Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks

8 March 2017

Papers citing "Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks"

50 / 125 papers shown

Title
VC dimensions of group convolutional neural networks P. Petersen A. Sepliarskaia VLM 34 7 0 19 Dec 2022
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think Christian H. X. Ali Mehmeti-Göpel Jan Disselhoff 20 5 0 30 Nov 2022
Limitations on approximation by deep and shallow neural networks G. Petrova P. Wojtaszczyk 46 7 0 30 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 41 6 0 02 Nov 2022
Is Out-of-Distribution Detection Learnable? Zhen Fang Yixuan Li Jie Lu Jiahua Dong Bo Han Feng Liu OODD 52 125 0 26 Oct 2022
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 54 9 0 25 Oct 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 35 14 0 24 Oct 2022
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 65 31 0 27 Sep 2022
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois Tatsunori Hashimoto Stefano Ermon Percy Liang SSL 86 41 0 13 Sep 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 52 11 0 16 Aug 2022
Large Language Models and the Reverse Turing Test T. Sejnowski ELM 41 107 0 28 Jul 2022
Deep Sufficient Representation Learning via Mutual Information Siming Zheng Yuanyuan Lin Jian Huang SSL DRL 56 0 0 21 Jul 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 48 3 0 14 Jun 2022
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks El Mehdi Achour Armand Foucault Sébastien Gerchinovitz Franccois Malgouyres 44 7 0 09 Jun 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong John E. Hopcroft Liwei Wang OOD 87 27 0 27 May 2022
Learning ReLU networks to high uniform accuracy is intractable Julius Berner Philipp Grohs F. Voigtlaender 46 4 0 26 May 2022
Analysis of convolutional neural network image classifiers in a rotationally symmetric model Michael Kohler Benjamin Kohler 43 5 0 11 May 2022
How do noise tails impact on deep ReLU networks? Jianqing Fan Yihong Gu Wen-Xin Zhou ODL 50 13 0 20 Mar 2022
Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering Ramin Raziperchikolaei Young-joo Chung 32 2 0 14 Mar 2022
Estimating a regression function in exponential families by model selection Juntong Chen 41 2 0 13 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 97 7 0 07 Mar 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 61 20 0 31 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 54 37 0 01 Jan 2022
Neural networks with linear threshold activations: structure and algorithms Sammy Khalife Hongyu Cheng A. Basu 52 16 0 15 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 35 18 0 11 Nov 2021
Improved Regularization and Robustness for Fine-tuning in Neural Networks Dongyue Li Hongyang R. Zhang NoLa 55 56 0 08 Nov 2021
Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion Jean-Samuel Leboeuf F. Leblanc M. Marchand 17 0 0 29 Oct 2021
Provable Lifelong Learning of Representations Xinyuan Cao Weiyang Liu Santosh Vempala CLL 44 14 0 27 Oct 2021
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 20 42 0 19 Oct 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 59 1 0 06 Oct 2021
Learning the hypotheses space from data through a U-curve algorithm Diego Marcondes Adilson Simonis Junior Barrera 44 1 0 08 Sep 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 67 13 0 21 Jul 2021
Learning from scarce information: using synthetic data to classify Roman fine ware pottery Santos J. Núñez Jareño Daniël P. van Helden Evgeny M. Mirkes I. Tyukin Penelope Allison 42 5 0 03 Jul 2021
Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning Alberto Badías A. Banerjee 34 3 0 02 Jul 2021
Deep Generative Learning via Schrödinger Bridge Gefei Wang Yuling Jiao Qiang Xu Yang Wang Can Yang DiffM OT 33 94 0 19 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 41 44 0 12 Jun 2021
Quantifying and Improving Transferability in Domain Generalization Guojun Zhang Han Zhao Yaoliang Yu Pascal Poupart 58 37 0 07 Jun 2021
Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sums Guido Montúfar Yue Ren Leon Zhang 30 40 0 16 Apr 2021
Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors Yuling Jiao Guohao Shen Yuanyuan Lin Jian Huang 76 50 0 14 Apr 2021
Generalization bounds via distillation Daniel J. Hsu Ziwei Ji Matus Telgarsky Lan Wang FedML 39 33 0 12 Apr 2021
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces Philipp Grohs F. Voigtlaender 49 36 0 06 Apr 2021
Fast Jacobian-Vector Product for Deep Networks Randall Balestriero Richard Baraniuk 41 4 0 01 Apr 2021
Quantitative approximation results for complex-valued neural networks A. Caragea D. Lee J. Maly G. Pfander F. Voigtlaender 23 5 0 25 Feb 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks Quynh N. Nguyen Marco Mondelli Guido Montúfar 35 82 0 21 Dec 2020
Computational Separation Between Convolutional and Fully-Connected Networks Eran Malach Shai Shalev-Shwartz 37 26 0 03 Oct 2020
The Kolmogorov-Arnold representation theorem revisited Johannes Schmidt-Hieber 35 130 0 31 Jul 2020
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training Andrea Montanari Yiqiao Zhong 66 95 0 25 Jul 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 41 14 0 25 May 2020
Learning the gravitational force law and other analytic functions Atish Agarwala Abhimanyu Das Rina Panigrahy Qiuyi Zhang MLT 25 0 0 15 May 2020
On Deep Instrumental Variables Estimate Ruiqi Liu Zuofeng Shang Guang Cheng 31 26 0 30 Apr 2020