Ben Adcock
According to our database1,
Ben Adcock
authored at least 74 papers
between 2010 and 2025.
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Bibliography
2025
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks.
Neural Networks, 2025
2024
Stable and Accurate Least Squares Radial Basis Function Approximations on Bounded Domains.
SIAM J. Numer. Anal., 2024
Learning Lipschitz Operators with respect to Gaussian Measures with Near-Optimal Sample Complexity.
CoRR, 2024
On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know'.
CoRR, 2024
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks.
CoRR, 2024
A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains.
SIAM J. Sci. Comput., February, 2023
Optimal approximation of infinite-dimensional holomorphic functions II: recovery from i.i.d. pointwise samples.
CoRR, 2023
Restarts subject to approximate sharpness: A parameter-free and optimal scheme for first-order methods.
CoRR, 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2022
Do Log Factors Matter? On Optimal Wavelet Approximation and the Foundations of Compressed Sensing.
Found. Comput. Math., 2022
CoRR, 2022
Is Monte Carlo a bad sampling strategy for learning smooth functions in high dimensions?
CoRR, 2022
On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples.
CoRR, 2022
Stable, accurate and efficient deep neural networks for inverse problems with analysis-sparse models.
CoRR, 2022
CoRR, 2022
2021
The Benefits of Acting Locally: Reconstruction Algorithms for Sparse in Levels Signals With Stable and Robust Recovery Guarantees.
IEEE Trans. Signal Process., 2021
The Gap between Theory and Practice in Function Approximation with Deep Neural Networks.
SIAM J. Math. Data Sci., 2021
Improved Recovery Guarantees and Sampling Strategies for TV Minimization in Compressive Imaging.
SIAM J. Imaging Sci., 2021
Iterative and greedy algorithms for the sparsity in levels model in compressed sensing.
CoRR, 2021
On the possibility of fast stable approximation of analytic functions from equispaced samples via polynomial frames.
CoRR, 2021
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data.
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Learning High-Dimensional Hilbert-Valued Functions With Deep Neural Networks From Limited Data.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains.
SIAM J. Math. Data Sci., 2020
The troublesome kernel: why deep learning for inverse problems is typically unstable.
CoRR, 2020
2019
IEEE Signal Process. Lett., 2019
Numerische Mathematik, 2019
Optimal sampling strategies for multivariate function approximation on general domains.
CoRR, 2019
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling.
CoRR, 2019
CoRR, 2019
2018
Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations.
SIAM/ASA J. Uncertain. Quantification, 2018
Found. Comput. Math., 2018
Sparse approximation of multivariate functions from small datasets via weighted orthogonal matching pursuit.
CoRR, 2018
2017
Resolution-Optimal Exponential and Double-Exponential Transform Methods for Functions with Endpoint Singularities.
SIAM J. Sci. Comput., 2017
2016
Efficient Compressed Sensing SENSE pMRI Reconstruction With Joint Sparsity Promotion.
IEEE Trans. Medical Imaging, 2016
On Asymptotic Incoherence and Its Implications for Compressed Sensing of Inverse Problems.
IEEE Trans. Inf. Theory, 2016
A Note on Compressed Sensing of Structured Sparse Wavelet Coefficients From Subsampled Fourier Measurements.
IEEE Signal Process. Lett., 2016
SIAM J. Numer. Anal., 2016
Found. Comput. Math., 2016
Compressed sensing with local structure: uniform recovery guarantees for the sparsity in levels class.
CoRR, 2016
Analyzing the structure of multidimensional compressed sensing problems through coherence.
CoRR, 2016
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
Sparsity and parallel acquisition: Optimal uniform and nonuniform recovery guarantees.
Proceedings of the 2016 IEEE International Conference on Multimedia & Expo Workshops, 2016
2015
Linear Stable Sampling Rate: Optimality of 2D Wavelet Reconstructions from Fourier Measurements.
SIAM J. Math. Anal., 2015
Generalized sampling and the stable and accurate reconstruction of piecewise analytic functions from their Fourier coefficients.
Math. Comput., 2015
2014
New Exponential Variable Transform Methods for Functions with Endpoint Singularities.
SIAM J. Numer. Anal., 2014
SIAM J. Numer. Anal., 2014
SIAM J. Imaging Sci., 2014
Parameter selection and numerical approximation properties of Fourier extensions from fixed data.
J. Comput. Phys., 2014
J. Comput. Appl. Math., 2014
The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing.
CoRR, 2014
Proceedings of the 23rd International Conference on Computer Communication and Networks, 2014
Non-convex compressed sensing CT reconstruction based on tensor discrete Fourier slice theorem.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
Efficient compressed sensing SENSE parallel MRI reconstruction with joint sparsity promotion and mutual incoherence enhancement.
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
2013
Beyond Consistent Reconstructions: Optimality and Sharp Bounds for Generalized Sampling, and Application to the Uniform Resampling Problem.
SIAM J. Math. Anal., 2013
Breaking the coherence barrier: asymptotic incoherence and asymptotic sparsity in compressed sensing
CoRR, 2013
Generalized sampling: stable reconstructions, inverse problems and compressed sensing over the continuum.
CoRR, 2013
2012
On optimal wavelet reconstructions from Fourier samples: linearity and universality of the stable sampling rate
CoRR, 2012
2011
Math. Comput., 2011
J. Approx. Theory, 2011
2010
Numerische Mathematik, 2010