Mark A. Davenport

According to our database1, Mark A. Davenport authored at least 76 papers between 2006 and 2022.

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Bibliography

2022
Learning Sinkhorn divergences for supervised change point detection.
CoRR, 2022

Active metric learning and classification using similarity queries.
CoRR, 2022

Harmless interpolation in regression and classification with structured features.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
As You Like It: Localization via Paired Comparisons.
J. Mach. Learn. Res., 2021

Thomson's Multitaper Method Revisited.
CoRR, 2021

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Switched Hawkes Processes.
Proceedings of the IEEE International Conference on Acoustics, 2021

Semi-supervised Sequence Classification through Change Point Detection.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Sparse Bayesian Learning With Dynamic Filtering for Inference of Time-Varying Sparse Signals.
IEEE Trans. Signal Process., 2020

Trading Beams for Bandwidth: Imaging with Randomized Beamforming.
SIAM J. Imaging Sci., 2020

Localized sketching for matrix multiplication and ridge regression.
CoRR, 2020

Simultaneous Preference and Metric Learning from Paired Comparisons.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generative causal explanations of black-box classifiers.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sample complexity and effective dimension for regression on manifolds.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Active Embedding Search via Noisy Paired Comparisons.
Proceedings of the Information Theory and Applications Workshop, 2020

The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Dynamic Knowledge Embedding and Tracing.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

Sample complexity bounds for localized sketching.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Estimation of Poisson Arrival Processes Under Linear Models.
IEEE Trans. Inf. Theory, 2019

Correction to: On the Stability and Accuracy of Least Squares Approximations.
Found. Comput. Math., 2019

Low-rank matrix completion and denoising under Poisson noise.
CoRR, 2019

Dynamical System Implementations of Sparse Bayesian Learning.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Joint Estimation of Trajectory and Dynamics from Paired Comparisons.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
ROAST: Rapid Orthogonal Approximate Slepian Transform.
IEEE Trans. Signal Process., 2018

A Unified Framework for Manifold Landmarking.
IEEE Trans. Signal Process., 2018

The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators.
IEEE Signal Process. Lett., 2018

Audio Classification Based on Weakly Labeled Data.
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Approximating Cellular Densities from High-Resolution Neuroanatomical Imaging Data.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Localized random projections with applications to coherent array imaging.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017
Active manifold learning via a unified framework for manifold landmarking.
CoRR, 2017

Fast orthogonal approximations of sampled sinusoids and bandlimited signals.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

The geometry of random paired comparisons.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Simultaneous recovery of a series of low-rank matrices by locally weighted matrix smoothing.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016
Constrained Adaptive Sensing.
IEEE Trans. Signal Process., 2016

An Overview of Low-Rank Matrix Recovery From Incomplete Observations.
IEEE J. Sel. Top. Signal Process., 2016

A Hawkes' eye view of network information flow.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Binary stable embedding via paired comparisons.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Analysis of wireless networks using Hawkes processes.
Proceedings of the 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2016

Dynamic matrix recovery from incomplete observations under an exact low-rank constraint.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Localizing users and items from paired comparisons.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Fast computations for approximation and compression in Slepian spaces.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015
Randomized multi-pulse time-of-flight mass spectrometry.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

Active Manifold Learning via Gershgorin Circle Guided Sample Selection.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection.
IEEE Signal Process. Mag., 2014

Manifold Based Dynamic Texture Synthesis from Extremely Few Samples.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries.
IEEE Trans. Inf. Theory, 2013

On the Fundamental Limits of Adaptive Sensing.
IEEE Trans. Inf. Theory, 2013

On the Stability and Accuracy of Least Squares Approximations.
Found. Comput. Math., 2013

Lower bounds for quantized matrix completion.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Cleaning up toxic waste: Removing nefarious contributions to recommendation systems.
Proceedings of the IEEE International Conference on Acoustics, 2013

Lost without a compass: Nonmetric triangulation and landmark multidimensional scaling.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range.
IEEE Trans. Signal Process., 2012

1-Bit Matrix Completion
CoRR, 2012

Compressive binary search.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

A compressive phase-locked loop.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

CoSaMP with redundant dictionaries.
Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012

Introduction to compressed sensing.
Proceedings of the Compressed Sensing, 2012

2011
Compressive Sensing of Analog Signals Using Discrete Prolate Spheroidal Sequences
CoRR, 2011

How well can we estimate a sparse vector?
CoRR, 2011

The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range
CoRR, 2011

The compressive multiplexer for multi-channel compressive sensing.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Analysis of orthogonal matching pursuit using the restricted isometry property.
IEEE Trans. Inf. Theory, 2010

Joint Manifolds for Data Fusion.
IEEE Trans. Image Process., 2010

Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Signal Processing With Compressive Measurements.
IEEE J. Sel. Top. Signal Process., 2010

Texas Hold 'Em algorithms for distributed compressive sensing.
Proceedings of the IEEE International Conference on Acoustics, 2010

High Dimensional Data Fusion via Joint Manifold Learning.
Proceedings of the Manifold Learning and Its Applications, 2010

2009
A simple proof that random matrices are democratic
CoRR, 2009

A Theoretical Analysis of Joint Manifolds
CoRR, 2009

Sparse Geodesic Paths.
Proceedings of the Manifold Learning and Its Applications, 2009

2008
Single-pixel imaging via compressive sampling.
IEEE Signal Process. Mag., 2008

2007
Regression Level Set Estimation Via Cost-Sensitive Classification.
IEEE Trans. Signal Process., 2007

Multiscale Random Projections for Compressive Classification.
Proceedings of the International Conference on Image Processing, 2007

The smashed filter for compressive classification and target recognition.
Proceedings of the Computational Imaging V, San Jose, 2007

2006
Sparse Signal Detection from Incoherent Projections.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Controlling False Alarms With Support Vector Machines.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006


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