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googlesamples/android-Notifications: Demonstrates best practices for Android Notifications (including P features) on both mobile and/or Wear.
Demonstrates best practices for Android Notifications (including P features) on both mobile and/or Wear. - googlesamples/android-Notifications
android  notification  sample  project  google 
3 days ago by lgtout
The Sounds Of Hell Recorded By Miner In Siberia! - YouTube
Hosea 4:6 - My people are destroyed for lack of knowledge: because thou hast rejected knowledge, I will also reject thee, that thou shalt be no priest to me:...
sample 
8 days ago by thx1138
Build an ASP.NET app in Azure with SQL Database | Microsoft Docs
Learn how to deploy a C# ASP.NET app with a SQL Server database to Azure.
azure  database  asp.net  sample  demo  cloud  paas  microsoft 
14 days ago by geekzter
Kotlin/kotlin-coroutines-examples: Examples for coroutines design in Kotlin
Examples for coroutines design in Kotlin. Contribute to Kotlin/kotlin-coroutines-examples development by creating an account on GitHub.
kotlin  coroutine  example  code  repo  sample  project 
14 days ago by lgtout
[1805.07883] How Many Samples are Needed to Estimate a Convolutional Neural Network?
A widespread folklore for explaining the success of Convolutional Neural Networks (CNNs) is that CNNs use a more compact representation than the Fully-connected Neural Network (FNN) and thus require fewer training samples to accurately estimate their parameters. We initiate the study of rigorously characterizing the sample complexity of estimating CNNs. We show that for an m-dimensional convolutional filter with linear activation acting on a d-dimensional input, the sample complexity of achieving population prediction error of ε is O˜(m/ε2) whereas the sample-complexity for its FNN counterpart is lower bounded by Ω(d/ε2) samples. Since, in typical settings m≪d, this result demonstrates the advantage of using a CNN. We further consider the sample complexity of estimating a one-hidden-layer CNN with linear activation where both the m-dimensional convolutional filter and the r-dimensional output weights are unknown. For this model, we show that the sample complexity is O˜((m+r)/ε2) when the ratio between the stride size and the filter size is a constant. For both models, we also present lower bounds showing our sample complexities are tight up to logarithmic factors. Our main tools for deriving these results are a localized empirical process analysis and a new lemma characterizing the convolutional structure. We believe that these tools may inspire further developments in understanding CNNs.
CNN  sample  complexity 
15 days ago by foodbaby
azureimds/IMDSSample.cs at master · Microsoft/azureimds
Azure Instance Metadata Samples. Contribute to Microsoft/azureimds development by creating an account on GitHub.
azure  c#  microsoft  github  sample  cloud  rest  api 
23 days ago by geekzter

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