LEADER 03028nam 22005295 450 001 996418261803316 005 20200703145346.0 010 $a3-030-39568-5 024 7 $a10.1007/978-3-030-39568-1 035 $a(CKB)4100000011232681 035 $a(DE-He213)978-3-030-39568-1 035 $a(MiAaPQ)EBC6199805 035 $a(PPN)248396307 035 $a(EXLCZ)994100000011232681 100 $a20200515d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFirst-order and Stochastic Optimization Methods for Machine Learning$b[electronic resource] /$fby Guanghui Lan 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XIII, 582 p. 18 illus., 16 illus. in color.) 225 1 $aSpringer Series in the Data Sciences,$x2365-5674 311 $a3-030-39567-7 320 $aIncludes bibliographical references and index. 327 $aMachine Learning Models -- Convex Optimization Theory -- Deterministic Convex Optimization -- Stochastic Convex Optimization -- Convex Finite-sum and Distributed Optimization -- Nonconvex Optimization -- Projection-free Methods -- Operator Sliding and Decentralized Optimization. 330 $aThis book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning. 410 0$aSpringer Series in the Data Sciences,$x2365-5674 606 $aMathematical optimization 606 $aMachine learning 606 $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 615 0$aMathematical optimization. 615 0$aMachine learning. 615 14$aOptimization. 615 24$aMachine Learning. 676 $a519.6 700 $aLan$b Guanghui$4aut$4http://id.loc.gov/vocabulary/relators/aut$01017962 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418261803316 996 $aFirst-order and Stochastic Optimization Methods for Machine Learning$92391161 997 $aUNISA