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"

9 / 109 papers shown

Title
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 28 117 0 17 Oct 2018
Learning Compressed Transforms with Low Displacement Rank Anna T. Thomas Albert Gu Tri Dao Atri Rudra Christopher Ré 27 40 0 04 Oct 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 18 226 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 21 57 0 21 May 2018
Functional Gradient Boosting based on Residual Network Perception Atsushi Nitanda Taiji Suzuki 25 25 0 25 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 27 74 0 15 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 27 294 0 10 Feb 2018
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 104 1,237 0 27 Jun 2017
Benefits of depth in neural networks Matus Telgarsky 153 603 0 14 Feb 2016