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.
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Updated
Nov 29, 2024 - Python
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
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)
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
A curated list of papers on cold-start recommendations.
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
cross-domain recommendation,transfer learning,pre-training,self-supervise learning papers and datasets
Lambda Dispatch for AWS Lambda - Avoid cold starts, save up to 80%!
[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.
ColdRec: An Open-Source Benchmark Toolbox for Cold-Start Recommendation.
[ACL 2023] The code for our ACL'23 paper Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach
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