This special issue will focus on the intersection of Information theory with estimation and inference. Information Theory has provided powerful tools as well as deep insights into optimal procedures for statistical inference and estimation. The application of these tools include characterization of optimal error probabilities in hypothesis testing, determination of minimax rates of convergence for estimation problems, analysis of message-passing and other efficient algorithms, as well as demonstrating the equivalence of different estimation problems. This issue will illuminate new connections between information theory, statistical inference, and estimation, as well as highlight applications where information-theoretic tools for inference and estimation have proved fruitful in a wide range of areas including signal processing, data mining, machine learning, pattern and image recognition, computational neuroscience, bioinformatics and cryptography.
IEEE Journal on Selected Areas in Information Theory (JSAIT)
Editor-in-Chief: Andrea Goldsmith (Stanford University)
Call for Papers
Prospective authors are invited to submit original manuscripts on topics within this broad scope including, but not limited to:
- Matrix and Tensor Estimation
- Graphical Models
- Optimization for Estimation and Inference
- High-dimensional Statistics
- Privacy
- Generalization Bounds and Connections to Learning Theory
- Functional Estimation
- Message-Passing Algorithms
- Bayesian Inference
- Black-box Uncertainty Quantification and Inference
- Combinatorial Estimation Problems
Guest Editors
Lead Guest Editor
- Devavrat Shah (MIT): [email protected]
Guest Editors
- Guy Bresler (MIT): [email protected]
- John Duchi (Stanford): [email protected]
- Po-Ling Loh (Univ of Wisconsin): [email protected]
- Ryan Tibshirani (CMU): [email protected]
- Yihong Wu (Yale): [email protected]
- Christina Lee Yu (Cornell): [email protected]
Senior Editor Advisers
- Emmanuel Candes (Stanford)
- Andrea Montanari (Stanford)
Submission Guidelines
Prospective authors must follow the IEEE Journal on Selected Areas in Information Theory guidelines regarding the manuscript and its format. For details and templates, please refer to the IEEE Journal on Selected Areas in Information Theory Author Information webpage. All papers should be submitted through Scholar One according to the following schedule:
Important Dates
Manuscript Due: May 15, 2020 (Extended from May 1)
Acceptance Notification: October 15, 2020
Final to Publisher: November 5, 2020
Expected Publication: November/December 2020
Manuscript Submission Website: https://mc.manuscriptcentral.com/jsait-ieee
Download this call for papers as a PDF .