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"

25 / 125 papers shown

Title
Memory capacity of neural networks with threshold and ReLU activations Roman Vershynin 38 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 43 110 0 29 Jun 2019
The phase diagram of approximation rates for deep neural networks Dmitry Yarotsky Anton Zhevnerchuk 35 121 0 22 Jun 2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks Yaoyu Zhang Zhi-Qin John Xu Yaoyu Zhang Zheng Ma MLT AI4CE 61 38 0 24 May 2019
How degenerate is the parametrization of neural networks with the ReLU activation function? Julius Berner Dennis Elbrächter Philipp Grohs ODL 45 28 0 23 May 2019
A lattice-based approach to the expressivity of deep ReLU neural networks V. Corlay J. Boutros P. Ciblat L. Brunel 37 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 63 961 0 24 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 63 505 0 19 Jan 2019
The capacity of feedforward neural networks Pierre Baldi Roman Vershynin 25 67 0 02 Jan 2019
Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data Shenhao Wang Qingyi Wang Jinhuan Zhao AI4TS 25 21 0 02 Jan 2019
A Theoretical Analysis of Deep Q-Learning Jianqing Fan Zhuoran Yang Yuchen Xie Zhaoran Wang 48 598 0 01 Jan 2019
On the potential for open-endedness in neural networks N. Guttenberg N. Virgo A. Penn 28 10 0 12 Dec 2018
Deep Active Learning with a Neural Architecture Search Yonatan Geifman Ran El-Yaniv AI4CE 22 44 0 19 Nov 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 39 117 0 17 Oct 2018
Learning Compressed Transforms with Low Displacement Rank Anna T. Thomas Albert Gu Tri Dao Atri Rudra Christopher Ré 32 40 0 04 Oct 2018
Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations Julius Berner Philipp Grohs Arnulf Jentzen 29 182 0 09 Sep 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 23 228 0 22 May 2018
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? S. Du Yining Wang Xiyu Zhai Sivaraman Balakrishnan Ruslan Salakhutdinov Aarti Singh SSL 39 57 0 21 May 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du Jason D. Lee 62 268 0 03 Mar 2018
Functional Gradient Boosting based on Residual Network Perception Atsushi Nitanda Taiji Suzuki 25 27 0 25 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 33 76 0 15 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 32 294 0 10 Feb 2018
Implicit Regularization in Deep Learning Behnam Neyshabur 17 145 0 06 Sep 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 110 1,241 0 27 Jun 2017
Benefits of depth in neural networks Matus Telgarsky 195 606 0 14 Feb 2016