01916nam0 2200421 i 450 VAN013284920230621114529.677N978331903257320210329d2014 |0itac50 baengCH|||| |||||Heavy Neutral Particle Decays to Tau PairsDetected with CMS in Proton Collisions at \sqrt{s}7TeVDoctoral Thesis accepted by University of Wisconsin–Madison, USAMichail BachtisChamSpringer2014xvi, 152 p.ill.24 cm001VAN01041932001 Springer thesesrecognizing outstanding Ph.D. research210 BerlinSpringer2010-VAN0134825Heavy Neutral Particle Decays to Tau Pairs177039581-XXQuantum theory [MSC 2020]VANC019967MF81V35Nuclear physics [MSC 2020]VANC023270MFHiggs Boson Measurement at CMSKW:KMSSMKW:KMinimal Supersymmetric Standard SodelKW:KPrize Winning ThesisKW:KTau DecaysKW:KTau IdentificationKW:KZ Decay to Tau LeptonKW:KZ Tau Cross SectionKW:KCHChamVANL001889BachtisMichailVANV106687791793Springer <editore>VANV108073650ITSOL20240614RICAhttp://doi.org/10.1007/978-3-319-03257-3E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN0132849BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08CONS e-book 2027 08eMF2027 20210329 Heavy Neutral Particle Decays to Tau Pairs1770395UNICAMPANIA03794nam 22007695 450 991083101510332120250527153253.09789819982776981998277410.1007/978-981-99-8277-6(MiAaPQ)EBC31097978(Au-PeEL)EBL31097978(CKB)30165811500041(DE-He213)978-981-99-8277-6(EXLCZ)993016581150004120240131d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierStochastic Approximation: A Dynamical Systems Viewpoint /by Vivek S. Borkar2nd ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (280 pages)Texts and Readings in Mathematics,2366-8725 ;48Print version: Borkar, Vivek S. Stochastic Approximation: a Dynamical Systems Viewpoint Singapore : Springer,c2024 9789819982769 Includes bibliographical references and index.1. Introduction -- 2. Convergence Analysis -- 3. Finite Time Bounds and Traps -- 4. Stability Criteria -- 5. Stochastic Recursive Inclusions -- 6. Asynchronous Schemes -- 7. A Limit Theorem for Fluctuations -- 8. Multiple Timescales -- 9. Constant Stepsize Algorithms -- 10. General Noise Models -- 11. Stochastic Gradient Schemes -- 12. Liapunov and Related Systems -- 13. Appendix A: Topics in Analysis -- 14. Appendix B: Ordinary Differential Equations -- 15. Appendix C: Topics in Probability -- Bibliography -- Index. .This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.Texts and Readings in Mathematics,2366-8725 ;48StatisticsArtificial intelligenceProbabilitiesOperations researchGame theoryAutomatic controlStatistical Theory and MethodsArtificial IntelligenceProbability TheoryOperations Research and Decision TheoryGame TheoryControl and Systems TheoryAnàlisi estocàsticathubLlibres electrònicsthubStatistics.Artificial intelligence.Probabilities.Operations research.Game theory.Automatic control.Statistical Theory and Methods.Artificial Intelligence.Probability Theory.Operations Research and Decision Theory.Game Theory.Control and Systems Theory.Anàlisi estocàstica519.2Borkar Vivek S.472615MiAaPQMiAaPQMiAaPQBOOK9910831015103321Stochastic approximation225441UNINA