Abstract:
The construction of a meaningful graph topology plays a crucial role in the effective representation, processing, analysis, and visualization of structured data. When a n...Show MoreMetadata
Abstract:
The construction of a meaningful graph topology plays a crucial role in the effective representation, processing, analysis, and visualization of structured data. When a natural choice of the graph is not readily available from the data sets, it is thus desirable to infer or learn a graph topology from the data. In this article, we survey solutions to the problem of graph learning, including classical viewpoints from statistics and physics, and more recent approaches that adopt a graph signal processing (GSP) perspective. We further emphasize the conceptual similarities and differences between classical and GSP-based graph-inference methods and highlight the potential advantage of the latter in a number of theoretical and practical scenarios. We conclude with several open issues and challenges that are keys to the design of future signal processing and machine-learning algorithms for learning graphs from data.
Published in: IEEE Signal Processing Magazine ( Volume: 36, Issue: 3, May 2019)
Department of Engineering Science, University of Oxford, United Kingdom
Xiaowen Dong (xdong@robots.ox.ac.uk) received his B.Eng. degree in information engineering from Zhejiang University, China, in 2004, his M.Sc. degree in signal processing and communications from the University of Edinburgh, United Kingdom, in 2008, and his Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology, Lausanne, in 2014. He is currently a departmental lecturer in the Department of E...Show More
Xiaowen Dong (xdong@robots.ox.ac.uk) received his B.Eng. degree in information engineering from Zhejiang University, China, in 2004, his M.Sc. degree in signal processing and communications from the University of Edinburgh, United Kingdom, in 2008, and his Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology, Lausanne, in 2014. He is currently a departmental lecturer in the Department of E...View more
Electrical engineering, Swiss Federal Institute of Technology (EPFL), Lausanne
Dorina Thanou (dorina.thanou@epfl.ch) received her B.Sc. degree in electrical and computer engineering from the University of Patras, Greece, in 2008, her M.Sc. degree in communication systems, and her Ph.D. degree in electrical engineering, both from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2010 and 2015, respectively. She is currently a senior data scientist at the Swiss Data Science Centre (EPFL/E...Show More
Dorina Thanou (dorina.thanou@epfl.ch) received her B.Sc. degree in electrical and computer engineering from the University of Patras, Greece, in 2008, her M.Sc. degree in communication systems, and her Ph.D. degree in electrical engineering, both from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2010 and 2015, respectively. She is currently a senior data scientist at the Swiss Data Science Centre (EPFL/E...View more
Department of Electrical and Computer Engineering, McGill University, Montréal, Canada
Michael Rabbat (mikerabbat@fb.com) received his B.Sc. degree from the University of Illinois at Urbana-Champaign, in 2001, his M.Sc. degree from Rice University, Houston, Texas, in 2003, and his Ph.D. degree from the University of Wisconsin, Madison, in 2006, all in electrical engineering. He is currently a research scientist in Facebook’s AI Research group. From 2007 to 2018, he was a professor in the Department of Elect...Show More
Michael Rabbat (mikerabbat@fb.com) received his B.Sc. degree from the University of Illinois at Urbana-Champaign, in 2001, his M.Sc. degree from Rice University, Houston, Texas, in 2003, and his Ph.D. degree from the University of Wisconsin, Madison, in 2006, all in electrical engineering. He is currently a research scientist in Facebook’s AI Research group. From 2007 to 2018, he was a professor in the Department of Elect...View more
Electrical engineering, Swiss Federal Institute of Technology (EPFL), Lausanne
Pascal Frossard (pascal.frossard@epfl.ch) received his M.S. and Ph.D. degrees in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 1997 and 2000, respectively. From 2001 to 2003, he was with the IBM T.J. Watson Research Center, Yorktown Heights, New York, where he was involved in media coding and streaming technologies. Since 2003, he has been a faculty member at EPFL, where he cur...Show More
Pascal Frossard (pascal.frossard@epfl.ch) received his M.S. and Ph.D. degrees in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 1997 and 2000, respectively. From 2001 to 2003, he was with the IBM T.J. Watson Research Center, Yorktown Heights, New York, where he was involved in media coding and streaming technologies. Since 2003, he has been a faculty member at EPFL, where he cur...View more
Contents Department of Engineering Science, University of Oxford, United Kingdom
Xiaowen Dong (xdong@robots.ox.ac.uk) received his B.Eng. degree in information engineering from Zhejiang University, China, in 2004, his M.Sc. degree in signal processing and communications from the University of Edinburgh, United Kingdom, in 2008, and his Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology, Lausanne, in 2014. He is currently a departmental lecturer in the Department of Engineering Science at the University of Oxford, United Kingdom. Prior to joining Oxford, he was a postdoctoral associate in the Massachusetts Institute of Technology Media Lab, Cambridge. He is primarily interested in utilizing graphs to model relational structure within the data and developing novel techniques that lie at the intersection of machine learning, signal processing, and complex networks.
Xiaowen Dong (xdong@robots.ox.ac.uk) received his B.Eng. degree in information engineering from Zhejiang University, China, in 2004, his M.Sc. degree in signal processing and communications from the University of Edinburgh, United Kingdom, in 2008, and his Ph.D. degree in electrical engineering from the Swiss Federal Institute of Technology, Lausanne, in 2014. He is currently a departmental lecturer in the Department of Engineering Science at the University of Oxford, United Kingdom. Prior to joining Oxford, he was a postdoctoral associate in the Massachusetts Institute of Technology Media Lab, Cambridge. He is primarily interested in utilizing graphs to model relational structure within the data and developing novel techniques that lie at the intersection of machine learning, signal processing, and complex networks.View more
Electrical engineering, Swiss Federal Institute of Technology (EPFL), Lausanne
Dorina Thanou (dorina.thanou@epfl.ch) received her B.Sc. degree in electrical and computer engineering from the University of Patras, Greece, in 2008, her M.Sc. degree in communication systems, and her Ph.D. degree in electrical engineering, both from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2010 and 2015, respectively. She is currently a senior data scientist at the Swiss Data Science Centre (EPFL/ETH Zurich). Prior to joining the SDSC, she was a postdoctoral researcher in the Signal Processing Laboratory at EPFL. Her research interests include graph-based signal processing for data representation and analysis as well as machine learning, with a particular focus on the design of interpretable models for real-world applications.
Dorina Thanou (dorina.thanou@epfl.ch) received her B.Sc. degree in electrical and computer engineering from the University of Patras, Greece, in 2008, her M.Sc. degree in communication systems, and her Ph.D. degree in electrical engineering, both from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2010 and 2015, respectively. She is currently a senior data scientist at the Swiss Data Science Centre (EPFL/ETH Zurich). Prior to joining the SDSC, she was a postdoctoral researcher in the Signal Processing Laboratory at EPFL. Her research interests include graph-based signal processing for data representation and analysis as well as machine learning, with a particular focus on the design of interpretable models for real-world applications.View more
Department of Electrical and Computer Engineering, McGill University, Montréal, Canada
Michael Rabbat (mikerabbat@fb.com) received his B.Sc. degree from the University of Illinois at Urbana-Champaign, in 2001, his M.Sc. degree from Rice University, Houston, Texas, in 2003, and his Ph.D. degree from the University of Wisconsin, Madison, in 2006, all in electrical engineering. He is currently a research scientist in Facebook’s AI Research group. From 2007 to 2018, he was a professor in the Department of Electrical and Computer Engineering at McGill University, Montréal, Canada. His research interests include graph signal processing, optimization, and distributed algorithms.
Michael Rabbat (mikerabbat@fb.com) received his B.Sc. degree from the University of Illinois at Urbana-Champaign, in 2001, his M.Sc. degree from Rice University, Houston, Texas, in 2003, and his Ph.D. degree from the University of Wisconsin, Madison, in 2006, all in electrical engineering. He is currently a research scientist in Facebook’s AI Research group. From 2007 to 2018, he was a professor in the Department of Electrical and Computer Engineering at McGill University, Montréal, Canada. His research interests include graph signal processing, optimization, and distributed algorithms.View more
Electrical engineering, Swiss Federal Institute of Technology (EPFL), Lausanne
Pascal Frossard (pascal.frossard@epfl.ch) received his M.S. and Ph.D. degrees in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 1997 and 2000, respectively. From 2001 to 2003, he was with the IBM T.J. Watson Research Center, Yorktown Heights, New York, where he was involved in media coding and streaming technologies. Since 2003, he has been a faculty member at EPFL, where he currently heads the Signal Processing Laboratory. His research interests include signal processing on graphs and networks, image representation and coding, and visual information analysis.
Pascal Frossard (pascal.frossard@epfl.ch) received his M.S. and Ph.D. degrees in electrical engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 1997 and 2000, respectively. From 2001 to 2003, he was with the IBM T.J. Watson Research Center, Yorktown Heights, New York, where he was involved in media coding and streaming technologies. Since 2003, he has been a faculty member at EPFL, where he currently heads the Signal Processing Laboratory. His research interests include signal processing on graphs and networks, image representation and coding, and visual information analysis.View more
