Benefits of depth in neural networks

14 February 2016

Papers citing "Benefits of depth in neural networks"

50 / 353 papers shown

Title
Generalization and Expressivity for Deep Nets Shao-Bo Lin 16 45 0 10 Mar 2018
Some Approximation Bounds for Deep Networks B. McCane Lech Szymanski 13 1 0 08 Mar 2018
The emergent algebraic structure of RNNs and embeddings in NLP Sean A. Cantrell 22 2 0 07 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du J. Lee 16 267 0 03 Mar 2018
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions Quynh N. Nguyen Mahesh Chandra Mukkamala Matthias Hein MLT 19 54 0 28 Feb 2018
Limits on representing Boolean functions by linear combinations of simple functions: thresholds, ReLUs, and low-degree polynomials Richard Ryan Williams 25 26 0 26 Feb 2018
Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy H. Fu Yuejie Chi Yingbin Liang FedML 19 39 0 18 Feb 2018
The Role of Information Complexity and Randomization in Representation Learning Matías Vera Pablo Piantanida L. Rey Vega 37 14 0 14 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 13 293 0 10 Feb 2018
Deep Learning Works in Practice. But Does it Work in Theory? L. Hoang R. Guerraoui PINN 28 3 0 31 Jan 2018
Lower bounds over Boolean inputs for deep neural networks with ReLU gates Anirbit Mukherjee A. Basu 20 20 0 08 Nov 2017
Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels Kai Zhong Zhao-quan Song Inderjit S. Dhillon 28 75 0 08 Nov 2017
Approximating Continuous Functions by ReLU Nets of Minimal Width Boris Hanin Mark Sellke 31 229 0 31 Oct 2017
Optimization Landscape and Expressivity of Deep CNNs Quynh N. Nguyen Matthias Hein 22 29 0 30 Oct 2017
Generalization in Deep Learning Kenji Kawaguchi L. Kaelbling Yoshua Bengio ODL 28 460 0 16 Oct 2017
Porcupine Neural Networks: (Almost) All Local Optima are Global S. Feizi Hamid Javadi Jesse M. Zhang David Tse 15 36 0 05 Oct 2017
Learning hard quantum distributions with variational autoencoders Andrea Rocchetto Edward Grant Sergii Strelchuk Giuseppe Carleo Simone Severini BDL DRL 22 76 0 02 Oct 2017
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P. Petersen Felix Voigtländer 76 470 0 15 Sep 2017
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 6 879 0 08 Sep 2017
Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks Zheng Xu Yen-Chang Hsu Jiawei Huang GAN 21 12 0 02 Sep 2017
A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community John E. Ball Derek T. Anderson Chee Seng Chan 27 521 0 01 Sep 2017
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 14 796 0 22 Aug 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard J. Lee 36 415 0 16 Jul 2017
On the Complexity of Learning Neural Networks Le Song Santosh Vempala John Wilmes Bo Xie 6 59 0 14 Jul 2017
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems J. C. Ye Yoseob Han Eunju Cha 36 16 0 03 Jul 2017
Neural networks and rational functions Matus Telgarsky 14 81 0 11 Jun 2017
Recovery Guarantees for One-hidden-layer Neural Networks Kai Zhong Zhao-quan Song Prateek Jain Peter L. Bartlett Inderjit S. Dhillon MLT 22 336 0 10 Jun 2017
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 21 174 0 16 May 2017
Detecting Statistical Interactions from Neural Network Weights Michael Tsang Dehua Cheng Yan Liu 25 192 0 14 May 2017
Deep Radial Kernel Networks: Approximating Radially Symmetric Functions with Deep Networks B. McCane Lech Szymanski 33 6 0 09 Mar 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian 16 423 0 08 Mar 2017
On the Expressive Power of Overlapping Architectures of Deep Learning Or Sharir Amnon Shashua 11 10 0 06 Mar 2017
Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction Eunhee Kang Junhong Min J. C. Ye MedIm OOD 30 61 0 04 Mar 2017
Deep artifact learning for compressed sensing and parallel MRI Dongwook Lee J. Yoo J. C. Ye MedIm 27 36 0 03 Mar 2017
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank Liang Zhao Siyu Liao Yanzhi Wang Zhe Li Jian Tang Victor Pan Bo Yuan 31 61 0 01 Mar 2017
Deep Semi-Random Features for Nonlinear Function Approximation Kenji Kawaguchi Bo Xie Vikas Verma Le Song 13 15 0 28 Feb 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question? David Balduzzi Marcus Frean Lennox Leary J. P. Lewis Kurt Wan-Duo Ma Brian McWilliams ODL 6 397 0 28 Feb 2017
On the ability of neural nets to express distributions Holden Lee Rong Ge Tengyu Ma Andrej Risteski Sanjeev Arora BDL 10 84 0 22 Feb 2017
Deep Learning and Hierarchal Generative Models Elchanan Mossel BDL GAN 12 23 0 29 Dec 2016
Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis Yoseob Han J. Yoo J. C. Ye 32 203 0 19 Nov 2016
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification Woong Bae J. Yoo J. C. Ye SupR 16 176 0 19 Nov 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 32 4,588 0 10 Nov 2016
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks David Balduzzi Brian McWilliams T. Butler-Yeoman 19 28 0 07 Nov 2016
Understanding Deep Neural Networks with Rectified Linear Units R. Arora A. Basu Poorya Mianjy Anirbit Mukherjee PINN 30 633 0 04 Nov 2016
Learning Identity Mappings with Residual Gates Pedro H. P. Savarese Leonardo O. Mazza Daniel R. Figueiredo 23 5 0 04 Nov 2016
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks Itay Safran Ohad Shamir 18 174 0 31 Oct 2016
Why Deep Neural Networks for Function Approximation? Shiyu Liang R. Srikant 17 383 0 13 Oct 2016
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 25 1,221 0 03 Oct 2016
AdaNet: Adaptive Structural Learning of Artificial Neural Networks Corinna Cortes X. Gonzalvo Vitaly Kuznetsov M. Mohri Scott Yang 21 282 0 05 Jul 2016
Robust Large Margin Deep Neural Networks Jure Sokolić Raja Giryes Guillermo Sapiro M. Rodrigues 26 307 0 26 May 2016