We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study
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Updated
Jul 11, 2024 - Python
We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study
Towards Knowledge-Based Personalized Product Description Generation in E-commerce @ KDD 2019
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。
Code for the paper 'Personalization in Goal-oriented Dialog' (NeurIPS 2017 Conversational AI Workshop)
[ECCV 2024🔥] Arc2Face: A Foundation Model of Human Faces
RecTools - library to build Recommendation Systems easier and faster than ever before
Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record
A general purpose recommender metrics library for fair evaluation.
Federated Learning Utilities and Tools for Experimentation
Official Implementation for "ConceptLab: Creative Generation using Diffusion Prior Constraints"
AAAI 2023 accepted paper, FedALA: Adaptive Local Aggregation for Personalized Federated Learning
EMNLP 2019: Generating Personalized Recipes from Historical User Preferences
Anti-DreamBooth: Protecting users from personalized text-to-image synthesis (ICCV 2023)
Official Implementation for "A Neural Space-Time Representation for Text-to-Image Personalization" (SIGGRAPH Asia 2023)
This is our implementation for our paper: TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation
Platform for building personalized AI applications
A lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement (ACM CHIL-2021)
[ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time
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