cold-start

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.

Power Tools for AI Engineers With Deadlines

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

[Up-to-date] A curated list of resources on cold-start recommendations.

深度学习与推荐系统学习，理论结合代码更香。

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)

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.

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 Toolbox for Cold-Start Recommendation.

Code for Paper (Preserving Diversity in Supervised Fine-tuning of Large Language Models)

[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.