Bubacarr Bah

Orcid: 0000-0003-3318-6668

According to our database1, Bubacarr Bah authored at least 26 papers between 2010 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Improved identification accuracy in equation learning via comprehensive R<sup>2</sup>-elimination and Bayesian model selection.
CoRR, 2023

A physics-informed neural network framework for modeling obstacle-related equations.
CoRR, 2023

Sparse Activations for Interpretable Disease Grading.
Proceedings of the Medical Imaging with Deep Learning, 2023

2021
Discrete optimization methods for group model selection in compressed sensing.
Math. Program., 2021

Efficient and Robust Mixed-Integer Optimization Methods for Training Binarized Deep Neural Networks.
CoRR, 2021

Towards the Localisation of Lesions in Diabetic Retinopathy.
Proceedings of the Intelligent Computing, 2021

Low Rank Matrix Approximation for Imputing Missing Categorical Data.
Proceedings of the Artificial Intelligence Research - Second Southern African Conference, 2021

Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

2020
Editorial: Recent Developments in Signal Approximation and Reconstruction.
Frontiers Appl. Math. Stat., 2020

Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing.
CoRR, 2020

An Integer Programming Approach to Deep Neural Networks with Binary Activation Functions.
CoRR, 2020

Efficient Noise-Blind 𝓁<sub>1</sub>-Regression of Nonnegative Compressible Signals.
CoRR, 2020

On Error Correction Neural Networks for Economic Forecasting.
Proceedings of the IEEE 23rd International Conference on Information Fusion, 2020

2019
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers.
CoRR, 2019

Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness.
Comput. Biol. Medicine, 2019

2018
On the Construction of Sparse Matrices From Expander Graphs.
Frontiers Appl. Math. Stat., 2018

2016
The Sample Complexity of Weighted Sparse Approximation.
IEEE Trans. Signal Process., 2016

Weighted sparse recovery with expanders.
CoRR, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2014
Model-based Sketching and Recovery with Expanders.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Metric learning with rank and sparsity constraints.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Vanishingly Sparse Matrices and Expander Graphs, With Application to Compressed Sensing.
IEEE Trans. Inf. Theory, 2013

On construction and analysis of sparse random matrices and expander graphs with applications to compressed sensing.
CoRR, 2013

Energy-aware adaptive bi-Lipschitz embeddings.
CoRR, 2013

2012
Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices
CoRR, 2012

2010
Improved Bounds on Restricted Isometry Constants for Gaussian Matrices.
SIAM J. Matrix Anal. Appl., 2010


  Loading...