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PaddlePaddle / ElasticCTR

Star 157

ElasticCTR，即飞桨弹性计算推荐系统，是基于Kubernetes的企业级推荐系统开源解决方案。该方案融合了百度业务场景下持续打磨的高精度CTR模型、飞桨开源框架的大规模分布式训练能力、工业级稀疏参数弹性调度服务，帮助用户在Kubernetes环境中一键完成推荐系统部署，具备高性能、工业级部署、端到端体验的特点，并且作为开源套件，满足二次深度开发的需求。

personalization ranking hdfs k8s recommender-system ctr
  • Updated Jul 11, 2020
  • Python

sisinflab / adversarial-recommender-systems-survey

Star 98

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.

security machine-learning ai deep-learning personalization generative-adversarial-network gan recsys recommender-system aml literature-review adversarial-machine-learning adversarial-attacks collabora future-visions
  • Updated Mar 3, 2021

TsingZ0 / PFL-Non-IID

Star 58

The origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated learning setting, a myriad of approaches has been proposed to crack this hard nut. In contrast, the personalized federated learning may take the advantage of the Non-IID data to learn the personalized model for each user. Thanks to @Stonesjtu, this platform can also record the GPU memory usage for the model.

python nlp platform machine-learning privacy simulation cv distributed-computing cnn pytorch personalization mnist rnn cifar10 differential-privacy cifar100 heterogeneity federated-learning fmnist non-iid
  • Updated Jan 15, 2022
  • Python

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