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 / 109 papers shown

Title
Is Out-of-Distribution Detection Learnable? Zhen Fang Yixuan Li Jie Lu Jiahua Dong Bo Han Feng Liu OODD 39 125 0 26 Oct 2022
The Curious Case of Benign Memorization Sotiris Anagnostidis Gregor Bachmann Lorenzo Noci Thomas Hofmann AAML 54 8 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 28 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 57 31 0 27 Sep 2022
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois Tatsunori Hashimoto Stefano Ermon Percy Liang SSL 83 41 0 13 Sep 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 19 11 0 16 Aug 2022
Large Language Models and the Reverse Turing Test T. Sejnowski ELM 28 107 0 28 Jul 2022
Deep Sufficient Representation Learning via Mutual Information Siming Zheng Yuanyuan Lin Jian Huang SSL DRL 47 0 0 21 Jul 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 33 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 32 7 0 09 Jun 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong J. Hopcroft Liwei Wang OOD 82 27 0 27 May 2022
Learning ReLU networks to high uniform accuracy is intractable Julius Berner Philipp Grohs F. Voigtlaender 32 4 0 26 May 2022
How do noise tails impact on deep ReLU networks? Jianqing Fan Yihong Gu Wen-Xin Zhou ODL 41 13 0 20 Mar 2022
Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering Ramin Raziperchikolaei Young-joo Chung 27 2 0 14 Mar 2022
Estimating a regression function in exponential families by model selection Juntong Chen 22 2 0 13 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 67 7 0 07 Mar 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 54 20 0 31 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 32 36 0 01 Jan 2022
Neural networks with linear threshold activations: structure and algorithms Sammy Khalife Hongyu Cheng A. Basu 42 14 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 25 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
Provable Lifelong Learning of Representations Xinyuan Cao Weiyang Liu Santosh Vempala CLL 25 13 0 27 Oct 2021
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 10 41 0 19 Oct 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 25 1 0 06 Oct 2021
Learning the hypotheses space from data through a U-curve algorithm Diego Marcondes Adilson Simonis Junior Barrera 39 1 0 08 Sep 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 33 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 37 5 0 03 Jul 2021
Deep Generative Learning via Schrödinger Bridge Gefei Wang Yuling Jiao Qiang Xu Yang Wang Can Yang DiffM OT 23 92 0 19 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 29 43 0 12 Jun 2021
Quantifying and Improving Transferability in Domain Generalization Guojun Zhang Han Zhao Yaoliang Yu Pascal Poupart 40 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 20 39 0 16 Apr 2021
Generalization bounds via distillation Daniel J. Hsu Ziwei Ji Matus Telgarsky Lan Wang FedML 25 32 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 31 34 0 06 Apr 2021
Fast Jacobian-Vector Product for Deep Networks Randall Balestriero Richard Baraniuk 31 4 0 01 Apr 2021
Quantitative approximation results for complex-valued neural networks A. Caragea D. Lee J. Maly G. Pfander F. Voigtlaender 13 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 25 81 0 21 Dec 2020
Computational Separation Between Convolutional and Fully-Connected Networks Eran Malach Shai Shalev-Shwartz 24 26 0 03 Oct 2020
The Kolmogorov-Arnold representation theorem revisited Johannes Schmidt-Hieber 30 126 0 31 Jul 2020
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training Andrea Montanari Yiqiao Zhong 49 95 0 25 Jul 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 34 14 0 25 May 2020
Learning the gravitational force law and other analytic functions Atish Agarwala Abhimanyu Das Rina Panigrahy Qiuyi Zhang MLT 16 0 0 15 May 2020
On Deep Instrumental Variables Estimate Ruiqi Liu Zuofeng Shang Guang Cheng 26 26 0 30 Apr 2020
Memory capacity of neural networks with threshold and ReLU activations Roman Vershynin 31 21 0 20 Jan 2020
Deep Gamblers: Learning to Abstain with Portfolio Theory Liu Ziyin Zhikang T. Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda 23 110 0 29 Jun 2019
The phase diagram of approximation rates for deep neural networks Dmitry Yarotsky Anton Zhevnerchuk 30 121 0 22 Jun 2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks Yaoyu Zhang Zhi-Qin John Xu Tao Luo Zheng Ma MLT AI4CE 39 38 0 24 May 2019
A lattice-based approach to the expressivity of deep ReLU neural networks V. Corlay J. Boutros P. Ciblat L. Brunel 27 4 0 28 Feb 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 55 961 0 24 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Tao Luo Yan Xiao Zheng Ma 23 503 0 19 Jan 2019
On the potential for open-endedness in neural networks N. Guttenberg N. Virgo A. Penn 21 10 0 12 Dec 2018