Spectrally-normalized margin bounds for neural networks

26 June 2017

Papers citing "Spectrally-normalized margin bounds for neural networks"

50 / 803 papers shown

Title
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond Xingguo Li Junwei Lu Zhaoran Wang Jarvis D. Haupt T. Zhao 25 78 0 13 Jun 2018
Data augmentation instead of explicit regularization Alex Hernández-García Peter König 30 141 0 11 Jun 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 14 373 0 08 Jun 2018
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach Ryo Karakida S. Akaho S. Amari FedML 27 140 0 04 Jun 2018
Minnorm training: an algorithm for training over-parameterized deep neural networks Yamini Bansal Madhu S. Advani David D. Cox Andrew M. Saxe ODL 13 18 0 03 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 19 9 0 01 Jun 2018
Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis Frederic Koehler Andrej Risteski 11 12 0 29 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 17 515 0 28 May 2018
The Singular Values of Convolutional Layers Hanie Sedghi Vineet Gupta Philip M. Long FAtt 31 200 0 26 May 2018
Step Size Matters in Deep Learning Kamil Nar S. Shankar Sastry 11 41 0 22 May 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 16 225 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 13 57 0 21 May 2018
A Study on Overfitting in Deep Reinforcement Learning Chiyuan Zhang Oriol Vinyals Rémi Munos Samy Bengio OffRL OnRL 16 383 0 18 Apr 2018
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou Victor Veitch Morgane Austern Ryan P. Adams Peter Orbanz 27 209 0 16 Apr 2018
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal Lucas Liebenwein Igor Gilitschenski Dan Feldman Daniela Rus 10 79 0 15 Apr 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity H. Gouk E. Frank Bernhard Pfahringer M. Cree 10 466 0 12 Apr 2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization Jiong Zhang Qi Lei Inderjit S. Dhillon 12 110 0 25 Mar 2018
Residual Networks: Lyapunov Stability and Convex Decomposition Kamil Nar S. Shankar Sastry ODL 14 3 0 22 Mar 2018
Information Theoretic Interpretation of Deep learning Tianchen Zhao FAtt 18 2 0 21 Mar 2018
FeTa: A DCA Pruning Algorithm with Generalization Error Guarantees Konstantinos Pitas Mike Davies P. Vandergheynst 13 2 0 12 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du J. Lee 16 267 0 03 Mar 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 13 435 0 23 Feb 2018
Asynchronous Byzantine Machine Learning (the case of SGD) Georgios Damaskinos El-Mahdi El-Mhamdi R. Guerraoui Rhicheek Patra Mahsa Taziki FedML 26 42 0 22 Feb 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 17 74 0 22 Feb 2018
Generalization in Machine Learning via Analytical Learning Theory Kenji Kawaguchi Yoshua Bengio Vikas Verma Leslie Pack Kaelbling 19 10 0 21 Feb 2018
Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization Yi Zhou Yingbin Liang Huishuai Zhang MLT 21 26 0 19 Feb 2018
Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy H. Fu Yuejie Chi Yingbin Liang FedML 16 39 0 18 Feb 2018
The Role of Information Complexity and Randomization in Representation Learning Matías Vera Pablo Piantanida L. Rey Vega 35 14 0 14 Feb 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 19 630 0 14 Feb 2018
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent Yifan Wu Barnabás Póczós Aarti Singh MLT 19 8 0 13 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 33 296 0 12 Feb 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 11 414 0 05 Feb 2018
Learning Compact Neural Networks with Regularization Samet Oymak MLT 35 39 0 05 Feb 2018
Fix your classifier: the marginal value of training the last weight layer Elad Hoffer Itay Hubara Daniel Soudry 27 101 0 14 Jan 2018
Theory of Deep Learning III: explaining the non-overfitting puzzle T. Poggio Kenji Kawaguchi Q. Liao Brando Miranda Lorenzo Rosasco Xavier Boix Jack Hidary H. Mhaskar ODL 16 128 0 30 Dec 2017
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 22 144 0 26 Dec 2017
Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations Yuanzhi Li Tengyu Ma Hongyang R. Zhang 18 31 0 26 Dec 2017
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning Siyuan Ma Raef Bassily M. Belkin 19 285 0 18 Dec 2017
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 19 543 0 18 Dec 2017
On the Discrimination-Generalization Tradeoff in GANs Pengchuan Zhang Qiang Liu Dengyong Zhou Tao Xu Xiaodong He 16 103 0 07 Nov 2017
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks Tengyuan Liang T. Poggio Alexander Rakhlin J. Stokes 25 224 0 05 Nov 2017
Network-size independent covering number bounds for deep networks Mayank Kabra K. Branson 16 0 0 02 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 38 854 0 29 Oct 2017
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data Alon Brutzkus Amir Globerson Eran Malach Shai Shalev-Shwartz MLT 37 276 0 27 Oct 2017
Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior Charles H. Martin Michael W. Mahoney AI4CE 22 62 0 26 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 52 9,587 0 25 Oct 2017
Implicit Regularization in Deep Learning Behnam Neyshabur 17 145 0 06 Sep 2017
The duality structure gradient descent algorithm: analysis and applications to neural networks Thomas Flynn 12 1 0 01 Aug 2017
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks Behnam Neyshabur Srinadh Bhojanapalli Nathan Srebro 14 600 0 29 Jul 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard J. Lee 27 414 0 16 Jul 2017