GPTQ运用海塞矩阵找下一个量化权重,论文中没有相关证明。因此翻阅OBD和OBS论文,OBD是这篇Yann Le Cun 1989年的论文(彼时还在贝尔实验室)。总体感觉上下文说明比较多,比较容易读懂。 Optimal Brain Damage,可顾名思义,最优大脑损坏,大脑神经元如果要选择损坏一部分权重,应该去掉哪些?就是经典的神经元剪枝问题。剪枝...
ResearchGate链接:https://www.researchgate.net/publication/3568764_Optimal_Brain_Surgeon_and_general_network_pruning OBS表示它不只做damage,还会做外科手术,它把一个权重调到0,会顺带把其他权重做自动调整,从而也无需做增量重训。 回到OBD的论文中的方程(1): 右边第一项和第三项,忽略;OBD假设H(i,j)为0(i!
OptimalBrainDamage-UniversityofMinnesotaDuluth 系统标签: brainoptimalduluthdamageminnesotaobd OptimalBrainDamage YannLeCun,JohnS.DenkerandSaraA.Solla presentedby ChaitanyaPolumetla Overview • Introduction • NeedforOBD • TheIdea • AuthorsProposal • WhyOBDcouldwork? • Experiments • Results ...
In order to reduce the number of model parameters (i.e. the number of weights), the Optimal Brain Damage (OBD) pruning algorithm is adopted for the recurrent neural models. Efficiency of the OBD algorithm is demonstrated for pruning neural models of a neutralisation reactor benchmark process. ...
We have used Optimal Brain Damage interactively to reduce the number of parameters in a practical neural network by a factor of four. We obtained an additional factor of more than two by using OBD to delete parameters automatically. The network's speed improved signi cantly, and its ...
Optimal Brain Damage (OBD) is a method for reducing the number of weights in a neural network. OBD estimates the increase in cost function if weights are pruned and is a valid approximation if the learning algorithm has converged into a ... V Tresp,R Neuneier,HG Zimmermann 被引量: 28发...
Optimal Brain Damage (OBD) and Optimal Brain Surgeon (OBS) represent two popular pruning procedures; however, pruning large networks trained on voluminous data sets using these methods easily becomes intractable. We present a number of approximations and discuss practical issues in real-world pruning,...
The optimal brain damage (OBD) scheme of Le Cun, Denker and Solla for pruning of feedforward networks has been implemented and applied to the contiguity cl... J Gorodkin,LK Hansen,A Krogh,... - 《International Journal of Neural Systems》 被引量: 58发表: 1993年 Dept. of Electr. Eng....
OBD and SNIP remove weights closer to start. This is actually good as later weights are considered to be more important. Effect of extreme pruning percentages comparison a) Without retraining: SNIP was pruned at initialisation, rest are pruned after training. b) With retraining: Top-3 pruning ...
A quantitative study of pruning by optimal brain damage The optimal brain damage (OBD) scheme of Le Cun, Denker and Solla for pruning of feedforward networks has been implemented and applied to the contiguity cl... J Gorodkin,LK Hansen,A Krogh,... - 《International Journal of Neural System...