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Theoretical Issues in Deep Networks: Approximation, Optimization and
  Generalization

Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization

Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2019
25 August 2019
T. Poggio
Andrzej Banburski
Q. Liao
    ODL
ArXiv (abs)PDFHTML

Papers citing "Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization"

50 / 78 papers shown
Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
Yong-Ming Tian
Shuang Liang
Shao-Qun Zhang
Feng-lei Fan
152
1
0
05 Nov 2025
Compositional Symmetry as Compression: Lie Pseudogroup Structure in Algorithmic Agents
Compositional Symmetry as Compression: Lie Pseudogroup Structure in Algorithmic Agents
Giulio Ruffini
AI4CE
79
0
0
12 Oct 2025
Interpretable Clinical Classification with Kolgomorov-Arnold Networks
Interpretable Clinical Classification with Kolgomorov-Arnold Networks
Alejandro Almodóvar
Patricia A. Apellániz
Alba Garrido
Fernando Fernández-Salvador
Santiago Zazo
J. Parras
276
1
0
20 Sep 2025
Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks
Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks
Jiun-Cheng Jiang
Morris Yu-Chao Huang
Tianlong Chen
Hsi-Sheng Goan
145
1
0
17 Sep 2025
Should We Always Train Models on Fine-Grained Classes?
Should We Always Train Models on Fine-Grained Classes?
Davide Pirovano
Federico Milanesio
Michele Caselle
Piero Fariselli
Matteo Osella
161
0
0
05 Sep 2025
The wall confronting large language models
The wall confronting large language models
P. V. Coveney
S. Succi
250
7
0
25 Jul 2025
Input Convex Kolmogorov Arnold Networks
Input Convex Kolmogorov Arnold Networks
Thomas Deschatre
Xavier Warin
301
1
0
27 May 2025
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture
Zuyu Xu
Bin Lv
224
4
0
30 Mar 2025
A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks
A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks
Quan Long
Bin Wang
Bing Xue
Mengjie Zhang
260
0
0
29 Jan 2025
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
Ashim Dahal
Saydul Akbar Murad
Nick Rahimi
484
1
0
27 Jan 2025
Dissecting a Small Artificial Neural Network
Dissecting a Small Artificial Neural Network
Xiguang Yang
Krish Arora
Michael Bachmann
277
0
0
03 Jan 2025
Gradient Boosting Trees and Large Language Models for Tabular Data
  Few-Shot Learning
Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot LearningConference on Computer Science and Information Systems (FedCSIS), 2024
Carlos Huertas
LMTD
328
4
0
06 Nov 2024
A resource-efficient model for deep kernel learning
A resource-efficient model for deep kernel learning
Luisa DÁmore
153
0
0
13 Oct 2024
KAN: Kolmogorov-Arnold Networks
KAN: Kolmogorov-Arnold Networks
Ziming Liu
Yixuan Wang
Sachin Vaidya
Fabian Ruehle
James Halverson
Marin Soljacic
Thomas Y. Hou
Max Tegmark
1.3K
1,468
0
30 Apr 2024
Training all-mechanical neural networks for task learning through in
  situ backpropagation
Training all-mechanical neural networks for task learning through in situ backpropagation
Shuaifeng Li
Xiaoming Mao
AI4CE
273
11
0
23 Apr 2024
Generative Subspace Adversarial Active Learning for Outlier Detection in
  Multiple Views of High-dimensional Data
Generative Subspace Adversarial Active Learning for Outlier Detection in Multiple Views of High-dimensional Data
Jose Cribeiro-Ramallo
Vadim Arzamasov
Federico Matteucci
Denis Wambold
Klemens Bohm
217
2
0
20 Apr 2024
A Unified Kernel for Neural Network Learning
A Unified Kernel for Neural Network Learning
Shao-Qun Zhang
Zong-Yi Chen
Yong-Ming Tian
Xun Lu
387
1
0
26 Mar 2024
Beyond Single-Model Views for Deep Learning: Optimization versus
  Generalizability of Stochastic Optimization Algorithms
Beyond Single-Model Views for Deep Learning: Optimization versus Generalizability of Stochastic Optimization Algorithms
Toki Tahmid Inan
Mingrui Liu
Amarda Shehu
241
0
0
01 Mar 2024
Surfing the modeling of PoS taggers in low-resource scenarios
Surfing the modeling of PoS taggers in low-resource scenarios
M. Ferro
V. Darriba
F. J. Ribadas
J. G. Gil
154
0
0
04 Feb 2024
Understanding and Leveraging the Learning Phases of Neural Networks
Understanding and Leveraging the Learning Phases of Neural Networks
Johannes Schneider
Mohit Prabhushankar
AI4CE
299
5
0
11 Dec 2023
Efficient Neural Networks for Tiny Machine Learning: A Comprehensive
  Review
Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review
M. Lê
Pierre Wolinski
Julyan Arbel
307
20
0
20 Nov 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
T. Getu
Georges Kaddoum
M. Bennis
396
1
0
13 Sep 2023
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function SpaceJournal of machine learning research (JMLR), 2023
Zhengdao Chen
502
4
0
03 Jul 2023
Why do CNNs excel at feature extraction? A mathematical explanation
Why do CNNs excel at feature extraction? A mathematical explanation
V. Nandakumar
Arush Tagade
Tongliang Liu
FAtt
138
1
0
03 Jul 2023
Homological Neural Networks: A Sparse Architecture for Multivariate
  Complexity
Homological Neural Networks: A Sparse Architecture for Multivariate Complexity
Yuanrong Wang
Antonio Briola
T. Aste
218
8
0
27 Jun 2023
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed
  on Orbits
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits
Zhuokai Zhao
Takumi Matsuzawa
W. Irvine
Michael Maire
G. Kindlmann
318
3
0
31 May 2023
Learning Capacity: A Measure of the Effective Dimensionality of a Model
Learning Capacity: A Measure of the Effective Dimensionality of a Model
Daiwei Chen
Wei-Di Chang
Pratik Chaudhari
176
7
0
27 May 2023
Performance Limits of a Deep Learning-Enabled Text Semantic
  Communication under Interference
Performance Limits of a Deep Learning-Enabled Text Semantic Communication under InterferenceIEEE Transactions on Wireless Communications (IEEE TWC), 2023
T. Getu
Walid Saad
Georges Kaddoum
M. Bennis
258
15
0
15 Feb 2023
Implicit regularization in Heavy-ball momentum accelerated stochastic
  gradient descent
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descentInternational Conference on Learning Representations (ICLR), 2023
Avrajit Ghosh
He Lyu
Xitong Zhang
Rongrong Wang
269
27
0
02 Feb 2023
Deep networks for system identification: a Survey
Deep networks for system identification: a Survey
G. Pillonetto
Aleksandr Aravkin
Daniel Gedon
L. Ljung
Antônio H. Ribeiro
Thomas B. Schon
OOD
367
98
0
30 Jan 2023
Norm-based Generalization Bounds for Compositionally Sparse Neural
  Networks
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks
Tomer Galanti
Mengjia Xu
Liane Galanti
T. Poggio
210
9
0
28 Jan 2023
Deep Learning Meets Sparse Regularization: A Signal Processing
  Perspective
Deep Learning Meets Sparse Regularization: A Signal Processing PerspectiveIEEE Signal Processing Magazine (IEEE Signal Process. Mag.), 2023
Rahul Parhi
Robert D. Nowak
393
35
0
23 Jan 2023
Exploring the Approximation Capabilities of Multiplicative Neural
  Networks for Smooth Functions
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions
Ido Ben-Shaul
Tomer Galanti
S. Dekel
319
4
0
11 Jan 2023
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix
  Factorization
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
JIAN-PENG Cao
Chao Qian
Yihui Huang
Dicheng Chen
Yuncheng Gao
Jiyang Dong
D. Guo
X. Qu
392
1
0
29 Dec 2022
Quantum Policy Gradient Algorithm with Optimized Action Decoding
Quantum Policy Gradient Algorithm with Optimized Action DecodingInternational Conference on Machine Learning (ICML), 2022
Nico Meyer
Daniel D. Scherer
Axel Plinge
Christopher Mutschler
M. Hartmann
246
29
0
13 Dec 2022
Super-model ecosystem: A domain-adaptation perspective
Super-model ecosystem: A domain-adaptation perspective
Fengxiang He
Dacheng Tao
DiffM
191
1
0
30 Aug 2022
What Can Be Learnt With Wide Convolutional Neural Networks?
What Can Be Learnt With Wide Convolutional Neural Networks?International Conference on Machine Learning (ICML), 2022
Francesco Cagnetta
Alessandro Favero
Matthieu Wyart
MLT
655
16
0
01 Aug 2022
Biologically Plausible Training of Deep Neural Networks Using a Top-down
  Credit Assignment Network
Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network
Jian-Hui Chen
Cheng-Lin Liu
Zuoren Wang
272
0
0
01 Aug 2022
Blind Estimation of a Doubly Selective OFDM Channel: A Deep Learning
  Algorithm and Theory
Blind Estimation of a Doubly Selective OFDM Channel: A Deep Learning Algorithm and Theory
T. Getu
N. Golmie
D. Griffith
222
2
0
30 May 2022
A Falsificationist Account of Artificial Neural Networks
A Falsificationist Account of Artificial Neural NetworksBritish Journal for the Philosophy of Science (BJPS), 2022
O. Buchholz
Eric Raidl
AI4CE
142
7
0
03 May 2022
On the influence of over-parameterization in manifold based surrogates
  and deep neural operators
On the influence of over-parameterization in manifold based surrogates and deep neural operatorsJournal of Computational Physics (JCP), 2022
Katiana Kontolati
S. Goswami
Michael D. Shields
George Karniadakis
308
51
0
09 Mar 2022
Explicit Regularization via Regularizer Mirror Descent
Explicit Regularization via Regularizer Mirror Descent
Navid Azizan
Sahin Lale
B. Hassibi
137
5
0
22 Feb 2022
The learning phases in NN: From Fitting the Majority to Fitting a Few
The learning phases in NN: From Fitting the Majority to Fitting a Few
Johannes Schneider
214
0
0
16 Feb 2022
Neural Capacitance: A New Perspective of Neural Network Selection via
  Edge Dynamics
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics
Chunheng Jiang
Tejaswini Pedapati
Pin-Yu Chen
Luke Huan
Jianxi Gao
240
2
0
11 Jan 2022
Federated Optimization of Smooth Loss Functions
Federated Optimization of Smooth Loss FunctionsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Ali Jadbabaie
A. Makur
Devavrat Shah
FedML
724
10
0
06 Jan 2022
On the Role of Neural Collapse in Transfer Learning
On the Role of Neural Collapse in Transfer LearningInternational Conference on Learning Representations (ICLR), 2021
Tomer Galanti
András Gyorgy
Marcus Hutter
SSL
298
111
0
30 Dec 2021
Towards the One Learning Algorithm Hypothesis: A System-theoretic
  Approach
Towards the One Learning Algorithm Hypothesis: A System-theoretic Approach
Christos N. Mavridis
John S. Baras
171
1
0
04 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU
  Neural Networks
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks
T. Getu
241
2
0
25 Nov 2021
Conditionally Gaussian PAC-Bayes
Conditionally Gaussian PAC-BayesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Eugenio Clerico
George Deligiannidis
Arnaud Doucet
301
11
0
22 Oct 2021
The Tensor Brain: A Unified Theory of Perception, Memory and Semantic
  Decoding
The Tensor Brain: A Unified Theory of Perception, Memory and Semantic DecodingNeural Computation (Neural Comput.), 2021
Volker Tresp
Sahand Sharifzadeh
Hang Li
Dario Konopatzki
Yunpu Ma
326
8
0
27 Sep 2021
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