LEADER 00932nam0-22003011i-450- 001 990006164990403321 005 19980601 035 $a000616499 035 $aFED01000616499 035 $a(Aleph)000616499FED01 035 $a000616499 100 $a19980601d1957----km-y0itay50------ba 105 $a--------00-yy 200 1 $a<>Demand and Supply of Scientific Personnel$fDavid M. Blank, George J. Stigler. 210 $aNew York$cNational Bureau of Economic Research$d1957 215 $aXIX,, 200 p.$d24 cm 225 1 $a"National Bureau of Economic Research"$v62 676 $a331.5 700 1$aBlank,$bDavid M.$0234000 702 1$aStigler,$bGeorge Joseph$f<1911-1991> 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990006164990403321 952 $aXV C 69 (62)$b66051$fFGBC 959 $aFGBC 996 $aDemand and Supply of Scientific Personnel$9644447 997 $aUNINA DB $aGIU01 LEADER 01154nam a2200289 i 4500 001 991001162259707536 008 050720s1997 nyua b 001 0 eng d 020 $a0471147664 035 $ab13329807-39ule_inst 040 $aDip.to Ingegneria dell'Innovazione$beng 082 0 $a511.322$220 245 00$aFuzzy information engineering :$ba guided tour of applications /$cedited by Didier Dubois, Henri Prade, and Ronald R. Yager 260 $aNew York :$bJohn Wiley e Sons,$c1997 300 $aviii, 712 p. :$bill. ;$c24 cm 500 $a"Wiley Computer Publishing." 504 $aIncludes bibliographical references and index 650 4$aInformation technology 650 4$aFuzzy sets 700 1 $aDubois, Didier 700 1 $aPrade, Henri M. 700 1 $aYager, Ronald R.,$d1941- 907 $a.b13329807$b09-02-07$c20-07-05 912 $a991001162259707536 945 $aLE026 511.322 DUB 01.01 1997$g1$i2026000018904$lle026$nProf. Pacella / Biblioteca$op$pE81.35$q-$rl$s- $t4$u2$v0$w2$x0$y.i14110258$z20-07-05 996 $aFuzzy information engineering$91105611 997 $aUNISALENTO 998 $ale026$b20-07-05$cm$da $e-$feng$gnyu$h0$i0 LEADER 03056uam 2200409 a 450 001 9910796406903321 005 20210111203515.0 010 $a1-119-48211-9 035 $a(CKB)3840000000340227 035 $a(CaSebORM)9781119482086 035 $a(MiAaPQ)EBC5240570 035 $a(BIP)060890092 035 $a(EXLCZ)993840000000340227 100 $a20230318d2018 uy 101 0 $aeng 135 $au||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Financial Machine Learning$b[electronic resource] /$fde Prado, Marcos 205 $a1st edition 210 1$cWiley,$d2018. 215 $a1 online resource (400 pages) 311 $a1-119-48208-9 327 $aMachine generated contents note: About the Author Preamble 1. Financial Machine Learning as a Distinct Subject Part 1: Data Analysis 2. Financial Data Structures 3. Labeling 4. Sample Weights 5. Fractionally Differentiated Features Part 2: Modelling 6. Ensemble Methods 7. Cross-validation in Finance 8. Feature Importance 9. Hyper-parameter Tuning with Cross-Validation Part 3: Backtesting 10. Bet Sizing 11. The Dangers of Backtesting 12. Backtesting through Cross-Validation 13. Backtesting on Synthetic Data 14. Backtest Statistics 15. Understanding Strategy Risk 16. Machine Learning Asset Allocation Part 4: Useful Financial Features 17. Structural Breaks 18. Entropy Features 19. Microstructural Features Part 5: High-Performance Computing Recipes 20. Multiprocessing and Vectorization 21. Brute Force and Quantum Computers 22. High-Performance Computational Intelligence and Forecasting Technologies Dr. Kesheng Wu and Dr. Horst Simon Index. 330 $aMachine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance. 610 $aFinance 610 $aMachine Learning 610 $aBusiness & Economics 610 $aComputers 676 $a332.0285/631 686 $aBUS036000$2bisacsh 700 $ade Prado$b Marcos$01544235 906 $aBOOK 912 $a9910796406903321 996 $aAdvances in Financial Machine Learning$93798306 997 $aUNINA LEADER 05341nam 2200685 a 450 001 9910830202703321 005 20230801225952.0 010 $a1-118-56288-7 010 $a1-283-94140-6 010 $a1-118-56293-3 035 $a(CKB)2670000000316641 035 $a(EBL)1106547 035 $a(OCoLC)823722212 035 $a(SSID)ssj0000804267 035 $a(PQKBManifestationID)11457990 035 $a(PQKBTitleCode)TC0000804267 035 $a(PQKBWorkID)10821734 035 $a(PQKB)10964835 035 $a(OCoLC)824081599 035 $a(MiAaPQ)EBC1106547 035 $a(EXLCZ)992670000000316641 100 $a20120208d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aX-rays and materials$b[electronic resource] /$fedited by Philippe Goudeau, Rene? Guinebretie?re 210 $aHoboken, N.J. $cISTE/Wiley$d2012 215 $a1 online resource (240 p.) 225 1 $aISTE 300 $aDescription based upon print version of record. 311 $a1-84821-342-5 320 $aIncludes bibliographical references and index. 327 $aCover; X-Rays and Materials; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1. Synchrotron Radiation: Instrumentation in Condensed Matter; 1.1. Introduction; 1.2. Light sources in the storage ring; 1.2.1. Bending magnets; 1.2.2. Insertion devices; 1.2.2.1. Wigglers; 1.2.2.2. Undulators; 1.3. Emittance and brilliance of a source; 1.4. X-ray diffraction with synchrotron radiation; 1.4.1. Angle-dispersive diffraction; 1.4.2. Energy dispersive diffraction; 1.5. X-ray absorption spectroscopy using synchrotron radiation; 1.5.1. X-ray absorption spectroscopy 327 $a1.5.2. Energy-scanned X-ray absorption spectroscopy1.5.3. Energy dispersive X-ray absorption spectroscopy; 1.6. SAMBA: the X-ray absorption spectroscopy beam line of SOLEIL for 4-40 keV; 1.7. The DIFFABS beam line; 1.7.1. Description of the beam line; 1.7.2. Examples of use of the DIFFABS beam line; 1.8. CRISTAL beam line; 1.8.1. Beam line optics; 1.8.2. Diffractometers; 1.8.3. Sample environments; 1.9. The SOLEIL ODE line for dispersive EXAFS; 1.9.1. Optics of the ODE line; 1.9.2. Magnetic circular dichroism 327 $a1.9.3. X-ray absorption spectroscopy under extreme pressure and/or temperature conditions1.10. Conclusion; 1.11. Bibliography; Chapter 2. Nanoparticle Characterization using Central X-ray Diffraction; 2.1. Introduction; 2.2. Definition of scattered intensity; 2.3. Invariance principle; 2.3.1. General case; 2.3.2. Isotropic systems; 2.3.3. Multi-level systems; 2.4. Behavior for large q: the Porod regime; 2.5. Particle-based systems; 2.5.1. Definition of form factor; 2.5.2. Introduction to the structure factor; 2.5.3. Intensity behavior at small q: the Guinier regime; 2.5.4. Volume measurements 327 $a2.5.5. Some well-known form factors2.5.6. Polyhedral particles; 2.5.6.1. Form factor of a polyhedron; 2.5.6.2. Comparison between different polyhedra with cylindrical and spherical forms; 2.6. An absolute scale for measuring particle numbers; 2.7. Conclusion; 2.8. Bibliography; Chapter 3. X-ray Diffraction for Structural Studies of Carbon Nanotubes and their Insertion Compounds; 3.1. Introduction; 3.1.1. Introduction to carbon nanotubes; 3.1.2. Uses of X-ray scattering for studies of carbon nanotubes; 3.2. Single-walled carbon nanotubes; 3.2.1. Calculation of a powder diffraction diagram 327 $a3.2.1.1. Individual nanotubes3.2.1.2. Bundle structure; 3.2.1.3. Inclusion of a distribution of nanotube diameters; 3.2.1.4. Effects of nanotube length; 3.2.2. Analysis of experimental scattering diagrams; 3.3. Multi-walled carbon nanotubes; 3.3.1. Calculation of powder diffraction diagrams for a powder of individual multi-walled nanotubes; 3.3.2. Analysis of an experimental diffraction diagram; 3.4. Hybrid nanotubes; 3.4.1. Peapods; 3.4.2. Ion insertion into nanotubes; 3.5. Textured powder samples; 3.5.1. Quantification of nanotube orientation 327 $a3.5.2. Separation of diffraction components in hybrid nanotubes 330 $aThis book presents reviews of various aspects of radiation/matter interactions, be these instrumental developments, the application of the study of the interaction of X-rays and materials to a particular scientific field, or specific methodological approaches. The overall aim of the book is to provide reference summaries for a range of specific subject areas within a pedagogical framework. Each chapter is written by an author who is well known within their field and who has delivered an invited lecture on their subject area as part of the "RX2009 - X-rays and Materials" colloqui 410 0$aISTE 606 $aMaterials$xAnalysis 606 $aX-ray microanalysis 606 $aX-rays$xDiffraction 606 $aX-ray spectroscopy 615 0$aMaterials$xAnalysis. 615 0$aX-ray microanalysis. 615 0$aX-rays$xDiffraction. 615 0$aX-ray spectroscopy. 676 $a620.11272 701 $aGoudeau$b Philippe$01699930 701 $aGuinebretie?re$b Rene?$0960291 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830202703321 996 $aX-rays and materials$94082559 997 $aUNINA