| 000 | 01978nam a2200337 i 4500 | ||
|---|---|---|---|
| 001 | 19283649 | ||
| 003 | (BD-SpBAUS)1 | ||
| 005 | 20220923163608.0 | ||
| 008 | 220922s2017 enk b 001 0 eng | ||
| 010 | _a 2016041654 | ||
| 020 | _a9781107154889 | ||
| 040 |
_aDLC _beng _cDLC _erda _dDLC _dBD-SpBAUS |
||
| 042 | _apcc | ||
| 082 | 0 | 0 |
_a518.1 _223 _bMIP 2017 |
| 100 | 1 |
_aMitzenmacher, Michael, _d1969- _eauthor. _96 |
|
| 245 | 1 | 0 |
_aProbability and computing / _cMichael Mitzenmacher and Eli Upfal. |
| 250 | _aSecond edition. | ||
| 263 | _a1704 | ||
| 264 | 1 |
_aCambridge, United Kingdom ; _aNew York, NY, USA : _bCambridge University Press, _c[2017] |
|
| 300 |
_axx pages : _billustartions ; _c24 cm |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_aunmediated _bn _2rdamedia |
||
| 338 |
_avolume _bnc _2rdacarrier |
||
| 504 | _aIncludes bibliographical references and index. | ||
| 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"-- _cProvided by publisher. |
||
| 650 | 0 |
_aAlgorithms. _97 |
|
| 650 | 0 |
_aProbabilities. _98 |
|
| 650 | 0 |
_aStochastic analysis. _99 |
|
| 700 | 1 |
_aUpfal, Eli, _d1954- _eauthor. _910 |
|
| 942 |
_2ddc _cBK _n0 |
||
| 999 |
_c1 _d1 |
||