LEADER 00000cgm a2200505 i 4500 
003    OCoLC 
005    20240129213017.0 
006    m     o  c         
007    cr cna|||||||| 
007    vz czazuu 
008    200724s2019    xx 051        o   vleng d 
029 1  AU@|b000071521927 
035    (OCoLC)1177143690 
037    CL0501000125|bSafari Books Online 
040    UMI|beng|erda|epn|cUMI|dOCLCF|dOCLCQ|dOCLCO 
049    INap 
099    Streaming Video O’Reilly for Public Libraries 
100 1  Weber, Mark,|eon-screen presenter. 
245 10 Fighting crime with graph learning /|cMark Weber.
       |h[O'Reilly electronic resource] 
264  1 [Place of publication not identified] :|bO'Reilly Media,
       |c2019. 
300    1 online resource (1 streaming video file (50 min., 57 
       sec.)) 
336    two-dimensional moving image|btdi|2rdacontent 
337    computer|bc|2rdamedia 
337    video|bv|2rdamedia 
338    online resource|bcr|2rdacarrier 
500    Title from title screen (viewed July 23, 2020). 
511 0  Presenter, Mark Weber. 
520    "Despite tremendous resources dedicated to anti-money 
       laundering (AML), only a tiny fraction of illicit activity
       is prevented. The research community can help. Mark Weber 
       (MIT-IBM Watson AI Lab) explores how to map the structural
       and behavioral dynamics driving the technical challenge, 
       and he reviews AML methods both current and emergent. 
       You'll get a first look at scalable graph convolutional 
       neural networks for forensic analysis of financial data, 
       which is massive, dense, and dynamic. Mark outlines 
       preliminary experimental results using a large synthetic 
       graph (1M nodes, 9M edges) generated by a data simulator 
       called AMLSim, and he considers opportunities for high 
       performance efficiency, in terms of computation and memory,
       and shares results from a simple graph compression 
       experiment, all of which supports the working hypothesis 
       that graph deep learning for AML bears great promise in 
       the fight against criminal financial activity. This 
       session is from the 2019 O'Reilly Artificial Intelligence 
       Conference in San Jose, CA."--Resource description page 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
611 20 O'Reilly Artificial Intelligence Conference|d(2019 :|cSan 
       Jose, Calif.) 
650  0 Graph theory|xData processing. 
650  0 Neural networks (Computer science) 
650  0 Criminal statistics|xData processing. 
650  0 Money laundering investigation. 
650  2 Neural Networks, Computer 
650  6 Réseaux neuronaux (Informatique) 
650  6 Statistiques criminelles|xInformatique. 
650  6 Blanchiment de l'argent|xEnquêtes. 
650  7 Criminal statistics|xData processing|2fast
       |0(OCoLC)fst00883502 
650  7 Graph theory|xData processing|2fast|0(OCoLC)fst00946587 
650  7 Money laundering investigation|2fast|0(OCoLC)fst01025325 
650  7 Neural networks (Computer science)|2fast
       |0(OCoLC)fst01036260 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/videos/~/0636920371205/?ar|zAvailable
       for O'Reilly for Public Libraries 
994    92|bJFN