Bubacarr Bah

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 28

Top Topics

Optimization Methods

Sparse Approximation

Model Selection

Top Venues

Frontiers Appl. Math. Stat.

Publications

Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
Recent methodological advances in federated learning for healthcare. Patterns 5 (6) (2024)
Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch
This actually looks like that: Proto-BagNets for local and global interpretability-by-design. CoRR (2024)
Hamid El Bahja, Jan Christian Hauffen, Peter Jung, Bubacarr Bah, Issa Karambal
A physics-informed neural network framework for modeling obstacle-related equations. CoRR (2023)
Daniel Nickelsen, Bubacarr Bah
Improved identification accuracy in equation learning via comprehensive R2-elimination and Bayesian model selection. Trans. Mach. Learn. Res. 2023 (2023)
Kerol R. Djoumessi Donteu, Indu Ilanchezian, Laura Kühlewein, Hanna Faber, Christian F. Baumgartner, Bubacarr Bah, Philipp Berens, Lisa M. Koch
Sparse Activations for Interpretable Disease Grading. MIDL (2023)
Daniel Nickelsen, Bubacarr Bah
-elimination and Bayesian model selection. CoRR (2023)
Samuel Ofosu Mensah, Bubacarr Bah, Willie Brink
Towards the Localisation of Lesions in Diabetic Retinopathy. SAI (3) (2021)
Jannis Kurtz, Bubacarr Bah
Efficient and Robust Mixed-Integer Optimization Methods for Training Binarized Deep Neural Networks. CoRR (2021)
Joseph Muthui Wacira, Dinna Ranirina, Bubacarr Bah
Low Rank Matrix Approximation for Imputing Missing Categorical Data. SACAIR (2021)
Hendrik Bernd Petersen, Shankar Agarwal, Peter Jung, Bubacarr Bah
Improving the Reliability of Pooled Testing with Combinatorial Decoding and Compressed Sensing. CISS (2021)
Bubacarr Bah, Jannis Kurtz, Oliver Schaudt
Discrete optimization methods for group model selection in compressed sensing. Math. Program. 190 (1) (2021)
Samuel Ofosu Mensah, Bubacarr Bah, Willie Brink
Towards the Localisation of Lesions in Diabetic Retinopathy. CoRR (2020)
Bubacarr Bah, Jean-Luc Bouchot
Editorial: Recent Developments in Signal Approximation and Reconstruction. Frontiers Appl. Math. Stat. 6 (2020)
Mhlasakululeka Mvubu, Emmanuel Kabuga, Christian Plitz, Bubacarr Bah, Ronnie Becker, Hans-Georg Zimmermann
On Error Correction Neural Networks for Economic Forecasting. FUSION (2020)
Bubacarr Bah, Jannis Kurtz
An Integer Programming Approach to Deep Neural Networks with Binary Activation Functions. CoRR (2020)
Mhlasakululeka Mvubu, Emmanuel Kabuga, Christian Plitz, Bubacarr Bah, Ronnie Becker, Hans-Georg Zimmermann
On Error Correction Neural Networks for Economic Forecasting. CoRR (2020)
Hendrik Bernd Petersen, Bubacarr Bah, Peter Jung
-Regression of Nonnegative Compressible Signals. CoRR (2020)
Hendrik Bernd Petersen, Bubacarr Bah, Peter Jung
Practical High-Throughput, Non-Adaptive and Noise-Robust SARS-CoV-2 Testing. CoRR (2020)
Emily Muller, Jonathan P. Shock, Andreas Bender, Julian Kleeberger, Tobias Högen, Martin Rosenfelder, Bubacarr Bah, Alex Lopez-Rolon
Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness. Comput. Biol. Medicine 107 (2019)
Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers. CoRR (2019)
Bubacarr Bah, Jannis Kurtz, Oliver Schaudt
Discrete Optimization Methods for Group Model Selection in Compressed Sensing. CoRR (2019)
Bubacarr Bah, Jared Tanner
On the Construction of Sparse Matrices From Expander Graphs. Frontiers Appl. Math. Stat. 4 (2018)
Bubacarr Bah, Jared Tanner
On the construction of sparse matrices from expander graphs. CoRR (2018)
Bubacarr Bah, Rachel Ward
The Sample Complexity of Weighted Sparse Approximation. IEEE Trans. Signal Process. 64 (12) (2016)
Bubacarr Bah
Weighted sparse recovery with expanders. CoRR (2016)
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
Convex block-sparse linear regression with expanders - provably. CoRR (2016)
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
Convex Block-sparse Linear Regression with Expanders - Provably. AISTATS (2016)
Bubacarr Bah, Rachel Ward
The sample complexity of weighted sparse approximation. CoRR (2015)
Bubacarr Bah, Luca Baldassarre, Volkan Cevher
Model-based Sketching and Recovery with Expanders. SODA (2014)
Bubacarr Bah, Stephen Becker, Volkan Cevher, Baran Gozcu
Metric learning with rank and sparsity constraints. ICASSP (2014)
Bubacarr Bah, Jared Tanner
Vanishingly Sparse Matrices and Expander Graphs, With Application to Compressed Sensing. IEEE Trans. Inf. Theory 59 (11) (2013)
Bubacarr Bah, Ali Sadeghian, Volkan Cevher
Energy-aware adaptive bi-Lipschitz embeddings. CoRR (2013)
Bubacarr Bah, Jared Tanner
On construction and analysis of sparse random matrices and expander graphs with applications to compressed sensing. CoRR (2013)
Bubacarr Bah, Jared Tanner
Vanishingly Sparse Matrices and Expander Graphs, with application to compressed sensing CoRR (2012)
Bubacarr Bah, Jared Tanner
Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices CoRR (2012)
Bubacarr Bah, Jared Tanner
Improved Bounds on Restricted Isometry Constants for Gaussian Matrices CoRR (2010)
Bubacarr Bah, Jared Tanner
Improved Bounds on Restricted Isometry Constants for Gaussian Matrices. SIAM J. Matrix Anal. Appl. 31 (5) (2010)