SGD Learns the Conjugate Kernel Class of the Network

27 February 2017

Papers citing "SGD Learns the Conjugate Kernel Class of the Network"

30 / 130 papers shown

Title
Decoupling Gating from Linearity Jonathan Fiat Eran Malach Shai Shalev-Shwartz 17 28 0 12 Jun 2019
Deep Reinforcement Learning for Unmanned Aerial Vehicle-Assisted Vehicular Networks M. Zhu Xiao-Yang Liu Xiaodong Wang 30 16 0 12 Jun 2019
Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound Zhao Song Xin Yang 23 91 0 09 Jun 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao Quanquan Gu MLT AI4CE 37 383 0 30 May 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 24 183 0 24 May 2019
Neural Temporal-Difference and Q-Learning Provably Converge to Global Optima Qi Cai Zhuoran Yang Jason D. Lee Zhaoran Wang 42 29 0 24 May 2019
On Exact Computation with an Infinitely Wide Neural Net Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang 65 906 0 26 Apr 2019
Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections E. Weinan Chao Ma Qingcan Wang Lei Wu MLT 37 22 0 10 Apr 2019
A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics E. Weinan Chao Ma Lei Wu MLT 27 122 0 08 Apr 2019
On the Power and Limitations of Random Features for Understanding Neural Networks Gilad Yehudai Ohad Shamir MLT 28 181 0 01 Apr 2019
Theory III: Dynamics and Generalization in Deep Networks Andrzej Banburski Q. Liao Brando Miranda Lorenzo Rosasco Fernanda De La Torre Jack Hidary T. Poggio AI4CE 35 3 0 12 Mar 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 57 1,080 0 18 Feb 2019
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao Quanquan Gu ODL MLT AI4CE 25 155 0 04 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
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 41 765 0 12 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization Zeyuan Allen-Zhu Yuanzhi Li Zhao Song AI4CE ODL 72 1,448 0 09 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,126 0 09 Nov 2018
On the Convergence Rate of Training Recurrent Neural Networks Zeyuan Allen-Zhu Yuanzhi Li Zhao Song 32 191 0 29 Oct 2018
A Priori Estimates of the Population Risk for Two-layer Neural Networks Weinan E Chao Ma Lei Wu 29 130 0 15 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 28 245 0 12 Oct 2018
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem Alon Brutzkus Amir Globerson MLT 19 7 0 06 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 65 1,252 0 04 Oct 2018
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds Santosh Vempala John Wilmes MLT 22 50 0 07 May 2018
A Provably Correct Algorithm for Deep Learning that Actually Works Eran Malach Shai Shalev-Shwartz MLT 24 30 0 26 Mar 2018
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks Peter L. Bartlett D. Helmbold Philip M. Long 36 116 0 16 Feb 2018
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 23 545 0 18 Dec 2017
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks Surbhi Goel Adam R. Klivans 30 27 0 11 Aug 2017
Weight Sharing is Crucial to Succesful Optimization Shai Shalev-Shwartz Ohad Shamir Shaked Shammah 44 12 0 02 Jun 2017
Random Features for Compositional Kernels Amit Daniely Roy Frostig Vineet Gupta Y. Singer CoGe 24 19 0 22 Mar 2017
Convergence Results for Neural Networks via Electrodynamics Rina Panigrahy Sushant Sachdeva Qiuyi Zhang MLT MDE 32 22 0 01 Feb 2017