

FOLLOWUS
Department of Statistics, University of California, Berkeley, CA 94720, USA
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
[ "", "Bin Yu is Chancellor's Professor at the departments of Statistics and of Electrical Engineering & Computer Sciences at the University of California at Berkeley. Her current research interests focus on statistics and machine learning theory, methodologies, and algorithms for solving high-dimensional data problems. Her group is engaged in interdisciplinary research with scientists from genomics, neuroscience, and remote sensing. She obtained her B.S. degree in mathematics from Peking University in 1984, her MA and PhD degrees in statistics from the University of California at Berkeley in 1987 and 1990, respectively. She was the Chair of Department of Statistics at UC Berkeley from 2009 to 2012, and is a founding co-director of the Microsoft Lab on Statistics and Information Technology at Peking University, China, and the Chair of the Scientific Advisory Committee for the Statistical Science Center at Peking University. She is a member of the U.S. National Academy of Sciences and Fellow of the American Academy of Arts and Sciences. She was a Guggenheim Fellow in 2006, an invited speaker at ICIAM in 2011, and the Tukey Memorial Lecturer of the Bernoulli Society in 2012. She was the President of the Institute of Mathematical Statistics (IMS) in 2013--2014, and the Rietz Lecturer of the IMS in 2016. She is a Fellow of IMS, ASA, AAAS, and IEEE. She served on the Board of Mathematics Sciences and Applications of the NAS and as a co-chair of SAMSI Advisory Committee. She is serving on the Board of Trustees at ICERM and Scientific Advisory Board of IPAM. She has served or is serving on numerous editorial boards, including Journal of Machine Learning Research (JMLR), Annals of Statistics, and Journal of American Statistical Association (JASA)" ]
Received:07 December 2017,
Revised:2018-;1-28,
Published:2018-01
Scan QR Code
Bin YU, Karl KUMBIER. Artificial intelligence and statistics[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(1): 6-9.
Bin YU, Karl KUMBIER. Artificial intelligence and statistics[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(1): 6-9. DOI: 10.1631/FITEE.1700813.
Artificial intelligence (AI) is intrinsically data-driven. It calls for the application of statistical concepts through human-machine collaboration during the generation of data
the development of algorithms
and the evaluation of results. This paper discusses how such human-machine collaboration can be approached through the statistical concepts of population
question of interest
representativeness of training data
and scrutiny of results (PQRS). The PQRS workflow provides a conceptual framework for integrating statistical ideas with human input into AI products and researches. These ideas include experimental design principles of randomization and local control as well as the principle of stability to gain reproducibility and interpretability of algorithms and data results. We discuss the use of these principles in the contexts of self-driving cars
automated medical diagnoses
and examples from the authors' collaborative research.
S Basu , , , K Kumbier , , , JB Brown , , , 等 . . Iterative random forests to discover predictive and stable highorder interactions . . PNAS , , 2018 . . 115 ( ( 8 ): ): 1 - - 6 . . DOI: 10.1073/pnas.1711236115 http://doi.org/10.1073/pnas.1711236115 . .
GE Box , , , JS Hunter , , , WG Hunter . . Statistics for Experimenters: Design, Innovation, and Discovery , , 2nd Ed. : : New York, USA Wiley-Interscience , , 2005 . . .
GW Imbens , , , DB Rubin . . Causal Inference for Statistics, Social, and Biomedical Sciences , , : : UK Cambridge University Press , , 2015 . . DOI: 10.1017/cbo9781139025751 http://doi.org/10.1017/cbo9781139025751 . .
WS McCulloch , , , W Pitts . . A logical calculus of the ideas immanent in nervous activity . . Bull Math Biophys , , 1943 . . 5 ( ( 4 ): ): 115 - - 133 . . DOI: 10.1007/BF02478259 http://doi.org/10.1007/BF02478259 . .
L Wolpert . . Positional information and the spatial pattern of cellular differentiation . . J Theor Biol , , 1969 . . 25 ( ( 1 ): ): 1 - - 47 . . DOI: 10.1016/s0022-5193(69)80016-0 http://doi.org/10.1016/s0022-5193(69)80016-0 . .
B Yu . . Stability . . Bernoulli , , 2013 . . 19 ( ( 4 ): ): 1484 - - 1500 . . DOI: 10.3150/13-bejsp14 http://doi.org/10.3150/13-bejsp14 . .
Publicity Resources
Related Articles
Related Author
Related Institution
京公网安备11010802024621