sparse approximation - Robuta Search

https://anr.fr/en/funded-projects-and-impact/funded-projects/project/funded/project/b2d9d3668f92a3b9fbbf7866072501ef-b48636c114/?tx_anrprojects_funded%5Bcontroller%5D=Funded&cHash=ccf3c5256dded088ef51d58e55d3fb0a Beyond compressive sensing: sparse approximation algorithms for ill-condioned inverse problems | ANR compressive sensing sparse approximation https://arxiv.org/abs/1205.2334 [1205.2334] Sparse Approximation via Penalty Decomposition Methods Abstract page for arXiv paper 1205.2334: Sparse Approximation via Penalty Decomposition Methods sparse approximation 1205 2334 via penalty https://openreview.net/forum?id=q3KSThy2GwB Practical Real Time Recurrent Learning with a Sparse Approximation | OpenReview Recurrent neural networks are usually trained with backpropagation through time, which requires storing a complete history of network states, and prohibits... real time recurrent learning sparse approximation practical openreview https://openreview.net/forum?id=i71zFLhBSw&referrer=%5Bthe%20profile%20of%20Gautam%20Pai%5D(%2Fprofile%3Fid%3D~Gautam_Pai1) Sparse Approximation of 3D Meshes Using the Spectral Geometry of the Hamiltonian Operator |... sparse approximation spectral geometry 3d meshes https://arxiv.org/abs/1205.2334v2 [1205.2334v2] Sparse Approximation via Penalty Decomposition Methods Abstract page for arXiv paper 1205.2334v2: Sparse Approximation via Penalty Decomposition Methods sparse approximation 1205 via penalty decomposition https://deepai.org/publication/the-l1-l2-minimization-with-rotation-for-sparse-approximation-in-uncertainty-quantification The l1-l2 minimization with rotation for sparse approximation in uncertainty quantification | DeepAI Jan 13, 2021 - 01/13/21 - This paper proposes a combination of rotational compressive sensing with the l1-l2 minimization to estimate coefficients of genera... https://openreview.net/forum?id=h1WGiCxywu Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation... The recent work by Dong and Yang (2023) showed for misspecified sparse linear bandits, one can obtain an $O\left(\epsilon\right)$-optimal policy using a... q learning linear function sparse https://arxiv.org/abs/1609.00246 [1609.00246] Sparse approximation of multilinear problems with applications to kernel-based methods... Abstract page for arXiv paper 1609.00246: Sparse approximation of multilinear problems with applications to kernel-based methods in UQ https://openreview.net/forum?id=rIx37QGIN5&referrer=%5Bthe%20profile%20of%20Zhifan%20Ye%5D(%2Fprofile%3Fid%3D~Zhifan_Ye1) Vitality: Unifying low-rank and sparse approximation for vision transformer acceleration with a... Vision Transformer (ViT) has emerged as a competitive alternative to convolutional neural networks for various computer vision applications. Specifically, ViT...