| 000 | 01753cam a22002658i 4500 | ||
|---|---|---|---|
| 005 | 20220518154638.0 | ||
| 008 | 160921s2017 enk b 001 0 eng | ||
| 020 | _a9780521835400 | ||
| 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. | ||
| 260 |
_aNw York: _bCambridge, _c2012 |
||
| 300 | _axvi,352p. | ||
| 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. _92582 |
|
| 650 | 0 |
_aProbabilities. _92583 |
|
| 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 |
_c241407 _d241407 |
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