Deep learning is adaptive to intrinsic dimensionality of model
smoothness in anisotropic Besov space

v1v2 (latest)

Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space

28 October 2019

Atsushi Nitanda

ArXiv (abs)PDF HTML

Papers citing "Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space"

17 / 17 papers shown

Title
Nested Expectations with Kernel Quadrature Zonghao Chen Masha Naslidnyk F. Briol 67 2 0 25 Feb 2025
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 126 4 0 05 Jun 2024
Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu Yuling Jiao Li Shen Haizhao Yang Xiliang Lu OffRL 87 1 0 19 Dec 2023
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training Masaaki Imaizumi AAML 66 4 0 08 Jul 2023
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions Ido Ben-Shaul Tomer Galanti S. Dekel 80 3 0 11 Jan 2023
Smooth Sailing: Improving Active Learning for Pre-trained Language Models with Representation Smoothness Analysis Josip Jukić Jan Snajder 68 5 0 20 Dec 2022
Understanding Deep Neural Function Approximation in Reinforcement Learning via $ε$ -Greedy Exploration Fanghui Liu Luca Viano Volkan Cevher 116 19 0 15 Sep 2022
On the inability of Gaussian process regression to optimally learn compositional functions M. Giordano Kolyan Ray Johannes Schmidt-Hieber 116 13 0 16 May 2022
Analysis of convolutional neural network image classifiers in a rotationally symmetric model Michael Kohler Benjamin Kohler 57 5 0 11 May 2022
Drift estimation for a multi-dimensional diffusion process using deep neural networks Akihiro Oga Yuta Koike DiffM 54 6 0 26 Dec 2021
Estimation of a regression function on a manifold by fully connected deep neural networks Michael Kohler S. Langer U. Reif 68 5 0 20 Jul 2021
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis Atsushi Nitanda Denny Wu Taiji Suzuki 86 29 0 31 Dec 2020
Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods Taiji Suzuki Shunta Akiyama MLT 65 12 0 06 Dec 2020
Estimation error analysis of deep learning on the regression problem on the variable exponent Besov space Kazuma Tsuji Taiji Suzuki 74 16 0 23 Sep 2020
A deep network construction that adapts to intrinsic dimensionality beyond the domain A. Cloninger T. Klock AI4CE 79 14 0 06 Aug 2020
Black-Box Optimization with Local Generative Surrogates S. Shirobokov V. Belavin Michael Kagan Andrey Ustyuzhanin A. G. Baydin 40 3 0 11 Feb 2020
Fast generalization error bound of deep learning without scale invariance of activation functions Y. Terada Ryoma Hirose MLT 33 7 0 25 Jul 2019