Ramji Venkataramanan

Ramji Venkataramanan

University of Cambridge

H-index: 20

Europe-United Kingdom

About Ramji Venkataramanan

Ramji Venkataramanan, With an exceptional h-index of 20 and a recent h-index of 16 (since 2020), a distinguished researcher at University of Cambridge, specializes in the field of Information theory, Statistical learning, Communications.

His recent articles reflect a diverse array of research interests and contributions to the field:

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

Quantitative Group Testing and Pooled Data with Sublinear Number of Tests

Coded Many-User Multiple Access via Approximate Message Passing

Mixed regression via approximate message passing

Sketching Sparse Low-rank Matrices with Near-optimal Sample-and Time-complexity Using Message Passing

Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing

Statistical-computational tradeoffs in mixed sparse linear regression

Bayes-optimal estimation in generalized linear models via spatial coupling

Ramji Venkataramanan Information

University

Position

___

Citations(all)

1185

Citations(since 2020)

739

Cited By

699

hIndex(all)

20

hIndex(since 2020)

16

i10Index(all)

29

i10Index(since 2020)

20

Email

University Profile Page

University of Cambridge

Google Scholar

View Google Scholar Profile

Ramji Venkataramanan Skills & Research Interests

Information theory

Statistical learning

Communications

Top articles of Ramji Venkataramanan

Title

Journal

Author(s)

Publication Date

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

arXiv preprint arXiv:2404.07864

Gabriel Arpino

Xiaoqi Liu

Ramji Venkataramanan

2024/4/11

Quantitative Group Testing and Pooled Data with Sublinear Number of Tests

International Zurich Seminar on Information and Communication (IZS 2024)

Nelvin Tan

Pablo Pascual Cobo

Ramji Venkataramanan

2024/3/6

Coded Many-User Multiple Access via Approximate Message Passing

arXiv preprint arXiv:2402.05625

Xiaoqi Liu

Kuan Hsieh

Ramji Venkataramanan

2024/2/8

Mixed regression via approximate message passing

Journal of Machine Learning Research

Nelvin Tan

Ramji Venkataramanan

2023

Sketching Sparse Low-rank Matrices with Near-optimal Sample-and Time-complexity Using Message Passing

IEEE Transactions on Information Theory

Xiaoqi Liu

Ramji Venkataramanan

2023/9

Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing

arXiv preprint arXiv:2308.14507

Yihan Zhang

Hong Chang Ji

Ramji Venkataramanan

Marco Mondelli

2023/8/28

Statistical-computational tradeoffs in mixed sparse linear regression

Gabriel Arpino

Ramji Venkataramanan

2023/7/12

Bayes-optimal estimation in generalized linear models via spatial coupling

Pablo Pascual Cobo

Kuan Hsieh

Ramji Venkataramanan

2023/6/25

Mixed linear regression via approximate message passing

Nelvin Tan

Ramji Venkataramanan

2023/4/11

Approximate message passing with rigorous guarantees for pooled data and quantitative group testing

arXiv preprint arXiv:2309.15507

Nelvin Tan

Jonathan Scarlett

Ramji Venkataramanan

2023/9/27

Near-Optimal Coding for Many-user Multiple Access Channels

IEEE Journal on Selected Areas in Information Theory

Kuan Hsieh

Cynthia Rush

Ramji Venkataramanan

2022/3/11

Precise asymptotics for spectral methods in mixed generalized linear models

arXiv preprint arXiv:2211.11368

Yihan Zhang

Marco Mondelli

Ramji Venkataramanan

2022/11/21

Optimal combination of linear and spectral estimators for generalized linear models

Foundations of Computational Mathematics

Marco Mondelli

Christos Thrampoulidis

Ramji Venkataramanan

2022/10

Estimation in rotationally invariant generalized linear models via approximate message passing

Ramji Venkataramanan

Kevin Kögler

Marco Mondelli

2022/6/28

A unifying tutorial on approximate message passing

Foundations and Trends® in Machine Learning

Oliver Y Feng

Ramji Venkataramanan

Cynthia Rush

Richard J Samworth

2022/5/29

Estimation of low-rank matrices via approximate message passing

Annals of Statistics

Andrea Montanari

Ramji Venkataramanan

2021/2/1

PCA initialization for approximate message passing in rotationally invariant models

Advances in Neural Information Processing Systems

Marco Mondelli

Ramji Venkataramanan

2021/12/6

Capacity-achieving spatially coupled sparse superposition codes with AMP decoding

IEEE Transactions on Information Theory

Cynthia Rush

Kuan Hsieh

Ramji Venkataramanan

2021/5/26

Modulated sparse superposition codes for the complex AWGN channel

IEEE Transactions on Information Theory

Kuan Hsieh

Ramji Venkataramanan

2021/5/17

Approximate message passing with spectral initialization for generalized linear models

Marco Mondelli

Ramji Venkataramanan

2021/3/18

See List of Professors in Ramji Venkataramanan University(University of Cambridge)

Co-Authors

H-index: 101
Kannan Ramchandran

Kannan Ramchandran

University of California, Berkeley

H-index: 29
S. Sandeep Pradhan

S. Sandeep Pradhan

University of Michigan-Dearborn

H-index: 24
Oliver Johnson

Oliver Johnson

University of Bristol

H-index: 15
Cynthia Rush

Cynthia Rush

Columbia University in the City of New York

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