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Publications are listed in reverse chronological order.
[6] Quantitative Group Testing and Pooled Data in the Linear Regime with Sublinear Tests
Nelvin Tan, Pablo Pascual Cobo, and Ramji Venkataramanan
In Submission
[arxiv] [code]
[5] Approximate Message Passing with Rigorous Guarantees for Pooled Data and Quantitative Group Testing
Nelvin Tan, Pablo Pascual Cobo, Jonathan Scarlett, and Ramji Venkataramanan
SIAM Journal on Mathematics of Data Science (SIMODS), 2024
[arxiv] [code]
[4] Mixed Regression via Approximate Message Passing
Nelvin Tan and Ramji Venkataramanan
Journal of Machine Learning Research (JMLR), 2023
[arxiv] [code]
[3] Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing
Eric Price, Jonathan Scarlett, and Nelvin Tan
Information and Inference: A Journal of the IMA, 2023
[arxiv]
[2] Performance Bounds for Group Testing With Doubly-Regular Designs
Nelvin Tan, Way Tan, and Jonathan Scarlett
IEEE Transactions on Information Theory, 2023
[arxiv]
[1] Near Optimal Sparsity-Constrained Group Testing: Improved Bounds and Algorithms
Oliver Gebhard, Max Hahn-Klimroth, Olaf Parczyk, Manuel Penschuck, Maurice Rolvien, Jonathan Scarlett, and Nelvin Tan
IEEE Transactions on Information Theory, 2022
[arxiv]
[4] Quantitative Group Testing and Pooled Data with Sublinear Number of Tests
Nelvin Tan, Pablo Pascual Cobo, and Ramji Venkataramanan
International Zurich Seminar on Information and Communication (IZS), 2024
[pdf]
[3] Mixed Linear Regression via Approximate Message Passing
Nelvin Tan and Ramji Venkataramanan
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
[full version] [poster] [code]
[2] An Analysis of the DD Algorithm for Group Testing with Size Constrained Tests
Nelvin Tan and Jonathan Scarlett
International Symposium on Information Theory (ISIT), 2021
[full version] [slides]
[1] Near-Optimal Sparse Adaptive Group Testing
Nelvin Tan and Jonathan Scarlett
International Symposium on Information Theory (ISIT), 2020
[arxiv] [slides]
[3] Approximate Message Passing for Matrix Regression
Nelvin Tan
Ph.D. Thesis (University of Cambridge), 2024
[2] Fast Splitting Algorithms for Noisy and Sparsity-Constrained Group Testing
Nelvin Tan
Final Year Project (National University of Singapore), 2021
[thesis] [slides]
[1] Sparse Group Testing: Bounds and Algorithms
Nelvin Tan
Undergraduate Research Opportunity Program (National University of Singapore), 2020
[thesis] [slides]