Papers on Computational Advertising
-
Updated
Feb 9, 2021 - Python
Papers on Computational Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
Android application for Internet privacy and security
advertools - online marketing productivity and analysis tools
DeepRec is a high-performance recommendation deep learning framework based on TensorFlow. It is hosted in incubation in LF AI & Data Foundation.
A simple Python wrapper for the Amazon.com Product Advertising API
CodeFund is an open source platform that helps fund maintainers, bloggers, and builders through non-tracking ethical ads
Curated list of ad-free alternatives to popular services on the web
Accelerated subscription for international/China region ad filtering rules(国际/中国地区广告过滤规则的加速订阅)
Website analytics, JavaScript error tracking + analytics, tag manager, data ingest endpoint creation (tracking pixels). GDPR + CCPA compliant.
A collection of research and application papers of (uncertainty) calibration techniques.
A collection of research and survey papers of fraud detection mainly in advertising.
The safe post-production pipeline - https://getavalon.github.io/2.0
MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets.
Deprecated. Please go to https://github.com/gitcoinco/code_fund_ads
The ethical ad server - ads for developers without all the tracking
A React implementation of the Google DFP/GPT api. https://react-dfp.surge.sh
A DAG based parallel task schedule framework for galois advertising|基于DAG(Directed Acyclic Graph)的并行任务调度系统,自动推导节点依赖生成DAG。
Add a description, image, and links to the advertising topic page so that developers can more easily learn about it.
To associate your repository with the advertising topic, visit your repo's landing page and select "manage topics."