Breaking the Curse of Dimensionality with Convex Neural Networks

30 December 2014

Papers citing "Breaking the Curse of Dimensionality with Convex Neural Networks"

10 / 10 papers shown

Title
Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini Adel Javanmard Murat A. Erdogdu OOD AAML 85 1 0 21 Oct 2024
Probing the Latent Hierarchical Structure of Data via Diffusion Models Antonio Sclocchi Alessandro Favero Noam Itzhak Levi Matthieu Wyart DiffM 56 5 0 17 Oct 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics Alireza Mousavi-Hosseini Denny Wu Murat A. Erdogdu MLT AI4CE 50 6 0 14 Aug 2024
Simultaneous System Identification and Model Predictive Control with No Dynamic Regret Hongyu Zhou Vasileios Tzoumas 116 4 0 04 Jul 2024
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities Rahul Parhi Michael Unser 58 5 0 05 Oct 2023
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks Jonathan W. Siegel 56 7 0 28 Jul 2023
Performative Prediction with Neural Networks Mehrnaz Mofakhami Ioannis Mitliagkas Gauthier Gidel 52 18 0 14 Apr 2023
Penalising the biases in norm regularisation enforces sparsity Etienne Boursier Nicolas Flammarion 64 17 0 02 Mar 2023
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions Aaron Mishkin Arda Sahiner Mert Pilanci OffRL 97 30 0 02 Feb 2022
Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization Zaïd Harchaoui A. Juditsky A. Nemirovski 56 189 0 10 Feb 2013