LEADER 03698oam 2200685I 450 001 9910785791603321 005 20200520144314.0 010 $a1-136-26639-9 010 $a1-283-58611-8 010 $a9786613898562 010 $a0-203-10856-6 010 $a1-136-26640-2 024 7 $a10.4324/9780203108567 035 $a(CKB)2670000000237973 035 $a(EBL)1016136 035 $a(OCoLC)809537724 035 $a(SSID)ssj0000704978 035 $a(PQKBManifestationID)12268920 035 $a(PQKBTitleCode)TC0000704978 035 $a(PQKBWorkID)10620781 035 $a(PQKB)10842557 035 $a(Au-PeEL)EBL1016136 035 $a(CaPaEBR)ebr10596269 035 $a(CaONFJC)MIL389856 035 $a(FINmELB)ELB133786 035 $a(MiAaPQ)EBC1016136 035 $a(PPN)198457219 035 $a(EXLCZ)992670000000237973 100 $a20180706d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFoucault and the politics of hearing /$fLauri Siisiainen 210 1$aLondon ;$aNew York :$cRoutledge,$d2013. 215 $a1 online resource (163 p.) 225 1 $aInterventions 300 $aDescription based upon print version of record. 311 $a1-138-85130-2 311 $a0-415-51926-8 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Copyright Page; Table of Contents; Acknowledgments; Introduction; 1 The archaeology of our ears; Murmur, madness, and language; The order of discourse and anonymous voice; The Birth of the Clinic and the exclusion of the "auditory-sonorous"; "Message or Noise?"; Confession and voice in Foucault's early encounter with Jean-Jacques Rousseau; Metamorphoses of the ear: Renaissance, Classicism, modernity; From anonymous murmur to vocal knowledge and power; 2 The genealogy of auditory-sonorous power and resistance; Surveillance and discipline: panoptic or panauditory power? 327 $aPanauditory surveillance and its fragility: "A King Listens"Sexuality, confession, and the sensualization of power; Multitudes and noise-abatement; The liberal governmentality, homo ?conomicus, and the threat of noise; 3 Voices of care, friendship, and parre?sia; Care of the self and the interior voice; Education, sonorous power, and the struggle of voices; The musical event: Foucault and Boulez; Music and the politics of friendship; Parre?sia and the voice of the crowd: auditory-sonorous politics in the final Colle?ge de France lectures; Conclusion: historicizing and politicizing our ears 327 $aNotesReferences; Index 330 $aThe issue of the senses and sensual perception in Michel Foucault's thought has been a source of prolific discussion already for quite some time. Often, Foucault has been accused of overemphasizing the centrality of sight, and has been portrayed as yet another thinker representative of Western ocularcentricism. This innovative new work seeks to challenge this portrait by presenting an alternative view of Foucault as a thinker for whom the sound, voice, hearing, and listening, the auditory-sonorous, actually did matter.Illus 410 0$aInterventions (Routledge (Firm)) 517 3 $aFoucault & the politics of hearing 606 $aPolitical psychology 606 $aHearing$xPolitical aspects 615 0$aPolitical psychology. 615 0$aHearing$xPolitical aspects. 676 $a320.01/9 700 $aSiisiainen$b Lauri.$01506586 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910785791603321 996 $aFoucault and the politics of hearing$93736877 997 $aUNINA LEADER 03854nam 22006495 450 001 9910300747503321 005 20200703082830.0 010 $a9781484235911 010 $a1484235916 024 7 $a10.1007/978-1-4842-3591-1 035 $a(CKB)4100000003359121 035 $a(MiAaPQ)EBC5356209 035 $a(DE-He213)978-1-4842-3591-1 035 $a(CaSebORM)9781484235911 035 $a(PPN)226699471 035 $a(OCoLC)1037100034 035 $a(OCoLC)on1037100034 035 $a(EXLCZ)994100000003359121 100 $a20180423d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Belief Nets in C++ and CUDA C: Volume 1 $eRestricted Boltzmann Machines and Supervised Feedforward Networks /$fby Timothy Masters 205 $a1st ed. 2018. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2018. 215 $a1 online resource (225 pages) $cillustrations 300 $aIncludes index. 311 08$a9781484235904 311 08$a1484235908 327 $a1. Introduction -- 2. Supervised Feedforward Networks -- 3. Restricted Boltzmann Machines -- 4. Greedy Training: Generative Samplings -- 5. DEEP Operating Manual. 330 $aDiscover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. The first of three in a series on C++ and CUDA C deep learning and belief nets, Deep Belief Nets in C++ and CUDA C: Volume 1 shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. As such, you?ll see that a typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. All the routines and algorithms presented in the book are available in the code download, which also contains some libraries of related routines. You will: Employ deep learning using C++ and CUDA C Work with supervised feedforward networks Implement restricted Boltzmann machines Use generative samplings Discover why these are important. 517 3 $aRestricted Boltzmann machines and supervised feedforward networks 517 3 $aDeep Belief Nets in C plus plus and CUDA C 606 $aArtificial intelligence 606 $aProgramming languages (Electronic computers) 606 $aBig data 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037 606 $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120 606 $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070 615 0$aArtificial intelligence. 615 0$aProgramming languages (Electronic computers) 615 0$aBig data. 615 14$aArtificial Intelligence. 615 24$aProgramming Languages, Compilers, Interpreters. 615 24$aBig Data. 615 24$aBig Data/Analytics. 676 $a006.32 700 $aMasters$b Timothy$4aut$4http://id.loc.gov/vocabulary/relators/aut$0105163 801 0$bUMI 801 1$bUMI 906 $aBOOK 912 $a9910300747503321 996 $aDeep Belief Nets in C++ and CUDA C: Volume 1$92497770 997 $aUNINA