics

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/11441/155627
https://idus.us.es/handle//11441/155627

Real-Time Scheduling Optimization of Integrated Energy Systems in Smart Grids based on Approximate Dynamic Programming

Autori: Dongzhao Wang Yue Sun Yan Wu a ďalší

Zdroj: Statistics, Optimization & Information Computing. 13:158-172

Modeling Dynamic Regime Shifts in Diffusion Processes: Approximate Maximum Likelihood Estimation for Two-Threshold Ornstein–Uhlenbeck Models.

Autori: Bekesiene, Svajone Nikitin, Anatolii Nechyporuk, Serhii

Zdroj: Mathematics (2227-7390). Nov2025, Vol. 13 Issue 21, p3450. 18p.

Predmety: *ORNSTEIN-Uhlenbeck process, *PARAMETER estimation, *STOCHASTIC processes, *PARAMETERIZATION, *DIFFUSION kinetics, *STOCHASTIC models, *ITERATIVE methods (Mathematics), *MAXIMUM likelihood statistics

A fully adaptive framework for continuous-state stochastic dynamic programming.

Autori: Fan, Huiyuan Tarun, Prashant K. Viswanatha, Amith a ďalší

Zdroj: Computers & Operations Research. Nov2025, Vol. 183, pN.PAG-N.PAG. 1p.

Predmety: *DYNAMIC programming, *STATISTICS, STATISTICAL models, SPACE exploration, COMPUTER engineering

An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application

Autori: Simão, Hugo P. Day, Jeff George, Abraham P. a ďalší

Zdroj: Transportation Science, 2009 May 01. 43(2), 178-197.

Prístupová URL adresa: https://www.jstor.org/stable/25769444

Online multivariate changepoint detection: leveraging links with computational geometry

Autori: Pishchagina, Liudmila Romano, Gaetano Fearnhead, Paul a ďalší

Prispievatelia: Pishchagina, Liudmila Romano, Gaetano Fearnhead, Paul a ďalší

Zdroj: Journal of the Royal Statistical Society Series B: Statistical Methodology.

Predmety: dynamic programming, FOS: Computer and information sciences, online changepoint detection, Computation, computational geometry, convex hull, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Computation (stat.CO)

Popis súboru: text

Prístupová URL adresa: http://arxiv.org/abs/2311.01174
https://hal.inrae.fr/hal-05239757v1
https://doi.org/10.1093/jrsssb/qkaf046
https://eprints.lancs.ac.uk/id/eprint/209818/

Deep Neural Networks Algorithms for Stochastic Control Problems on Finite Horizon: Convergence Analysis

Autori: Côme Huré Huyên Pham Achref Bachouch a ďalší

Prispievatelia: Côme Huré Huyên Pham Achref Bachouch a ďalší

Zdroj: SIAM Journal on Numerical Analysis. 59:525-557

Predmety: dynamic programming, FOS: Computer and information sciences, 90C39, [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Probability (math.PR), statistical risk AMS subject classifications. 65C05, Deep learning, [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC], Machine Learning (stat.ML), performance iteration, 93E35, 01 natural sciences, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], convergence analysis, Statistics - Machine Learning, Optimization and Control (math.OC), FOS: Mathematics, regress now, quantization, 0101 mathematics, Mathematics - Optimization and Control, 65C05, 90C39, 93E35, 68T07, Mathematics - Probability

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/pdf/1812.04300
http://arxiv.org/abs/1812.04300
https://arxiv.org/pdf/1812.04300.pdf
https://ui.adsabs.harvard.edu/abs/2018arXiv181204300H/abstract
http://ui.adsabs.harvard.edu/abs/2018arXiv181204300H/abstract
https://arxiv.org/abs/1812.04300
https://dblp.uni-trier.de/db/journals/siamnum/siamnum59.html#HurePBL21
https://hal.archives-ouvertes.fr/hal-01949213/document
https://hal.archives-ouvertes.fr/hal-01949213v2
https://epubs.siam.org/doi/abs/10.1137/20M1316640
https://hal.science/hal-01949213v2
https://hal.science/hal-01949213v2/document
https://doi.org/10.1137/20m1316640

Exact and rapid linear clustering of networks with dynamic programming

Autori: Alice Patania Antoine Allard Jean-Gabriel Young

Zdroj: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 479

Predmety: Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Data Structures and Algorithms, 0103 physical sciences, Computer Science - Social and Information Networks, Data Structures and Algorithms (cs.DS), Statistics - Computation, 01 natural sciences, Computation (stat.CO), Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2301.10403

EFFICIENT NEURAL NETWORK APPROACHES FOR CONDITIONAL OPTIMAL TRANSPORT WITH APPLICATIONS IN BAYESIAN INFERENCE.

Autori: ZHEYU OLIVER WANG BAPTISTA, RICARDO MARZOUK, YOUSSEF a ďalší

Zdroj: SIAM Journal on Scientific Computing. 2025, Vol. 47 Issue 4, pC979-C1005. 27p.

Predmety: *ARTIFICIAL neural networks, *BAYESIAN field theory, *DYNAMIC programming, *STATISTICAL sampling, *MATHEMATICAL optimization, *NUMERICAL analysis, *MAXIMUM likelihood statistics

State abstraction discovery from progressive disaggregation methods

Autori: Forghieri, Orso Castel, Hind Hyon, Emmanuel a ďalší

Prispievatelia: Forghieri, Orso Castel, Hind Hyon, Emmanuel a ďalší

Zdroj: EWLR 2024: 17th European Workshop on Reinforcement Learning ; 17th European Workshop on Reinforcement Learning (EWLR) ; https://hal.science/hal-05004125 ; 17th European Workshop on Reinforcement Learning (EWLR), Oct 2024, Toulouse, France

Predmety: Markov decision Processes, Reinforcement Learning, State abstraction, Approximate Dynamic Programming, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Geografické téma: Toulouse, France

Dostupnosť: https://hal.science/hal-05004125
https://hal.science/hal-05004125v1/document
https://hal.science/hal-05004125v1/file/56_State_Abstraction_Discovery.pdf

Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees.

Autori: Zeng, Siliang Hong, Mingyi Garcia, Alfredo

Zdroj: Operations Research. Mar/Apr2025, Vol. 73 Issue 2, p720-737. 18p.

Predmety: *DISCRETE choice models, *COMPUTER programming, *MARKOV processes, MAXIMUM likelihood statistics, REINFORCEMENT learning

Dynamic programming based optimized product quantization for approximate nearest neighbor search.

Autori: Cai, Yuanzheng Ji, Rongrong Li, Shaozi

Zdroj: Neurocomputing. Dec2016, Vol. 217, p110-118. 9p.

Predmety: *DYNAMIC programming, *NEAREST neighbor analysis (Statistics), *SUBSPACES (Mathematics), *ALGORITHMS, *GRAPH theory

A NONPARAMETRIC ROBUST OPTIMIZATION APPROACH FOR CHANCE-CONSTRAINED KNAPSACK PROBLEM.

Autori: XU, LIANG ZHANG, CHAO XU, ZHOU a ďalší

Zdroj: SIAM Journal on Optimization. 2025, Vol. 35 Issue 2, p739-766. 28p.

Predmety: *ROBUST optimization, *KNAPSACK problems, *RANDOM sets, *DYNAMIC programming, *OPTIMIZATION algorithms, *NONPARAMETRIC statistics, *STOCHASTIC programming, *COMBINATORIAL optimization

Equilibria of large random Lotka-Volterra systems with vanishing species: a mathematical approach.

Autori: Akjouj I Hachem W Maïda M a ďalší

Zdroj: Journal of mathematical biology [J Math Biol] 2024 Nov 07; Vol. 89 (6), pp. 61. Date of Electronic Publication: 2024 Nov 07.

Spôsob vydávania: Journal Article

Informácie o časopise: Publisher: Springer Verlag Country of Publication: Germany NLM ID: 7502105 Publication Model: Electronic Cited Medium: Internet ISSN: 1432-1416 (Electronic) Linking ISSN: 03036812 NLM ISO Abbreviation: J Math Biol Subsets: MEDLINE

Výrazy zo slovníka MeSH: Algorithms* , Mathematical Concepts* , Ecosystem* , Models, Biological* , Population Dynamics*/statistics & numerical data, Animals ; Linear Models ; Computer Simulation ; Models, Statistical

Estimation of High-Dimensional Contextual Pricing Models with Nonparametric Price Confounders.

Autori: Wang, Yining Liu, Quanquan

Zdroj: Operations Research. Nov/Dec2025, Vol. 73 Issue 6, p3065-3084. 20p.

Predmety: *ECONOMIC demand, *TIME-based pricing, *REVENUE management, INSTRUMENTAL variables (Statistics), SAMPLING errors, FEATURE selection

Efficient approximate algorithms for a class of dynamic lot size problems under product substitution.

Autori: Huang, Shanming Xue, Feng Yang, Wanshuo

Zdroj: Journal of Industrial & Management Optimization. Jan2024, Vol. 20 Issue 1, p1-24. 24p.

Predmety: *DYNAMIC programming, *ALGORITHMS, *PROBLEM solving, POLYNOMIAL time algorithms, BIPARTITE graphs

An Approximate Dynamic Programming Approach to Adversarial Online Learning

Autori: Kamble, Vijay Loiseau, Patrick Walrand, Jean

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computer Science and Game Theory, Statistics - Machine Learning, Computer Science - Data Structures and Algorithms, 0502 economics and business, 05 social sciences, Data Structures and Algorithms (cs.DS), Machine Learning (stat.ML), 0102 computer and information sciences, 01 natural sciences, Computer Science and Game Theory (cs.GT), Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/1603.04981

Good Prophets Know When the End Is Near.

Autori: Banerjee, Siddhartha Freund, Daniel

Zdroj: Management Science. Jun2025, Vol. 71 Issue 6, p4877-4894. 18p.

Predmety: *BIN packing problem, *MATHEMATICAL optimization, *STOCHASTIC processes, PREDICTIVE control systems, LOSS functions (Statistics)

Enhancing Hydrological Model Performance Through Clustering of Dynamic Catchment Characteristics and Parameter Discretization.

Autori: Wang, Xiao Lan, Tian Zhang, Hongbo a ďalší

Zdroj: Water Resources Research; Oct2025, Vol. 61 Issue 10, p1-28, 28p

Predmety: HYDROLOGIC models, DISCRETIZATION methods, WATERSHEDS, RUNOFF models, CALIBRATION, DATA mining, WATER management