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"
(Python, R, C) Collective (multi-view/multi-way) matrix factorization, including cold-start functionality (recommender systems, imputation, dimensionality reduction)
#计算机科学#深度学习与推荐系统学习，理论结合代码更香。
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
[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.
ColdRec: An Open-Source Benchmark Toolbox for Cold-Start Recommendation.
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