Nonparametric regression using deep neural networks with ReLU activation function

22 August 2017

Papers citing "Nonparametric regression using deep neural networks with ReLU activation function"

50 / 54 papers shown

Title
Efficient Adaptive Experimentation with Non-Compliance Miruna Oprescu Brian M Cho Nathan Kallus 110 0 0 23 May 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 155 0 0 21 Apr 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 66 0 0 28 Jan 2025
Deep Partially Linear Transformation Model for Right-Censored Survival Data Junkai Yin Yue Zhang Zhangsheng Yu 232 0 0 10 Dec 2024
Understanding the Effect of GCN Convolutions in Regression Tasks Juntong Chen Johannes Schmidt-Hieber Claire Donnat Olga Klopp GNN 57 0 0 26 Oct 2024
Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini Adel Javanmard Murat A. Erdogdu OOD AAML 92 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 65 5 0 17 Oct 2024
Nested Deep Learning Model Towards A Foundation Model for Brain Signal Data Fangyi Wei Jiajie Mo Kai Zhang Haipeng Shen Srikantan Nagarajan Fei Jiang 122 2 0 04 Oct 2024
On the expressiveness and spectral bias of KANs Yixuan Wang Jonathan W. Siegel Ziming Liu Thomas Y. Hou 73 11 0 02 Oct 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 76 4 0 05 Jun 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 92 2 0 15 May 2024
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan OOD CML 191 2 0 07 May 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 149 528 0 30 Apr 2024
Deep Horseshoe Gaussian Processes Ismael Castillo Thibault Randrianarisoa BDL UQCV 70 5 0 04 Mar 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation Jikai Jin Vasilis Syrgkanis CML 103 1 0 22 Feb 2024
Nonlinear functional regression by functional deep neural network with kernel embedding Zhongjie Shi Jun Fan Linhao Song Ding-Xuan Zhou Johan A. K. Suykens 262 5 0 05 Jan 2024
Deep Huber quantile regression networks Hristos Tyralis Georgia Papacharalampous N. Dogulu Kwok-Pan Chun UQCV 75 2 0 17 Jun 2023
Utility Theory of Synthetic Data Generation Shi Xu W. Sun Guang Cheng 117 5 0 17 May 2023
Deep ReLU network approximation of functions on a manifold Johannes Schmidt-Hieber 48 92 0 02 Aug 2019
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality Ryumei Nakada Masaaki Imaizumi AI4CE 31 38 0 04 Jul 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 109 3,399 0 28 Mar 2019
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations Subutai Ahmad Luiz Scheinkman 47 96 0 27 Mar 2019
The State of Sparsity in Deep Neural Networks Trevor Gale Erich Elsen Sara Hooker 103 755 0 25 Feb 2019
How do infinite width bounded norm networks look in function space? Pedro H. P. Savarese Itay Evron Daniel Soudry Nathan Srebro 57 166 0 13 Feb 2019
Neural Network Topologies for Sparse Training Ryan A. Robinett J. Kepner 20 7 0 14 Sep 2018
Does data interpolation contradict statistical optimality? M. Belkin Alexander Rakhlin Alexandre B. Tsybakov 64 218 0 25 Jun 2018
Comparison of non-linear activation functions for deep neural networks on MNIST classification task Dabal Pedamonti 40 186 0 08 Apr 2018
A comparison of deep networks with ReLU activation function and linear spline-type methods Konstantin Eckle Johannes Schmidt-Hieber 60 327 0 06 Apr 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 173 3,433 0 09 Mar 2018
Characterizing Implicit Bias in Terms of Optimization Geometry Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro AI4CE 62 404 0 22 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 130 293 0 10 Feb 2018
Deep Expander Networks: Efficient Deep Networks from Graph Theory Ameya Prabhu G. Varma A. Namboodiri GNN 63 71 0 23 Nov 2017
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 83 908 0 27 Oct 2017
Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science Decebal Constantin Mocanu Elena Mocanu Peter Stone Phuong H. Nguyen M. Gibescu A. Liotta 121 625 0 15 Jul 2017
Fast learning rate of deep learning via a kernel perspective Taiji Suzuki 39 6 0 29 May 2017
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 128 256 0 04 May 2017
Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review T. Poggio H. Mhaskar Lorenzo Rosasco Brando Miranda Q. Liao 74 575 0 02 Nov 2016
Why Deep Neural Networks for Function Approximation? Shiyu Liang R. Srikant 73 383 0 13 Oct 2016
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 137 1,226 0 03 Oct 2016
Deep vs. shallow networks : An approximation theory perspective H. Mhaskar T. Poggio 98 341 0 10 Aug 2016
Risk Bounds for High-dimensional Ridge Function Combinations Including Neural Networks Jason M. Klusowski Andrew R. Barron 54 69 0 05 Jul 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi 299 14,196 0 23 Feb 2016
Benefits of depth in neural networks Matus Telgarsky 292 605 0 14 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.4K 192,638 0 10 Dec 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 247 6,628 0 08 Jun 2015
Highway Networks R. Srivastava Klaus Greff Jürgen Schmidhuber 120 1,765 0 03 May 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 121 703 0 30 Dec 2014
Convolutional Neural Networks at Constrained Time Cost Kaiming He Jian Sun 3DV 60 1,291 0 04 Dec 2014
On the Number of Linear Regions of Deep Neural Networks Guido Montúfar Razvan Pascanu Kyunghyun Cho Yoshua Bengio 77 1,250 0 08 Feb 2014
On the number of response regions of deep feed forward networks with piece-wise linear activations Razvan Pascanu Guido Montúfar Yoshua Bengio FAtt 102 257 0 20 Dec 2013