LEADER 02655nam 22005175 450 001 9910896193803321 005 20241008130240.0 010 $a3-031-65820-5 024 7 $a10.1007/978-3-031-65820-4 035 $a(CKB)36315667800041 035 $a(MiAaPQ)EBC31713218 035 $a(Au-PeEL)EBL31713218 035 $a(DE-He213)978-3-031-65820-4 035 $a(EXLCZ)9936315667800041 100 $a20241008d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiscrete Stochastic Processes $eTools for Machine Learning and Data Science /$fby Nicolas Privault 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (294 pages) 225 1 $aSpringer Undergraduate Mathematics Series,$x2197-4144 311 $a3-031-65819-1 327 $a- 1. A Summary of Markov Chains -- 2. Phase-Type Distributions -- 3. Synchronizing Automata -- 4. Random Walks and Recurrence -- 5. Cookie-Excited Random Walks -- 6. Convergence to Equilibrium -- 7. The Ising Model -- 8. Search Engines -- 9. Hidden Markov Model -- 10. Markov Decision Processes. 330 $aThis text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phase-type distributions, applications to search engines and probabilistic automata, and an introduction to the Ising model used in statistical physics. Applications to data science are also considered via hidden Markov models and Markov decision processes. A total of 32 exercises and 17 longer problems are provided with detailed solutions and cover various topics of interest, including statistical learning. 410 0$aSpringer Undergraduate Mathematics Series,$x2197-4144 606 $aStochastic processes 606 $aComputer science$xMathematics 606 $aStochastic Processes 606 $aMathematical Applications in Computer Science 615 0$aStochastic processes. 615 0$aComputer science$xMathematics. 615 14$aStochastic Processes. 615 24$aMathematical Applications in Computer Science. 676 $a006.310727 700 $aPrivault$b Nicolas$0475313 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910896193803321 996 $aDiscrete Stochastic Processes$94212338 997 $aUNINA