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amf

AMF: Adaptive Matrix Factorization for Online QoS Prediction

an-attention-based-spatiotemporal-lstm-network-for-next-poi-recommendation

A python vision code of An Attention-based Spatiotemporal LSTM Network for Next POI Recommendation

antcolonyalgorithm

蚁群算法的JS实现

cape

In this repository, We're going to implement the paper, which is "Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation", (B. Chang et al, IJCAI-ECAI'18), using a PyTorch library.

cuiyue

daisyrec

A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks

datawhale_learning

Datawhale_Learning涵盖了AI领域从理论知识到动手实践的学习内容

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models for search and recommendation.

deepctr-torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepmove

Codes for WWW'18 Paper-DeepMove: Predicting Human Mobility with Attentional Recurrent Network

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

fast-transx

An Efficient implementation of TransE and its extended models for Knowledge Representation Learning

forum

蓝灯(Lantern)官方论坛

gate

The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"

geneticalgorithm

遗传算法的JS实现

graphembedding

Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec

herec

Source code for TKDE 2018 "Heterogeneous information network embedding for recommendation"

hierarchical-attention-networks

Implementation of Hierarchical Attention Networks as presented in https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf

hme

HME a hybrid memory emulator for studying the performance and energy characteristics of upcoming NVM technologies. HME exploits features available in commodity NUMA architectures to emulate two kinds of memories: fast, local DRAM, and slower, remote NVM on other NUMA nodes. HME can emulates a wide range of NVM latencies and bandwidth by injecting different memory access delay on the remote NUMA nodes. To facilitate programmers and researchers in evaluating the impact of NVM on the application performance, a high-level programming interface is also provided to allocate memory from NVM or DRAM nodes.

jntm

Source code for ACM TOIS 2017 paper "A Neural Network Approach to Joint Modeling Social Networks and Mobile Trajectories".

kgpolicy

Reinforced Negative Sampling over Knowledge Graph for Recommendation, WWW2020

kmodes

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

lantern

Lantern官方版本下载 蓝灯 翻墙 代理 科学上网 外网 加速器 梯子 路由 lantern proxy vpn censorship-circumvention censorship gfw accelerator

lbsn2vec

Code release for LBSN2Vec

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

lglmf

LGLMF: Local Geographical based Logistic Matrix Factorization Model for POI Recommendation

lrsbasics

Basics of Recommender Systems: Study of Location-Based Social Networks

lstpm

Ke Sun, Tieyun Qian, Tong Chen, Yile Liang, Quoc Viet Hung Nguyen, Hongzhi Yin: Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation. AAAI 2020 accepted.

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！