عرض عادي
Prediction, learning, and games / Nicolo Cesa-Bianchi, Gabor Lugosi.
نوع المادة :
نصالناشر:Cambridge ; New York : Cambridge University Press, 2006وصف:xii, 394 pages : illustrations ; 27 cmنوع المحتوى:- text
- unmediated
- volume
- 0521841089
- 9780521841085
- QA269 .C45 2006
المحتويات:
ملخص:This text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences.
1. Introduction -- 2. Prediction with expert advice -- 3. Tight bounds for specific losses -- 4. Randomized prediction -- 5. Efficient forecasters for large classes of experts -- 6. Prediction with limited feedback -- 7. Prediction and playing games -- 8. Absolute loss -- 9. Logarithmic loss -- 10. Sequential investment -- 11. Linear pattern recognition -- 12. Linear classification.
| نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
|---|---|---|---|---|---|---|---|
كتاب
|
UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA269 .C45 2006 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30020000012774 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
| QA268 .Y36 2020 Improving image quality in visual cryptography / | QA269 .B47 1992 Fun and games : a text on game theory | QA269 B475 2007 Playing for real : a text on game theory / | QA269 .C45 2006 Prediction, learning, and games / | QA269 .N687 2011 Super cooperators : evolution, altruism and human behaviour or why we need each other to succeed / | QA269 .N687 2011 Super cooperators : evolution, altruism and human behaviour or why we need each other to succeed / | QA269 .R37 1994 Games and information : an introduction to game theory |
Includes bibliographical references (pages 373-386) and indexes.
1. Introduction -- 2. Prediction with expert advice -- 3. Tight bounds for specific losses -- 4. Randomized prediction -- 5. Efficient forecasters for large classes of experts -- 6. Prediction with limited feedback -- 7. Prediction and playing games -- 8. Absolute loss -- 9. Logarithmic loss -- 10. Sequential investment -- 11. Linear pattern recognition -- 12. Linear classification.
This text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences.
