Mark A. Davenport

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 69

Top Venues

Publications

Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood
Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures. Trans. Mach. Learn. Res. 2024 (2024)
Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood
Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures. CoRR (2024)
Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher Rozell
Distance preservation in state-space methods for detecting causal interactions in dynamical systems. CoRR (2023)
Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features. CoRR (2023)
Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. NeurIPS (2023)
Andrew D. McRae, Justin Romberg, Mark A. Davenport
Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer. IEEE Trans. Inf. Theory 69 (3) (2023)
Namrata Nadagouda, Austin Xu, Mark A. Davenport
Active metric learning and classification using similarity queries. UAI (2023)
Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. CoRR (2023)
Coleman DeLude, Rakshith Sharma Srinivasa, Santhosh Karnik, Christopher Hood, Mark A. Davenport, Justin Romberg
Iterative Broadband Source Localization. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya K. Muthukumar
Harmless interpolation in regression and classification with structured features. AISTATS (2022)
Andrew D. McRae, Austin Xu, Jihui Jin, Namrata Nadagouda, Nauman Ahad, Peimeng Guan, Santhosh Karnik, Mark A. Davenport
Delta Distancing: A Lifting Approach to Localizing Items from User Comparisons. ICASSP (2022)
Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport
Learning Sinkhorn divergences for supervised change point detection. CoRR (2022)
Namrata Nadagouda, Austin Xu, Mark A. Davenport
Active metric learning and classification using similarity queries. CoRR (2022)
Peimeng Guan, Jihui Jin, Justin Romberg, Mark A. Davenport
Loop Unrolled Shallow Equilibrium Regularizer (LUSER) - A Memory-Efficient Inverse Problem Solver. CoRR (2022)
Santhosh Karnik, Justin Romberg, Mark A. Davenport
Thomson's Multitaper Method Revisited. IEEE Trans. Inf. Theory 68 (7) (2022)
Andrew K. Massimino, Mark A. Davenport
As You Like It: Localization via Paired Comparisons. J. Mach. Learn. Res. 22 (2021)
Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya Muthukumar
Harmless interpolation in regression and classification with structured features. CoRR (2021)
Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. NeurIPS (2021)
Namrata Nadagouda, Mark A. Davenport
Switched Hawkes Processes. ICASSP (2021)
Nauman Ahad, Mark A. Davenport
Semi-supervised Sequence Classification through Change Point Detection. AAAI (2021)
Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. CoRR (2021)
Santhosh Karnik, Justin Romberg, Mark A. Davenport
Thomson's Multitaper Method Revisited. CoRR (2021)
Nauman Ahad, Mark A. Davenport
Semi-supervised sequence classification through change point detection. CoRR (2020)
Liangbei Xu, Mark A. Davenport
Dynamic Knowledge embedding and tracing. CoRR (2020)
Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Mark A. Davenport, Christopher Rozell
Generative causal explanations of black-box classifiers. CoRR (2020)
Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
Sparse Bayesian Learning With Dynamic Filtering for Inference of Time-Varying Sparse Signals. IEEE Trans. Signal Process. 68 (2020)
Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
Localized sketching for matrix multiplication and ridge regression. CoRR (2020)
Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
Trading Beams for Bandwidth: Imaging with Randomized Beamforming. SIAM J. Imaging Sci. 13 (1) (2020)
Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
Active Embedding Search via Noisy Paired Comparisons. ITA (2020)
Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Christopher Rozell, Mark A. Davenport
Generative causal explanations of black-box classifiers. NeurIPS (2020)
Austin Xu, Mark A. Davenport
Simultaneous Preference and Metric Learning from Paired Comparisons. CoRR (2020)
Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
Sample complexity bounds for localized sketching. AISTATS (2020)
Austin Xu, Mark A. Davenport
Simultaneous Preference and Metric Learning from Paired Comparisons. NeurIPS (2020)
Andrew D. McRae, Justin Romberg, Mark A. Davenport
Sample complexity and effective dimension for regression on manifolds. CoRR (2020)
Andrew D. McRae, Justin Romberg, Mark A. Davenport
Sample complexity and effective dimension for regression on manifolds. NeurIPS (2020)
Liangbei Xu, Mark A. Davenport
Dynamic Knowledge Embedding and Tracing. EDM (2020)
Chris Sabillon, Abbas Rashidi, Biswanath Samanta, Mark A. Davenport, David V. Anderson
Audio-Based Bayesian Model for Productivity Estimation of Cyclic Construction Activities. J. Comput. Civ. Eng. 34 (1) (2020)
Gregory Canal, Marissa Connor, Jihui Jin, Namrata Nadagouda, Matthew R. O'Shaughnessy, Christopher J. Rozell, Mark A. Davenport
The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model. ICASSP (2020)
Andrew D. McRae, Mark A. Davenport
Low-rank matrix completion and denoising under Poisson noise. CoRR (2019)
Albert Cohen, Mark A. Davenport, Dany Leviatan
Correction to: On the Stability and Accuracy of Least Squares Approximations. Found. Comput. Math. 19 (1) (2019)
Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
Active embedding search via noisy paired comparisons. CoRR (2019)
Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
Dynamical System Implementations of Sparse Bayesian Learning. CAMSAP (2019)
Gregory H. Canal, Matthew R. O'Shaughnessy, Christopher J. Rozell, Mark A. Davenport
Joint Estimation of Trajectory and Dynamics from Paired Comparisons. CAMSAP (2019)
Michael G. Moore, Mark A. Davenport
Estimation of Poisson Arrival Processes Under Linear Models. IEEE Trans. Inf. Theory 65 (6) (2019)
Gregory Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
Active Embedding Search via Noisy Paired Comparisons. ICML (2019)
Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg
ROAST: Rapid Orthogonal Approximate Slepian Transform. IEEE Trans. Signal Process. 66 (22) (2018)
Michael G. Moore, Mark A. Davenport
Estimation of Poisson arrival processes under linear models. CoRR (2018)
Theodore J. LaGrow, Michael G. Moore, Judy A. Prasad, Mark A. Davenport, Eva L. Dyer
Approximating Cellular Densities from High-Resolution Neuroanatomical Imaging Data. EMBC (2018)
Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin
The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. IEEE Signal Process. Lett. 25 (1) (2018)
Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
Localized random projections with applications to coherent array imaging. Allerton (2018)
Andrew K. Massimino, Mark A. Davenport
As you like it: Localization via paired comparisons. CoRR (2018)
Hongteng Xu, Licheng Yu, Mark A. Davenport, Hongyuan Zha
A Unified Framework for Manifold Landmarking. IEEE Trans. Signal Process. 66 (21) (2018)
Chieh-Feng Cheng, David V. Anderson, Mark A. Davenport, Abbas Rashidi
Audio Classification Based on Weakly Labeled Data. SSP (2018)
Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin
The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. CoRR (2017)
Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin K. Romberg
Fast orthogonal approximations of sampled sinusoids and bandlimited signals. ICASSP (2017)
Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg
ROAST: Rapid Orthogonal Approximate Slepian Transform. CoRR (2017)
Hongteng Xu, Licheng Yu, Mark A. Davenport, Hongyuan Zha
Active manifold learning via a unified framework for manifold landmarking. CoRR (2017)
Liangbei Xu, Mark A. Davenport
Simultaneous recovery of a series of low-rank matrices by locally weighted matrix smoothing. CAMSAP (2017)
Andrew K. Massimino, Mark A. Davenport
The geometry of random paired comparisons. ICASSP (2017)
Michael G. Moore, Mark A. Davenport
A Hawkes' eye view of network information flow. SSP (2016)
Andrew K. Massimino, Mark A. Davenport
Binary stable embedding via paired comparisons. SSP (2016)
Liangbei Xu, Mark A. Davenport
Dynamic matrix recovery from incomplete observations under an exact low-rank constraint. CoRR (2016)
Matthew R. O'Shaughnessy, Mark A. Davenport
Localizing users and items from paired comparisons. MLSP (2016)
Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf
Constrained Adaptive Sensing. IEEE Trans. Signal Process. 64 (20) (2016)
Mark A. Davenport, Justin K. Romberg
An overview of low-rank matrix recovery from incomplete observations. CoRR (2016)
Santhosh Karnik, Zhihui Zhu, Michael B. Wakin, Justin K. Romberg, Mark A. Davenport
Fast computations for approximation and compression in Slepian spaces. GlobalSIP (2016)
Mark A. Davenport, Justin K. Romberg
An Overview of Low-Rank Matrix Recovery From Incomplete Observations. IEEE J. Sel. Top. Signal Process. 10 (4) (2016)
Liangbei Xu, Mark A. Davenport
Dynamic matrix recovery from incomplete observations under an exact low-rank constraint. NIPS (2016)
Michael G. Moore, Mark A. Davenport
Analysis of wireless networks using Hawkes processes. SPAWC (2016)
Hongteng Xu, Hongyuan Zha, Ren-Cang Li, Mark A. Davenport
Active Manifold Learning via Gershgorin Circle Guided Sample Selection. AAAI (2015)
Michael G. Moore, Andrew K. Massimino, Mark A. Davenport
Randomized multi-pulse time-of-flight mass spectrometry. CAMSAP (2015)
Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf
Constrained adaptive sensing. CoRR (2015)
Rebecca M. Willett, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. IEEE Signal Process. Mag. 31 (1) (2014)
Hongteng Xu, Hongyuan Zha, Mark A. Davenport
Manifold Based Dynamic Texture Synthesis from Extremely Few Samples. CVPR (2014)
Ery Arias-Castro, Emmanuel J. Candès, Mark A. Davenport
On the Fundamental Limits of Adaptive Sensing. IEEE Trans. Inf. Theory 59 (1) (2013)
Albert Cohen, Mark A. Davenport, Dany Leviatan
On the Stability and Accuracy of Least Squares Approximations. Found. Comput. Math. 13 (5) (2013)
Mark A. Davenport, Deanna Needell, Michael B. Wakin
Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries. IEEE Trans. Inf. Theory 59 (10) (2013)
Adam Charles, Ali Ahmed, Aditya Joshi, Stephen Conover, Christopher K. Turnes, Mark A. Davenport
Cleaning up toxic waste: Removing nefarious contributions to recommendation systems. ICASSP (2013)
Mary Wootters, Yaniv Plan, Mark A. Davenport, Ewout van den Berg
Lower bounds for quantized matrix completion. ISIT (2013)
Mark A. Davenport
Lost without a compass: Nonmetric triangulation and landmark multidimensional scaling. CAMSAP (2013)
Mark A. Davenport, Ery Arias-Castro
Compressive binary search CoRR (2012)
Mark A. Davenport, Ery Arias-Castro
Compressive binary search. ISIT (2012)
Mark A. Davenport, Yaniv Plan, Ewout van den Berg, Mary Wootters
1-Bit Matrix Completion CoRR (2012)
Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range. IEEE Trans. Signal Process. 60 (9) (2012)
Stephen R. Schnelle, John P. Slavinsky, Petros Boufounos, Mark A. Davenport, Richard G. Baraniuk
A compressive phase-locked loop. ICASSP (2012)
Mark A. Davenport, Deanna Needell, Michael B. Wakin
CoSaMP with redundant dictionaries. ACSCC (2012)
Mark A. Davenport, Deanna Needell, Michael B. Wakin
Signal Space CoSaMP for Sparse Recovery with Redundant Dictionaries CoRR (2012)
Ery Arias-Castro, Emmanuel J. Candès, Mark A. Davenport
On the Fundamental Limits of Adaptive Sensing CoRR (2011)
Mark A. Davenport, Michael B. Wakin
Compressive Sensing of Analog Signals Using Discrete Prolate Spheroidal Sequences CoRR (2011)
Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range CoRR (2011)
Emmanuel J. Candès, Mark A. Davenport
How well can we estimate a sparse vector? CoRR (2011)
John P. Slavinsky, Jason N. Laska, Mark A. Davenport, Richard G. Baraniuk
The compressive multiplexer for multi-channel compressive sensing. ICASSP (2011)
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
High Dimensional Data Fusion via Joint Manifold Learning. AAAI Fall Symposium: Manifold Learning and Its Applications (2010)
Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
Texas Hold 'Em algorithms for distributed compressive sensing. ICASSP (2010)
Mark A. Davenport, Michael B. Wakin
Analysis of orthogonal matching pursuit using the restricted isometry property. IEEE Trans. Inf. Theory 56 (9) (2010)
Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. IEEE Trans. Pattern Anal. Mach. Intell. 32 (10) (2010)
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
Joint Manifolds for Data Fusion. IEEE Trans. Image Process. 19 (10) (2010)
Mark A. Davenport, Petros Boufounos, Michael B. Wakin, Richard G. Baraniuk
Signal Processing With Compressive Measurements. IEEE J. Sel. Top. Signal Process. 4 (2) (2010)
Mark A. Davenport, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk
A simple proof that random matrices are democratic CoRR (2009)
Mark A. Davenport, Richard G. Baraniuk
Sparse Geodesic Paths. AAAI Fall Symposium: Manifold Learning and Its Applications (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mark A. Davenport