Our Most Downloaded and Cited AI/ML Books
I have asserted in past emails that our Artificial Intelligence and Machine Learning series is one of the top sources of information available to the AI/ML community. Here’s proof from an outside source. Scopus has ranked our AI/ML series #1 in the Computer Science > Artificial Intelligence subject area (for book series) and has the highest CITE Score (11.6). For comparison purposes, the next highest CITE Score is 3.2. I thought this might be a good lead-in to a list of our top 5 most cited (via Google Scholar) and downloaded titles. Downloads are defined as PDF version downloads on the Synthesis Digital Library of Engineering and Computer Science by readers at subscribing institutions. If this many people trust these books for research and reference, maybe you can too. |
| Most Downloaded and Cited Books Introduction to Semi-Supervised Learning Xiaojin Zhu and Andrew Goldberg, University of Wisconsin, Madison Downloads – 11,872 Citations – 1,624 Buy This BookCheck if you have access via Synthesis Digital Library Active Learning Burr Setlles, Carnegie Mellon University Downloads – 7,321 Citations – 5,061 Buy This BookCheck if you have access via Synthesis Digital Library Algorithms for Reinforcement Learning Csaba Szepesvari, University of Alberta Downloads – 6,816 Citations – 909 Buy This BookCheck if you have access via Synthesis Digital Library Markov Logic: An Interface Layer for Artificial Intelligence Pedro Domingos, University of Washington Daniel Lowd, University of Oregon Downloads – 5,222 Citations – 530 Buy This BookCheck if you have access via Synthesis Digital Library Visual Object Recognition Kristen Grauman, University of Texas at Austin Bastian Leibe, RWTH Aachen University Downloads – 4,372 Citations – 199 Buy This BookCheck if you have access via Synthesis Digital Library Brent Beckley Direct Marketing Manager Morgan & Claypool Publishers Sponsored by Morgan & Claypool Publishers |