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High-Dimensional Optimization and Probability [[electronic resource] ] : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias
| High-Dimensional Optimization and Probability [[electronic resource] ] : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (417 pages) |
| Disciplina | 519.3 |
| Collana | Springer Optimization and Its Applications |
| Soggetto topico |
Mathematical optimization
Probabilities Business information services Mathematics Optimization Applied Probability IT in Business Applications of Mathematics Optimització matemàtica Probabilitats |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-00832-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Projection of a point onto a convex set via Charged Balls Method (E. Abbasov ) -- Towards optimal sampling for learning sparse approximations in high dimensions (Adcock) -- Recent Theoretical Advances in Non-Convex Optimization (Gasnikov) -- Higher Order Embeddings for the Composition of the Harmonic Projection and Homotopy Operators (Ding) -- Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming (M.V. Dolgopolik) -- On the Expected Extinction Time for the Adjoint Circuit Chains associated with a Random Walk with Jumps in Random Environments (Ganatsiou) -- A statistical learning theory approach for the analysis of the trade-off between sample size and precision in truncated ordinary least squares (Raciti) -- Recent theoretical advances in decentralized distributed convex optimization (Gasnikov) -- On training set selection in spatial deep learning (M.T. Hendrix) -- Surrogate-Based Reduced Dimension Global Optimization in Process Systems Engineering (Xiang Li) -- A viscosity iterative method with alternated inertial terms for solving the split feasibility problem (Rassias) -- Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques (Aboushelbaya) -- Nonsmooth Mathematical Programs with Vanishing Constraints in Banach Spaces (Singh). |
| Record Nr. | UNISA-996485662403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
High-Dimensional Optimization and Probability : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias
| High-Dimensional Optimization and Probability : With a View Towards Data Science / / edited by Ashkan Nikeghbali, Panos M. Pardalos, Andrei M. Raigorodskii, Michael Th. Rassias |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (417 pages) |
| Disciplina | 519.3 |
| Collana | Springer Optimization and Its Applications |
| Soggetto topico |
Mathematical optimization
Probabilities Business information services Mathematics Optimization Applied Probability IT in Business Applications of Mathematics Optimització matemàtica Probabilitats |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-00832-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Projection of a point onto a convex set via Charged Balls Method (E. Abbasov ) -- Towards optimal sampling for learning sparse approximations in high dimensions (Adcock) -- Recent Theoretical Advances in Non-Convex Optimization (Gasnikov) -- Higher Order Embeddings for the Composition of the Harmonic Projection and Homotopy Operators (Ding) -- Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming (M.V. Dolgopolik) -- On the Expected Extinction Time for the Adjoint Circuit Chains associated with a Random Walk with Jumps in Random Environments (Ganatsiou) -- A statistical learning theory approach for the analysis of the trade-off between sample size and precision in truncated ordinary least squares (Raciti) -- Recent theoretical advances in decentralized distributed convex optimization (Gasnikov) -- On training set selection in spatial deep learning (M.T. Hendrix) -- Surrogate-Based Reduced Dimension Global Optimization in Process Systems Engineering (Xiang Li) -- A viscosity iterative method with alternated inertial terms for solving the split feasibility problem (Rassias) -- Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques (Aboushelbaya) -- Nonsmooth Mathematical Programs with Vanishing Constraints in Banach Spaces (Singh). |
| Record Nr. | UNINA-9910586596903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||