Summary of Thermodynamic Natural Gradient Descent, by Kaelan Donatella et al.
Thermodynamic Natural Gradient Descentby Kaelan Donatella, Samuel Duffield, Maxwell Aifer, Denis Melanson, Gavin Crooks, Patrick…
Summary of On the Stability Of Gradient Descent with Second Order Dynamics For Time-varying Cost Functions, by Travis E. Gibson et al.
On the stability of gradient descent with second order dynamics for time-varying cost functionsby Travis…
Summary of Deep Linear Networks For Regression Are Implicitly Regularized Towards Flat Minima, by Pierre Marion et al.
Deep linear networks for regression are implicitly regularized towards flat minimaby Pierre Marion, Lénaïc ChizatFirst…
Summary of Fadam: Adam Is a Natural Gradient Optimizer Using Diagonal Empirical Fisher Information, by Dongseong Hwang
FAdam: Adam is a natural gradient optimizer using diagonal empirical Fisher informationby Dongseong HwangFirst submitted…
Summary of Approximation and Gradient Descent Training with Neural Networks, by G. Welper
Approximation and Gradient Descent Training with Neural Networksby G. WelperFirst submitted to arxiv on: 19…
Summary of Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model, by Chenyin Gao et al.
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Modelby Chenyin Gao, Zhiming Zhang, Shu…
Summary of Adjacent Leader Decentralized Stochastic Gradient Descent, by Haoze He et al.
Adjacent Leader Decentralized Stochastic Gradient Descentby Haoze He, Jing Wang, Anna ChoromanskaFirst submitted to arxiv…
Summary of Nonparametric Teaching Of Implicit Neural Representations, by Chen Zhang et al.
Nonparametric Teaching of Implicit Neural Representationsby Chen Zhang, Steven Tin Sui Luo, Jason Chun Lok…
Summary of Learning Multi-agent Communication From Graph Modeling Perspective, by Shengchao Hu et al.
Learning Multi-Agent Communication from Graph Modeling Perspectiveby Shengchao Hu, Li Shen, Ya Zhang, Dacheng TaoFirst…
Summary of Analysis Of the Rate Of Convergence Of An Over-parametrized Convolutional Neural Network Image Classifier Learned by Gradient Descent, By Michael Kohler et al.
Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned…