Code for "MoME: Mixture-of-Masked-Experts for Efficient Multi-Task Recommendation"

主流推荐系统Rank算法的实现

在常规推荐系统算法和系统双优化的范式下，一线公司针对单个任务或单个业务的效果挖掘几乎达到极限。从2019年我们开始关注多种信息的萃取融合，提出了OneRec算法，希望通过平台或外部各种各样的信息来进行知识集成，打破数据孤岛，极大扩充推荐的“Extra World Knowledge”。 已实践的算法包括行为数据，内容描述，社交信息，知识图谱等。在OneRec，每种信息和整体算法的集成是可插拔…

This is the notes of the way of machine learning study. You may find something useful in it.

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.

Code for the NeurIPS'17 paper "DropoutNet: Addressing Cold Start in Recommender Systems"

The implementation for our paper "Slate-Aware Ranking for Recommendation" accepted by WSDM.23

The code of CL4CTR

A framework for large scale recommendation algorithms.

Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)

An implementation of a deep learning recommendation model (DLRM)

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

A collection of research and application papers about Strategy, Match, Targeting and Creatives in Internet advertising.

Python-based framework for building and evaluating session-based and session-aware recommender systems.

大规模推荐模型训练工具

Source code and dataset for KDD 2020 paper "Controllable Multi-Interest Framework for Recommendation"

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 Neu…

Implementation of CAN: Revisiting Feature Co-Action for Click-Through RatePrediction

code of our AAAI 2021 paper Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper submitted to KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversio…

Multi-task Learning Model for Recommender Systems

links to conference publications in graph-based deep learning

A library for end-to-end learning of embedding index and retrieval model

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embed…

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

A curated list of awesome self-supervised methods

《深入浅出图神经网络：GNN原理解析》配套代码

code for the paper "Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint"