000 01709cam a22002538i 4500
005 20220518154754.0
008 160921s2017 enk b 001 0 eng
020 _a9781107154889
041 _aeng
082 0 0 _a519.2
_bMIT
100 1 _aMitzenmacher, Michael,
_92581
245 1 0 _aProbability and computing /
_cMichael Mitzenmacher Eli Upfal.
250 _aSecond edition.
300 _apages cm
520 _a"Greatly expanded, this new edition requires only an elementary background in discrete mathematics and offers a comprehensive introduction to the role of randomization and probabilistic techniques in modern computer science. Newly added chapters and sections cover topics including normal distributions, sample complexity, VC dimension, Rademacher complexity, power laws and related distributions, cuckoo hashing, and the Lovasz Local Lemma. Material relevant to machine learning and big data analysis enables students to learn modern techniques and applications. Among the many new exercises and examples are programming-related exercises that provide students with excellent training in solving relevant problems. This book provides an indispensable teaching tool to accompany a one- or two-semester course for advanced undergraduate students in computer science and applied mathematics"--
650 0 _aAlgorithms.
_92969
650 0 _aProbabilities.
_92970
650 0 _aStochastic analysis.
_92584
700 1 _aUpfal, Eli,
_92585
856 4 2 _uhttps://www.loc.gov/catdir/enhancements/fy1618/2016041654-b.html
856 4 2 _uhttps://www.loc.gov/catdir/enhancements/fy1618/2016041654-d.html
856 4 1 _uhttps://www.loc.gov/catdir/enhancements/fy1618/2016041654-t.html
942 _cBK
999 _c241742
_d241742