Description: Machine Learning and Knowledge Discovery in Databases by Massih-Reza Amini, Asja Fischer, Tias Guns, Grigorios Tsoumakas, Petra Kralj Novak, Stéphane Canu Estimated delivery 3-12 business days Format Paperback Condition Brand New Description The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; .Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track. Details ISBN 3031264185 ISBN-13 9783031264184 Title Machine Learning and Knowledge Discovery in Databases Author Massih-Reza Amini, Asja Fischer, Tias Guns, Grigorios Tsoumakas, Petra Kralj Novak, Stéphane Canu Format Paperback Year 2023 Pages 633 Edition 1st Publisher Springer International Publishing AG GE_Item_ID:151439326; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 113.98 USD
Location: Fairfield, Ohio
End Time: 2024-11-27T07:46:59.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9783031264184
Book Title: Machine Learning and Knowledge Discovery in Databases
Number of Pages: Xlvi, 633 Pages
Language: English
Publication Name: Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V
Publisher: Springer
Subject: Intelligence (Ai) & Semantics, Computer Science, General, Applied
Publication Year: 2023
Type: Textbook
Item Weight: 36.2 Oz
Author: Stéphane Canu
Subject Area: Mathematics, Computers, Science
Item Length: 9.3 in
Item Width: 6.1 in
Series: Lecture Notes in Computer Science Ser.
Format: Trade Paperback
