Decision Learning: Learning with Strategic Decision Making

November 14, 2013
K. J. Ray Liu | University of Maryland, College Park

With the increasing ubiquity and power of mobile devices as well as the prevalence of social networks, more and more decisions and activities in our daily life are being recorded, tracked, and shared. This abundant and still growing real life data, known as “big data”, provides a tremendous research opportunity in various fields whereas traditionally data collected only in controlled and laboratory environment are available for analysis. To analyze, learn and understand such user-generated big data, machine learning has been an important tool and various machine learning algorithms have been developed. However, most existing machine learning algorithms focus on optimizing a global objective function at macroeconomic level, while totally ignore users’ local interests at the microeconomic level. Since the user-generated big data is the outcome of users’ decisions, actions and their socio-economic interactions, which are highly dynamic, without involving users’ local behaviors and interests, the results learned at a certain time instance may not be applicable in a future time instance. In this talk, we present a new tool called “decision learning” that can involve users’ behaviors and interactions by combining learning with strategic decision making. We will discuss some examples to show how decision learning can be used to better analyze users’ optimal decision from a user’ perspective and design a mechanism from the system designer’s perspective to achieve a desirable outcome.

Speaker Details

Dr. K. J. Ray Liu was named a Distinguished Scholar-Teacher of University of Maryland in 2007, where he is Christine Kim Eminent Professor of Information Technology. He leads the Maryland Signals and Information Group conducting research encompassing broad areas of signal processing and communications with recent focus on cooperative communications, cognitive networking, social learning and networks, and information forensics and security. Dr. Liu has received numerous honors and awards including IEEE Signal Processing Society 2009 Technical Achievement Award. A Fellow of the IEEE and AAAS, he is recognized by Thomson Reuters as an ISI Highly Cited Researcher. Dr. Liu is President of IEEE Signal Processing Society. He was the Editor-in-Chief of IEEE Signal Processing Magazine and the founding Editor-in-Chief of EURASIP Journal on Advances in Signal Processing. Dr. Liu also received various research and teaching recognitions from the University of Maryland, including Poole and Kent Senior Faculty Teaching Award, Outstanding Faculty Research Award, and Outstanding Faculty Service Award, all from A. James Clark School of Engineering; and Invention of the Year Award from Office of Technology Commercialization.