Federal learning: dividing non IID samples by mixed distribution

We're blogging Federal learning: dividing non IID samples by ill conditioned independent identically distributed We have studied the division of samples according to pathological non IID in the paper of the founding of federal learning [1]. In the last blog post Federal learning: dividing non IID samples by Dirichlet distribution We have also m ...

Added by new7media on Thu, 10 Mar 2022 15:54:05 +0200

[traffic sign recognition] traffic sign recognition in haze weather based on matlab GUI BP neural network (with panel) [including Matlab source code phase 1771]

1, Brief introduction of BP neural network traffic sign recognition Road traffic signs are used to prohibit, warn, instruct and restrict road users to use roads in an orderly manner to ensure travel safety If the road traffic signs can be recognized automatically, the occurrence of road traffic accidents will be greatly reduced However, due to ...

Added by the182guy on Thu, 10 Mar 2022 10:19:15 +0200

DBMTL introduction and implementation of multitasking learning model

This paper introduces the multitasking learning algorithm published by Ali in 2019. The model shows the Bayesian network causality between targets, integrates and models the complex causality network between features and multiple targets, and eliminates the strong independent assumptions in the general MTL model. Since there is no specific assu ...

Added by rami on Thu, 10 Mar 2022 10:08:55 +0200

[source code analysis] NVIDIA HugeCTR, GPU version parameter server ----- Local hash table

[source code analysis] NVIDIA HugeCTR, GPU version parameter server -- (9) -- local hash table 0x00 summary In this series, we introduce HugeCTR, an industry-oriented recommendation system training framework, which is optimized for large-scale CTR models with model parallel embedding and data parallel intensive networks. This article introduce ...

Added by micah1701 on Wed, 09 Mar 2022 14:22:18 +0200

[GNN benchmark] Figure benchmark data set of machine learning

Figure ImageNet of neural network? Open source millions of OGB benchmark data sets such as Stanford University In the small data full of "MNIST", does graph neural network also need a big benchmark such as "ImageNet"? Recently, Professor Jure Leskovec of Stanford University announced the open source of Open Graph Benchmar ...

Added by scopley on Wed, 09 Mar 2022 09:47:27 +0200

Surface finishing plan - the third bullet

& & other algorithms 1, Algorithm Given an array of prices, its ith element price [i] represents the price of a given stock on day I. You can only choose to buy this stock one day and sell it on a different day in the future. Design an algorithm to calculate the maximum profit you can make. Return the maximum profit you can make ...

Added by srhino on Wed, 09 Mar 2022 09:29:10 +0200

Graphic big data | Spark machine learning - workflow and Feature Engineering

Author: Han Xinzi@ShowMeAI Tutorial address: http://www.showmeai.tech/tutorials/84 Article address: http://www.showmeai.tech/article-detail/180 Notice: All Rights Reserved. Please contact the platform and the author for reprint and indicate the source 1.Spark machine learning workflow 1) Spark mllib and ml Spark also has MLlib/ML for big d ...

Added by nunomira on Tue, 08 Mar 2022 18:14:48 +0200

[machine learning] how to use Bayes_opt, HyperOpt and Optuna realize parameter optimization? How to use Bayesian search to improve the speed of parameter optimization?

Contents of this chapter: How to use Bayes_opt to achieve parameter optimization, and cases?How to use HyperOpt to realize parameter optimization, and cases?How to use Optuna to realize parameter optimization, and cases? HPO LibraryPros and cons evaluationRecommendation Indexbayes_opt✅ Bayesian Optimization Based on Gaussian process ✅ When ...

Added by groberts23 on Tue, 08 Mar 2022 14:48:38 +0200

keras.layers.LSTM, Dense, etc. transfer input_ The shape parameter is given to the first layer

@Created on: 20210413 @Modified on: 20210413 1. Background At keras In the Sequential sequential model API of layers, the Sequential model is a linear stack of multiple network layers. You can pass the list of layers to the Sequential constructor. The methods and properties include: model.layers is a flattened list that contains the netw ...

Added by bandit8 on Tue, 08 Mar 2022 01:09:42 +0200

Reinforcement learning algorithm: PPO2 creates a bitcoin trading robot that won't lose money

Creating a bitcoin trading robot will not lose money In this article, we will create a deep reinforcement learning agent to learn to make money through bitcoin trading. In this tutorial, we will use the PPO agent in OpenAIgym and the stable baselines Library (a branch of OpenAI's baselines Library). The purpose of this series of articles is to ...

Added by decessus on Mon, 07 Mar 2022 21:53:14 +0200