# Feiyang/MetaEmbedding

<https://repo.masters-masters.com/en/repos/Feiyang/MetaEmbedding>

[Home](https://repo.masters-masters.com/en) › [Feiyang](https://repo.masters-masters.com/en/owners/Feiyang) › [MetaEmbedding](https://repo.masters-masters.com/en/repos/Feiyang/MetaEmbedding)

Feiyang/MetaEmbedding has 100 stars on GitHub. Its RepoMasters card: Prototype tier. Codes for our SIGIR-2019 paper "Warm Up Cold-start Advertisements…

| Field | Value |
| --- | --- |
| Owner | [Feiyang](https://repo.masters-masters.com/en/owners/Feiyang) |
| Stars | 100 |
| Forks | 32 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2019 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [Feiyang/MetaEmbedding](https://github.com/Feiyang/MetaEmbedding) |

## Repository

Codes for our SIGIR-2019 paper "Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings"

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.