Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1603.00988
Cited By
v1
v2
v3
v4 (latest)
Learning Functions: When Is Deep Better Than Shallow
3 March 2016
H. Mhaskar
Q. Liao
T. Poggio
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Learning Functions: When Is Deep Better Than Shallow"
50 / 64 papers shown
Nonlocal techniques for the analysis of deep ReLU neural network approximations
Cornelia Schneider
Mario Ullrich
Jan Vybiral
276
3
0
07 Apr 2025
Deep Learning as Ricci Flow
Anthony Baptista
Alessandro Barp
Tapabrata Chakraborti
Chris Harbron
Ben D. MacArthur
Christopher R. S. Banerji
AI4CE
302
2
0
22 Apr 2024
Freely Long-Thinking Transformer (FraiLT)
Akbay Tabak
114
0
0
21 Jan 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models
Annual Review of Statistics and Its Application (ARSIA), 2024
Namjoon Suh
Guang Cheng
MedIm
366
19
0
14 Jan 2024
Loose lips sink ships: Mitigating Length Bias in Reinforcement Learning from Human Feedback
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Wei Shen
Rui Zheng
Wenyu Zhan
Jun Zhao
Jiajun Sun
Tao Gui
Tao Gui
Xuanjing Huang
ALM
400
73
0
08 Oct 2023
Deep neural network approximation of composite functions without the curse of dimensionality
Adrian Riekert
170
1
0
12 Apr 2023
Universal Approximation Property of Hamiltonian Deep Neural Networks
IEEE Control Systems Letters (L-CSS), 2023
M. Zakwan
M. d’Angelo
Giancarlo Ferrari-Trecate
228
7
0
21 Mar 2023
Expressivity of Shallow and Deep Neural Networks for Polynomial Approximation
Itai Shapira
146
0
0
06 Mar 2023
Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves
Xiaohong Chen
Yuan Liao
Weichen Wang
198
0
0
31 Dec 2022
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
S. Cohan
N. Kim
David Rolnick
M. van de Panne
177
7
0
24 Oct 2022
Cooperative Deep
Q
Q
Q
-learning Framework for Environments Providing Image Feedback
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Krishnan Raghavan
Vignesh Narayanan
S. Jagannathan
VLM
OffRL
122
3
0
28 Oct 2021
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
Chi-Ken Lu
Patrick Shafto
BDL
259
4
0
01 Oct 2021
The staircase property: How hierarchical structure can guide deep learning
Neural Information Processing Systems (NeurIPS), 2021
Emmanuel Abbe
Enric Boix-Adserà
Matthew Brennan
Guy Bresler
Dheeraj M. Nagaraj
220
64
0
24 Aug 2021
Stochastic Deep Model Reference Adaptive Control
IEEE Conference on Decision and Control (CDC), 2021
Girish Joshi
Girish Chowdhary
BDL
92
3
0
04 Aug 2021
Tensor Methods in Computer Vision and Deep Learning
Proceedings of the IEEE (Proc. IEEE), 2021
Yannis Panagakis
Jean Kossaifi
Grigorios G. Chrysos
James Oldfield
M. Nicolaou
Anima Anandkumar
Stefanos Zafeiriou
168
158
0
07 Jul 2021
Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning
Alberto Badías
A. Banerjee
297
6
0
02 Jul 2021
The Representation Power of Neural Networks: Breaking the Curse of Dimensionality
Moise Blanchard
M. A. Bennouna
163
7
0
10 Dec 2020
Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks
Multiscale Modeling & simulation (MMS), 2020
Matthew T.C. Li
L. Demanet
Leonardo Zepeda-Núnez
188
13
0
24 Nov 2020
Grow-Push-Prune: aligning deep discriminants for effective structural network compression
Qing Tian
Tal Arbel
James J. Clark
184
10
0
29 Sep 2020
Expressivity of Deep Neural Networks
Ingo Gühring
Mones Raslan
Gitta Kutyniok
216
61
0
09 Jul 2020
Learning the mapping
x
↦
∑
i
=
1
d
x
i
2
\mathbf{x}\mapsto \sum_{i=1}^d x_i^2
x
↦
∑
i
=
1
d
x
i
2
: the cost of finding the needle in a haystack
Jiefu Zhang
Leonardo Zepeda-Núnez
Xingtai Lv
Lin Lin
102
0
0
24 Feb 2020
Stationary Points of Shallow Neural Networks with Quadratic Activation Function
D. Gamarnik
Eren C. Kizildag
Ilias Zadik
223
15
0
03 Dec 2019
On the space-time expressivity of ResNets
J. Muller
AI4TS
228
5
0
21 Oct 2019
Deep Model Reference Adaptive Control
IEEE Conference on Decision and Control (CDC), 2019
Girish Joshi
Girish Chowdhary
BDL
AI4CE
130
69
0
18 Sep 2019
Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions
Shenhao Wang
Baichuan Mo
Jinhua Zhao
112
1
0
16 Sep 2019
Learning Hierarchically Structured Concepts
Neural Networks (NN), 2019
Nancy A. Lynch
Frederik Mallmann-Trenn
259
11
0
10 Sep 2019
PolyGAN: High-Order Polynomial Generators
Grigorios G. Chrysos
Stylianos Moschoglou
Yannis Panagakis
Stefanos Zafeiriou
GAN
157
19
0
19 Aug 2019
A Review on Deep Learning in Medical Image Reconstruction
Journal of the Operations Research Society of China (JORSC), 2019
Hai-Miao Zhang
Bin Dong
MedIm
386
150
0
23 Jun 2019
A Selective Overview of Deep Learning
Jianqing Fan
Cong Ma
Yiqiao Zhong
BDL
VLM
423
145
0
10 Apr 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
Gitta Kutyniok
P. Petersen
Mones Raslan
R. Schneider
297
216
0
31 Mar 2019
Limiting Network Size within Finite Bounds for Optimization
Linu Pinto
Sasi Gopalan
79
2
0
07 Mar 2019
Complexity of Linear Regions in Deep Networks
Boris Hanin
David Rolnick
273
254
0
25 Jan 2019
Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image Classification
S. H. Shabbeer Basha
S. Dubey
Viswanath Pulabaigari
Snehasis Mukherjee
OOD
159
464
0
21 Jan 2019
Realizing data features by deep nets
Zheng-Chu Guo
Lei Shi
Shao-Bo Lin
128
21
0
01 Jan 2019
BCR-Net: a neural network based on the nonstandard wavelet form
Yuwei Fan
Cindy Orozco Bohorquez
Lexing Ying
140
55
0
20 Oct 2018
Training Deeper Neural Machine Translation Models with Transparent Attention
Ankur Bapna
Mengzhao Chen
Orhan Firat
Yuan Cao
Yonghui Wu
267
144
0
22 Aug 2018
Are Efficient Deep Representations Learnable?
International Conference on Learning Representations (ICLR), 2018
Maxwell Nye
Andrew M. Saxe
93
24
0
17 Jul 2018
Bounds on the Approximation Power of Feedforward Neural Networks
International Conference on Machine Learning (ICML), 2018
M. Mehrabi
A. Tchamkerten
Mansoor I. Yousefi
98
12
0
29 Jun 2018
Deep Multiscale Model Learning
Yating Wang
Siu Wun Cheung
Eric T. Chung
Y. Efendiev
Min Wang
AI4CE
123
82
0
13 Jun 2018
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks
Yingzhou Li
Xiuyuan Cheng
Jianfeng Lu
351
23
0
18 May 2018
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization
Peter L. Bartlett
S. Evans
Philip M. Long
256
32
0
13 Apr 2018
A high-bias, low-variance introduction to Machine Learning for physicists
Pankaj Mehta
Marin Bukov
Ching-Hao Wang
A. G. Day
C. Richardson
Charles K. Fisher
D. Schwab
AI4CE
397
951
0
23 Mar 2018
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation
Shiyu Duan
Shujian Yu
Yunmei Chen
José C. Príncipe
335
17
0
11 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky
382
320
0
10 Feb 2018
Approximating Continuous Functions by ReLU Nets of Minimal Width
Boris Hanin
Mark Sellke
241
264
0
31 Oct 2017
Learning hard quantum distributions with variational autoencoders
Andrea Rocchetto
Edward Grant
Risi Kondor
Giuseppe Carleo
Simone Severini
BDL
DRL
238
87
0
02 Oct 2017
Optimal approximation of piecewise smooth functions using deep ReLU neural networks
P. Petersen
Felix Voigtländer
578
514
0
15 Sep 2017
On the Compressive Power of Deep Rectifier Networks for High Resolution Representation of Class Boundaries
Senjian An
Bennamoun
F. Boussaïd
82
2
0
24 Aug 2017
General AI Challenge - Round One: Gradual Learning
Jan Feyereisl
Matej Nikl
Martin Poliak
Martin Stránský
M. Vlasak
CLL
AI4CE
134
1
0
17 Aug 2017
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Boris Hanin
375
379
0
09 Aug 2017
1
2
Next
Page 1 of 2
