Alternatives and similar repositories for LargeBatchCTR

Users that are interested in LargeBatchCTR are comparing it to the libraries listed below

• alibaba / nann
  A flexible, high-performance framework for large-scale retrieval problems based on TensorFlow.
  ☆165Updated 7 months ago
• massquantity / dismember
  Advanced Retrieval Algorithms for Decomposing Large-Scale Candidate Set into Pieces.
  ☆72Updated 5 months ago
• Tencent / embedx
  embedx 是基于 c++ 开发的、完全自研的分布式 embedding 训练和推理框架。它目前支持 图模型、深度排序、召回模型和图与排序、图与召回的联合训练模型等
  ☆309Updated last year
• LibRerank-Community / LibRerank
  LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EG…
  ☆262Updated 3 years ago
• clabrugere / wukong-recommendation
  Implements the paper "Wukong: Towards a Scaling Law for Large-Scale Recommendation" from Meta.
  ☆72Updated 8 months ago
• Angel-ML / PyTorch-On-Angel
  PyTorch On Angel, arming PyTorch with a powerful Parameter Server, which enable PyTorch to train very big models.
  ☆168Updated 2 months ago
• laming-chen / fast-map-dpp
  Fast Greedy MAP Inference for DPP
  ☆129Updated 5 years ago
• tttwwy / sim
  ☆64Updated 4 years ago
• alibaba / TorchEasyRec
  An easy-to-use framework for large scale recommendation algorithms.
  ☆221Updated this week
• jdcomsearch / poeem
  A library for end-to-end learning of embedding index and retrieval model
  ☆62Updated 4 years ago
• yahoo / FmFM
  ☆41Updated 4 years ago
• ptzhangAlg / RecAlg
  ☆31Updated 2 years ago
• PersiaML / PERSIA
  High performance distributed framework for training deep learning recommendation models based on PyTorch.
  ☆408Updated 3 months ago
• morningsky / Torch-RecHub
  A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.
  ☆82Updated 3 years ago
• xuanjixiao / onerec
  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 Knowl…
  ☆177Updated last week
• JDGalileo / galileo
  Galileo library for large scale graph training by JD
  ☆151Updated 3 years ago
• reczoo / BARS
  BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
  ☆378Updated 10 months ago
• stasi009 / NumpyWDL
  Implement Wide & Deep algorithm by using NumPy
  ☆156Updated 6 years ago
• MarcoMorik / Dynamic-Fairness
  Dynamic Fair Rankings
  ☆87Updated 2 years ago
• Z-Y-Zhang / one_epoch_phenomenon
  This is the implementation of `Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Models`, which is accepted by …
  ☆28Updated 2 years ago
• huangsg1 / Internet-advertising-mechanism-and-strategy
  计算广告机制策略相关材料整理(A collection of research and application papers about Strategy in Internet advertising.)
  ☆170Updated last year
• xidongbo / AITM
  TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper accepted by KDD21: Modeling th…
  ☆117Updated last year
• Qihoo360 / tensornet
  a TensorFlow-based distributed training framework optimized for large-scale sparse data.
  ☆329Updated 2 months ago
• CAN-Paper / Co-Action-Network
  Implementation of CAN: Revisiting Feature Co-Action for Click-Through RatePrediction
  ☆221Updated 4 years ago
• zhuchenxv / AutoFIS
  AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction
  ☆184Updated 3 years ago
• easezyc / Multitask-Recommendation-Library
  MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets.
  ☆329Updated 2 years ago
• fukang93 / YCDL
  DNN framework based on ps-lite
  ☆30Updated 4 years ago
• chenghuige / mind
  2020 MIND news recomendation first place solution
  ☆95Updated 4 years ago
• reczoo / RecBook
  推荐系统修炼手册
  ☆117Updated 3 years ago
• yongqyu / DIEN-tf2
  Deep Interest Network for Click-Through Rate Prediction / Deep Interest Evolution Network for Click-Through Rate Prediction
  ☆80Updated 5 years ago