LEADER 03290nam 22007335 450 001 996655263503316 005 20251204162508.0 010 $a3-031-85160-9 024 7 $a10.1007/978-3-031-85160-5 035 $a(CKB)38496453200041 035 $a(DE-He213)978-3-031-85160-5 035 $a(MiAaPQ)EBC32006609 035 $a(Au-PeEL)EBL32006609 035 $a(OCoLC)1523376299 035 $a(PPN)284780081 035 $a(EXLCZ)9938496453200041 100 $a20250411d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Optimal Transport $eÉcole d'Été de Probabilités de Saint-Flour XLIX ? 2019 /$fby Sinho Chewi, Jonathan Niles-Weed, Philippe Rigollet 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (XIV, 260 p. 10 illus., 3 illus. in color.) 225 1 $aÉcole d'Été de Probabilités de Saint-Flour ;$v2364 311 08$a3-031-85159-5 327 $a1. Optimal Transport -- 2. Estimation of Wasserstein distances -- 3. Estimation of transport maps -- 4. Entropic optimal transport -- 5. Wasserstein gradient flows: theory.-6. Wasserstein gradient flows: applications -- 7. Metric geometry of the Wasserstein space -- 8. Wasserstein barycenters. 330 $aThis monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. It is primarily tailored for students and researchers in these fields, yet it remains accessible to a broader audience of applied mathematicians and computer scientists. Each chapter is complemented with exercises for the reader to test their understanding. As such, this monograph is suitable for a graduate course on the topic of statistical optimal transport. 410 0$aÉcole d'Été de Probabilités de Saint-Flour ;$v2364 606 $aStatistics 606 $aMachine learning 606 $aMathematical optimization 606 $aCalculus of variations 606 $aStatistical physics 606 $aProbabilities 606 $aStatistical Theory and Methods 606 $aMachine Learning 606 $aCalculus of Variations and Optimization 606 $aStatistical Physics 606 $aProbability Theory 615 0$aStatistics. 615 0$aMachine learning. 615 0$aMathematical optimization. 615 0$aCalculus of variations. 615 0$aStatistical physics. 615 0$aProbabilities. 615 14$aStatistical Theory and Methods. 615 24$aMachine Learning. 615 24$aCalculus of Variations and Optimization. 615 24$aStatistical Physics. 615 24$aProbability Theory. 676 $a519.5 700 $aChewi$b Sinho$4aut$4http://id.loc.gov/vocabulary/relators/aut$01816819 702 $aNiles-Weed$b Jonathan$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aRigollet$b Philippe$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996655263503316 996 $aStatistical Optimal Transport$94373637 997 $aUNISA