Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets

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Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets

17 September 2023

Pulkit Gopalani

Anirbit Mukherjee

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Papers citing "Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets"

19 / 19 papers shown

Title
Classification of Data Generated by Gaussian Mixture Models Using Deep ReLU Networks Tiancong Zhou X. Huo 47 4 0 15 Aug 2023
Gradient descent provably escapes saddle points in the training of shallow ReLU networks Patrick Cheridito Arnulf Jentzen Florian Rossmannek 103 5 0 03 Aug 2022
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations? Niladri S. Chatterji Philip M. Long Peter L. Bartlett 42 12 0 09 Feb 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network Mo Zhou Rong Ge Chi Jin 126 46 0 04 Feb 2021
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks Cong Fang Jason D. Lee Pengkun Yang Tong Zhang OOD FedML 143 58 0 03 Jul 2020
Depth-2 Neural Networks Under a Data-Poisoning Attack Sayar Karmakar Anirbit Mukherjee Ramchandran Muthukumar 29 7 0 04 May 2020
Enhanced Convolutional Neural Tangent Kernels Zhiyuan Li Ruosong Wang Dingli Yu S. Du Wei Hu Ruslan Salakhutdinov Sanjeev Arora 68 133 0 03 Nov 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 402 183 0 24 May 2019
Mean Field Analysis of Deep Neural Networks Justin A. Sirignano K. Spiliopoulos 89 82 0 11 Mar 2019
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 111 840 0 19 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 203 775 0 12 Nov 2018
Learning Two-layer Neural Networks with Symmetric Inputs Rong Ge Rohith Kuditipudi Zhize Li Xiang Wang OOD MLT 201 59 0 16 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 250 245 0 12 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 245 1,276 0 04 Oct 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 109 863 0 18 Apr 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du Jason D. Lee 183 272 0 03 Mar 2018
Theory of Deep Learning IIb: Optimization Properties of SGD Chiyuan Zhang Q. Liao Alexander Rakhlin Brando Miranda Noah Golowich T. Poggio ODL 61 71 0 07 Jan 2018
Recovery Guarantees for One-hidden-layer Neural Networks Kai Zhong Zhao Song Prateek Jain Peter L. Bartlett Inderjit S. Dhillon MLT 183 337 0 10 Jun 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 84 521 0 13 Feb 2017

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