Deep Learning Meets Sparse Regularization: A Signal Processing Perspective

23 January 2023

Papers citing "Deep Learning Meets Sparse Regularization: A Signal Processing Perspective"

18 / 18 papers shown

Title
An Overview of Low-Rank Structures in the Training and Adaptation of Large Models Laura Balzano Tianjiao Ding B. Haeffele Soo Min Kwon Qing Qu Peng Wang Z. Wang Can Yaras OffRL AI4CE 62 0 0 25 Mar 2025
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries Chris Kolb T. Weber Bernd Bischl David Rügamer 113 0 0 04 Feb 2025
The Effects of Multi-Task Learning on ReLU Neural Network Functions Julia B. Nakhleh Joseph Shenouda Robert D. Nowak 34 1 0 29 Oct 2024
ReTok: Replacing Tokenizer to Enhance Representation Efficiency in Large Language Model Shuhao Gu Mengdi Zhao Bowen Zhang Liangdong Wang Jijie Li Guang Liu 25 2 0 06 Oct 2024
Approaching Deep Learning through the Spectral Dynamics of Weights David Yunis Kumar Kshitij Patel Samuel Wheeler Pedro H. P. Savarese Gal Vardi Karen Livescu Michael Maire Matthew R. Walter 52 3 0 21 Aug 2024
ReLUs Are Sufficient for Learning Implicit Neural Representations Joseph Shenouda Yamin Zhou Robert D. Nowak 30 5 0 04 Jun 2024
Towards a Sampling Theory for Implicit Neural Representations Mahrokh Najaf Gregory Ongie 26 0 0 28 May 2024
Random ReLU Neural Networks as Non-Gaussian Processes Rahul Parhi Pakshal Bohra Ayoub El Biari Mehrsa Pourya Michael Unser 63 1 0 16 May 2024
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models Jeremy E. Cohen Valentin Leplat 63 1 0 27 Mar 2024
Applied Causal Inference Powered by ML and AI Victor Chernozhukov Christian Hansen Nathan Kallus Martin Spindler Vasilis Syrgkanis CML 36 29 0 04 Mar 2024
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities Rahul Parhi Michael Unser 39 5 0 05 Oct 2023
Weighted variation spaces and approximation by shallow ReLU networks Ronald A. DeVore Robert D. Nowak Rahul Parhi Jonathan W. Siegel 30 5 0 28 Jul 2023
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression Joseph Shenouda Rahul Parhi Kangwook Lee Robert D. Nowak 31 12 0 25 May 2023
Penalising the biases in norm regularisation enforces sparsity Etienne Boursier Nicolas Flammarion 34 14 0 02 Mar 2023
Convergence Rates of Oblique Regression Trees for Flexible Function Libraries M. D. Cattaneo Rajita Chandak Jason M. Klusowski 26 11 0 26 Oct 2022
From Kernel Methods to Neural Networks: A Unifying Variational Formulation M. Unser 48 7 0 29 Jun 2022
Understanding neural networks with reproducing kernel Banach spaces Francesca Bartolucci E. De Vito Lorenzo Rosasco S. Vigogna 39 50 0 20 Sep 2021
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks Rahul Parhi Robert D. Nowak 50 38 0 18 Sep 2021