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Demba E. Ba
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2020 – today
- 2024
- [c25]Alexander Lin, Demba E. Ba:
An Efficient Algorithm For Clustered Multi-Task Compressive Sensing. ICASSP 2024: 2550-2554 - [i29]Jonathan Huml, Abiy Tasissa, Demba E. Ba:
Clustering Inductive Biases with Unrolled Networks. CoRR abs/2402.10213 (2024) - 2023
- [j18]Bahareh Tolooshams
, Satish Mulleti
Unrolled Compressed Blind-Deconvolution. IEEE Trans. Signal Process. 71: 2118-2129 (2023) - [j17]Abiy Tasissa
K-Deep Simplex: Manifold Learning via Local Dictionaries. IEEE Trans. Signal Process. 71: 3741-3754 (2023) - [c24]Emmanouil Theodosis, Demba E. Ba:
Learning Silhouettes with Group Sparse Autoencoders. ICASSP 2023: 1-5 - [c23]Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba:
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. ICML 2023: 21153-21181 - [i28]Jonathan Huml, Abiy Tasissa, Demba E. Ba:
Sparse, Geometric Autoencoder Models of V1. CoRR abs/2302.11162 (2023) - [i27]Demba E. Ba, Akshunna S. Dogra, Rikab Gambhir, Abiy Tasissa, Jesse Thaler:
SHAPER: Can You Hear the Shape of a Jet? CoRR abs/2302.12266 (2023) - [i26]Emmanouil Theodosis, Karim Helwani, Demba E. Ba:
Learning Linear Groups in Neural Networks. CoRR abs/2305.18552 (2023) - [i25]Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba:
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. CoRR abs/2306.03249 (2023) - [i24]Alexander Lin, Demba E. Ba:
An Efficient Algorithm for Clustered Multi-Task Compressive Sensing. CoRR abs/2310.00420 (2023) - 2022
- [j16]Andrew H. Song
Gaussian Process Convolutional Dictionary Learning. IEEE Signal Process. Lett. 29: 95-99 (2022) - [j15]Bahareh Tolooshams, Demba E. Ba:
Stable and Interpretable Unrolled Dictionary Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j14]Alexander Lin
Covariance-Free Sparse Bayesian Learning. IEEE Trans. Signal Process. 70: 3818-3831 (2022) - [c22]Alexander Lin, Andrew H. Song, Berkin Bilgic
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. ICASSP 2022: 1511-1515 - [c21]Alexander Lin, Andrew H. Song, Demba E. Ba:
Mixture Model Auto-Encoders: Deep Clustering Through Dictionary Learning. ICASSP 2022: 3368-3372 - [i23]Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba:
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. CoRR abs/2202.12808 (2022) - [i22]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Learning Filter-Based Compressed Blind-Deconvolution. CoRR abs/2209.14165 (2022) - [i21]Emmanouil Theodosis, Demba E. Ba:
Learning unfolded networks with a cyclic group structure. CoRR abs/2211.09238 (2022) - 2021
- [j13]Bahareh Tolooshams
Deep Residual Autoencoders for Expectation Maximization-Inspired Dictionary Learning. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2415-2429 (2021) - [c20]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution. ICASSP 2021: 2890-2894 - [c19]Abiy Tasissa, Pranay Tankala, Demba E. Ba:
Weighed ℓ1 on the Simplex: Compressive Sensing Meets Locality. SSP 2021: 476-480 - [c18]Andrew H. Song, Demba E. Ba, Emery N. Brown:
PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components. UAI 2021: 1371-1381 - [i20]Emmanouil Theodosis, Bahareh Tolooshams, Pranay Tankala, Abiy Tasissa, Demba E. Ba:
On the convergence of group-sparse autoencoders. CoRR abs/2102.07003 (2021) - [i19]Andrew H. Song, Bahareh Tolooshams, Demba E. Ba:
Gaussian Process Convolutional Dictionary Learning. CoRR abs/2104.00530 (2021) - [i18]Abiy Tasissa, Pranay Tankala, Demba E. Ba:
Weighed 𝓁1 on the simplex: Compressive sensing meets locality. CoRR abs/2104.13894 (2021) - [i17]Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba:
Covariance-Free Sparse Bayesian Learning. CoRR abs/2105.10439 (2021) - [i16]Bahareh Tolooshams, Demba E. Ba:
PUDLE: Implicit Acceleration of Dictionary Learning by Backpropagation. CoRR abs/2106.00058 (2021) - [i15]Alexander Lin, Andrew H. Song, Demba E. Ba:
Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning. CoRR abs/2110.04683 (2021) - 2020
- [j12]Andrew H. Song
Convolutional Dictionary Learning With Grid Refinement. IEEE Trans. Signal Process. 68: 2558-2573 (2020) - [j11]Demba E. Ba
Deeply-Sparse Signal rePresentations (D$\text{S}^2$P). IEEE Trans. Signal Process. 68: 4727-4742 (2020) - [c17]Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba:
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions. ICML 2020: 9493-9503 - [i14]Abiy Tasissa, Emmanouil Theodosis, Bahareh Tolooshams, Demba E. Ba:
Dense and Sparse Coding: Theory and Architectures. CoRR abs/2006.09534 (2020) - [i13]Bahareh Tolooshams, Satish Mulleti, Demba E. Ba, Yonina C. Eldar:
Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution. CoRR abs/2010.11391 (2020) - [i12]Pranay Tankala, Abiy Tasissa, James M. Murphy, Demba E. Ba:
Manifold Learning and Deep Clustering with Local Dictionaries. CoRR abs/2012.02134 (2020)
2010 – 2019
- 2019
- [c16]Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba:
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. AISTATS 2019: 2476-2484 - [c15]Javier Zazo, Bahareh Tolooshams, Demba E. Ba:
Convolutional Dictionary Learning in Hierarchical Networks. CAMSAP 2019: 131-135 - [c14]Andrew H. Song, Leon Chlon, Hugo Soulat, John Tauber, Sandya Subramanian, Demba E. Ba, Michael J. Prerau
Multitaper Infinite Hidden Markov Model for EEG. EMBC 2019: 5803-5807 - [c13]Thomas Chang, Bahareh Tolooshams, Demba E. Ba:
Randnet: Deep Learning with Compressed Measurements of Images. MLSP 2019: 1-6 - [c12]Taposh Banerjee, Stephen A. Allsop, Kay M. Tye, Demba E. Ba, Vahid Tarokh:
Sequential Detection of Regime Changes in Neural Data. NER 2019: 139-142 - [i11]Bahareh Tolooshams, Sourav Dey, Demba E. Ba:
Deep Residual Auto-Encoders for Expectation Maximization-based Dictionary Learning. CoRR abs/1904.08827 (2019) - [i10]Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba:
Deep Exponential-Family Auto-Encoders. CoRR abs/1907.03211 (2019) - [i9]Andrew H. Song, Francisco J. Flores, Demba E. Ba:
Fast Convolutional Dictionary Learning off the Grid. CoRR abs/1907.09063 (2019) - [i8]Javier Zazo, Bahareh Tolooshams, Demba E. Ba:
Convolutional Dictionary Learning in Hierarchical Networks. CoRR abs/1907.09881 (2019) - [i7]Thomas Chang, Bahareh Tolooshams, Demba E. Ba:
RandNet: deep learning with compressed measurements of images. CoRR abs/1908.09258 (2019) - 2018
- [j10]Yingzhuo Zhang, Noa Malem-Shinitski, Stephen A. Allsop, Kay Tye, Demba E. Ba:
Estimating a Separably Markov Random Field from Binary Observations. Neural Comput. 30(4) (2018) - [j9]Seong-Eun Kim
A Multitaper Frequency-Domain Bootstrap Method. IEEE Signal Process. Lett. 25(12): 1805-1809 (2018) - [j8]Gabriel Schamberg
A Modularized Efficient Framework for Non-Markov Time Series Estimation. IEEE Trans. Signal Process. 66(12): 3140-3154 (2018) - [c11]Taposh Banerjee, John S. Choi, Bijan Pesaran, Demba E. Ba, Vahid Tarokh:
Wavelet Shrinkage and Thresholding Based Robust Classification for Brain-Computer Interface. ICASSP 2018: 836-840 - [c10]Bahareh Tolooshams, Sourav Dey, Demba E. Ba:
Scalable Convolutional Dictionary Learning with constrained Recurrent Sparse Auto-encoders. MLSP 2018: 1-6 - [c9]Taposh Banerjee, John S. Choi, Bijan Pesaran, Demba E. Ba, Vahid Tarokh:
Classification of Local Field Potentials using Gaussian Sequence Model. SSP 2018: 683-687 - [i6]Leon Chlon, Andrew H. Song, Sandya Subramanian, Hugo Soulat, John Tauber, Demba E. Ba, Michael J. Prerau:
Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference. CoRR abs/1805.07300 (2018) - [i5]Bahareh Tolooshams, Sourav Dey, Demba E. Ba:
Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-encoders. CoRR abs/1807.04734 (2018) - [i4]Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba:
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach. CoRR abs/1810.09920 (2018) - 2017
- [i3]Gabriel Schamberg, Demba E. Ba, Todd P. Coleman:
A Modularized Efficient Framework for Non-Markov Time Series Estimation. CoRR abs/1706.04685 (2017) - [i2]Yingzhuo Zhang, Noa Malem-Shinitski, Stephen A. Allsop, Kay Tye, Demba E. Ba:
Estimating a Separably-Markov Random Field (SMuRF) from Binary Observations. CoRR abs/1709.09723 (2017) - [i1]Taposh Banerjee, John S. Choi, Bijan Pesaran, Demba E. Ba, Vahid Tarokh:
Classification of Local Field Potentials using Gaussian Sequence Model. CoRR abs/1710.01821 (2017) - 2016
- [c8]Gabriel Schamberg
Efficient low-rank spectrotemporal decomposition using ADMM. SSP 2016: 1-5 - 2014
- [j7]Demba E. Ba, Simona Temereanca
Algorithms for the analysis of ensemble neural spiking activity using simultaneous-event multivariate point-process models. Frontiers Comput. Neurosci. 8: 6 (2014) - [j6]Luca Citi
Likelihood Methods for Point Processes with Refractoriness. Neural Comput. 26(2): 237-263 (2014) - [j5]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Convergence and Stability of Iteratively Re-weighted Least Squares Algorithms. IEEE Trans. Signal Process. 62(1): 183-195 (2014) - [c7]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Neural spike train denoising by point process re-weighted iterative smoothing. ACSSC 2014: 763-768 - 2013
- [j4]Robert Haslinger, Demba E. Ba, Ralf Galuske, Ziv Williams, Gordon Pipa:
Missing mass approximations for the partition function of stimulus driven Ising models. Frontiers Comput. Neurosci. 7: 96 (2013) - 2012
- [j3]Flavio P. Ribeiro, Dinei A. F. Florêncio, Demba E. Ba, Cha Zhang:
Geometrically Constrained Room Modeling With Compact Microphone Arrays. IEEE Trans. Speech Audio Process. 20(5): 1449-1460 (2012) - [c6]Demba E. Ba, Behtash Babadi, Patrick L. Purdon, Emery N. Brown:
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization. NIPS 2012: 2636-2644 - 2011
- [b1]Demba E. Ba:
Algorithms and inference for simultaneous-event multivariate point-process, with applications to neural data. Massachusetts Institute of Technology, Cambridge, MA, USA, 2011 - 2010
- [j2]Flavio P. Ribeiro, Cha Zhang, Dinei A. F. Florêncio, Demba E. Ba:
Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization. IEEE Trans. Speech Audio Process. 18(7): 1781-1792 (2010) - [c5]Demba E. Ba, Flavio P. Ribeiro, Cha Zhang, Dinei A. F. Florêncio:
L1 regularized room modeling with compact microphone arrays. ICASSP 2010: 157-160 - [c4]Flavio P. Ribeiro, Demba E. Ba, Cha Zhang, Dinei A. F. Florêncio:
Turning enemies into friends: Using reflections to improve sound source localization. ICME 2010: 731-736
2000 – 2009
- 2008
- [j1]Cha Zhang, Dinei A. F. Florêncio, Demba E. Ba, Zhengyou Zhang:
Maximum Likelihood Sound Source Localization and Beamforming for Directional Microphone Arrays in Distributed Meetings. IEEE Trans. Multim. 10(3): 538-548 (2008) - 2007
- [c3]Demba E. Ba, Dinei A. F. Florêncio, Cha Zhang:
Enhanced MVDR Beamforming for Arrays of Directional Microphones. ICME 2007: 1307-1310 - [c2]Demba E. Ba, Vivek K. Goyal
Integer Polar Coordinates for Compression. ISIT 2007: 1116-1120 - 2006
- [c1]Demba E. Ba, Vivek K. Goyal
Nonlinear Transform Coding: Polar Coordinates Revisited. DCC 2006: 438
Coauthor Index
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last updated on 2024-08-06 22:05 CEST by the dblp team
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