推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
#时序数据库#Power Tools for AI Engineers With Deadlines
翻译 - H1st AI解决了工业AI的关键“冷启动”问题：对人类专业知识进行编码以增加数据的缺乏，同时构建向机器学习未来的平稳过渡。此问题已导致大多数工业AI项目失败。
This repository includes some papers that I have read or which I think may be very interesting.
Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling
A curated list of resources on cold-start recommendations.
Source code for KDD 2020 paper "Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation"
#计算机科学#深度学习与推荐系统学习，理论结合代码更香。
(Python, R, C) Collective (multi-view/multi-way) matrix factorization, including cold-start functionality (recommender systems, imputation, dimensionality reduction)
Scaffolding for Cloud Functions deployed with the Firebase CLI that minimize cold starts by using TypeScript async imports
An application to help prevent cold starts in AWS Lambda functions.
#计算机科学#Source code for MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation. TKDE 2022.
keep lambdas warm and monitor cold starts with a simple decorator
Lambda Dispatch for AWS Lambda - Avoid cold starts, save up to 80%!
cross-domain recommendation，transfer learning，pre-training，self-supervise learning papers and datasets
ColdRec: An Open-Source Benchmark Toolbox for Cold-Start Recommendation.
[WWW 2021]Task-adaptive Neural Process for User Cold-Start Recommendation
A recommender engine built for a Bay Area online dating website to maximize the successful matches by introducing hybrid recommender system and reverse match technique.
Python implementation of "Content-based recommendations with poisson factorization", with some extensions
Accompanying code for reproducing experiments from the HybridSVD paper. Preprint is available at https://arxiv.org/abs/1802.06398.
papers of universal user representation learning for recommendation