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

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