Transfer Learning
Transfer learning deals with how systems can quickly adapt themselves to new
situations, new tasks and new environments. It gives machine learning systems the
ability to leverage auxiliary data and models to help solve target problems when there
is only a small amount of data available in the target domain. This makes such systems
more reliable and robust, keeping the machine learning model faced with
unforeseeable changes from deviating too much from expected performance. At an
enterprise level, transfer learning allows knowledge to be reused so experience gained
once can be repeatedly applied to the real world.
This self-contained, comprehensive reference text begins by describing the standard
algorithms and then demonstrates how these are used in different transfer learning
paradigms and applications. It offers a solid grounding for newcomers as well as new
insights for seasoned researchers and developers.
qiang yangis the Head of AI at WeBank and a chair professor of computer
science and engineering at Hong Kong University of Science and Technology. He is a
fellow of the ACM, AAAI, IEEE, IAPR and AAAS, and has served on the AAAI
Executive Council and as president of IJCAI. Awards include the 2004/2005 ACM
KDDCUP Championship, the ACM SIGKDD Distinguished Service Award and
AAAI Innovative AI Applications Award. His books includeIntelligent Planning,
Crafting Your Research Future and Constraint-Based Design Recovery for
Software Engineering.
yu zhangis an associate professor in the Department of Computer Science and
Engineering at Southern University of Science and Technology. He has published
about sixty papers in top-tier AI and machine learning conferences and journals. He
won the best paper awards at UAI 2010 and PAKDD 2019, and the best student paper
award in the 2013 IEEE/WIC/ACM International Conference on Web Intelligence. He
was awarded the Young National Distinguished Scholar in China.
wenyuan daiis the Founder and CEO of 4Paradigm Co.,
Transfer Learning_Qiang Yang, Yu Zhang, Wenyuan Dai, Sinno Jialin Pan.pdf