Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization

25 August 2019

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

50 / 72 papers shown

Title
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture Zuyu Xu Bin Lv 41 0 0 30 Mar 2025
A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks Quan Long Bin Wang Bing Xue Mengjie Zhang 53 0 0 29 Jan 2025
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification Ashim Dahal Saydul Akbar Murad Nick Rahimi 42 0 0 27 Jan 2025
Dissecting a Small Artificial Neural Network Xiguang Yang Krish Arora Michael Bachmann 32 0 0 03 Jan 2025
Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning Carlos Huertas LMTD 56 1 0 06 Nov 2024
A resource-efficient model for deep kernel learning Luisa DÁmore 24 0 0 13 Oct 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 98 485 0 30 Apr 2024
Training all-mechanical neural networks for task learning through in situ backpropagation Shuaifeng Li Xiaoming Mao AI4CE 37 1 0 23 Apr 2024
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 34 1 0 20 Apr 2024
A Unified Kernel for Neural Network Learning Shao-Qun Zhang Zong-Yi Chen Yong-Ming Tian Xun Lu 29 1 0 26 Mar 2024
Beyond Single-Model Views for Deep Learning: Optimization versus Generalizability of Stochastic Optimization Algorithms Toki Tahmid Inan Mingrui Liu Amarda Shehu 36 0 0 01 Mar 2024
Surfing the modeling of PoS taggers in low-resource scenarios M. Ferro V. Darriba F. J. Ribadas J. G. Gil 19 0 0 04 Feb 2024
Understanding and Leveraging the Learning Phases of Neural Networks Johannes Schneider Mohit Prabhushankar AI4CE 19 1 0 11 Dec 2023
Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review M. Lê Pierre Wolinski Julyan Arbel 36 8 0 20 Nov 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 40 1 0 13 Sep 2023
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space Zhengdao Chen 44 1 0 03 Jul 2023
Why do CNNs excel at feature extraction? A mathematical explanation V. Nandakumar Arush Tagade Tongliang Liu FAtt 11 0 0 03 Jul 2023
Homological Neural Networks: A Sparse Architecture for Multivariate Complexity Yuanrong Wang Antonio Briola T. Aste 46 6 0 27 Jun 2023
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits Zhuokai Zhao Takumi Matsuzawa W. Irvine Michael Maire G. Kindlmann 54 2 0 31 May 2023
Learning Capacity: A Measure of the Effective Dimensionality of a Model Daiwei Chen Wei-Di Chang Pratik Chaudhari 37 3 0 27 May 2023
Performance Limits of a Deep Learning-Enabled Text Semantic Communication under Interference T. Getu Walid Saad Georges Kaddoum M. Bennis 26 8 0 15 Feb 2023
Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent Avrajit Ghosh He Lyu Xitong Zhang Rongrong Wang 53 21 0 02 Feb 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 37 36 0 30 Jan 2023
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks Tomer Galanti Mengjia Xu Liane Galanti T. Poggio 38 9 0 28 Jan 2023
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective Rahul Parhi Robert D. Nowak 43 25 0 23 Jan 2023
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions Ido Ben-Shaul Tomer Galanti S. Dekel 31 3 0 11 Jan 2023
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 24 1 0 29 Dec 2022
Quantum Policy Gradient Algorithm with Optimized Action Decoding Nico Meyer Daniel D. Scherer Axel Plinge Christopher Mutschler M. Hartmann 29 20 0 13 Dec 2022
Super-model ecosystem: A domain-adaptation perspective Fengxiang He Dacheng Tao DiffM 35 1 0 30 Aug 2022
What Can Be Learnt With Wide Convolutional Neural Networks? Francesco Cagnetta Alessandro Favero M. Wyart MLT 41 12 0 01 Aug 2022
Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network Jian-Hui Chen Cheng-Lin Liu Zuoren Wang 26 0 0 01 Aug 2022
Blind Estimation of a Doubly Selective OFDM Channel: A Deep Learning Algorithm and Theory T. Getu N. Golmie D. Griffith 22 2 0 30 May 2022
A Falsificationist Account of Artificial Neural Networks O. Buchholz Eric Raidl AI4CE 17 4 0 03 May 2022
On the influence of over-parameterization in manifold based surrogates and deep neural operators Katiana Kontolati S. Goswami Michael D. Shields George Karniadakis 17 41 0 09 Mar 2022
Explicit Regularization via Regularizer Mirror Descent Navid Azizan Sahin Lale B. Hassibi 20 4 0 22 Feb 2022
The learning phases in NN: From Fitting the Majority to Fitting a Few Johannes Schneider 14 0 0 16 Feb 2022
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics Chunheng Jiang Tejaswini Pedapati Pin-Yu Chen Yizhou Sun Jianxi Gao 24 2 0 11 Jan 2022
Federated Optimization of Smooth Loss Functions Ali Jadbabaie A. Makur Devavrat Shah FedML 24 7 0 06 Jan 2022
On the Role of Neural Collapse in Transfer Learning Tomer Galanti András Gyorgy Marcus Hutter SSL 21 88 0 30 Dec 2021
Towards the One Learning Algorithm Hypothesis: A System-theoretic Approach Christos N. Mavridis John S. Baras 26 1 0 04 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks T. Getu 27 2 0 25 Nov 2021
Conditionally Gaussian PAC-Bayes Eugenio Clerico George Deligiannidis Arnaud Doucet 37 10 0 22 Oct 2021
The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding Volker Tresp Sahand Sharifzadeh Hang Li Dario Konopatzki Yunpu Ma 30 5 0 27 Sep 2021
Task Guided Compositional Representation Learning for ZDA Shuang Liu Mete Ozay OOD 25 0 0 13 Sep 2021
Towards Understanding Theoretical Advantages of Complex-Reaction Networks Shao-Qun Zhang Gaoxin Wei Zhi-Hua Zhou 23 17 0 15 Aug 2021
Distribution of Classification Margins: Are All Data Equal? Andrzej Banburski Fernanda De La Torre Nishka Pant Ishana Shastri T. Poggio 33 4 0 21 Jul 2021
Convergence rates for shallow neural networks learned by gradient descent Alina Braun Michael Kohler S. Langer Harro Walk 22 10 0 20 Jul 2021
Estimation of a regression function on a manifold by fully connected deep neural networks Michael Kohler S. Langer U. Reif 22 4 0 20 Jul 2021
Theory of Deep Convolutional Neural Networks III: Approximating Radial Functions Tong Mao Zhongjie Shi Ding-Xuan Zhou 16 33 0 02 Jul 2021
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks S. Lorenzen Christian Igel M. Nielsen MQ 11 17 0 24 Jun 2021