Pinned Repositories
chicago-taxi-data
Import and analyze Chicago public taxi data
d4d-challenge
differential-privacy-library
Diffprivlib: The IBM Differential Privacy Library
dp-learn
dp-sparse-mcs
code for 'Differential Location Privacy for Sparse Mobile Crowdsensing' at ICDM'16
FIM_Local_Differential_Privacy
frequent itemset mining with differential privacy in local setting
hello-world
test
k_annonymity
本科毕设时的代码，用于k匿名栅格化位置隐私保护“群智背景下”
Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
mlcube
MLCube™ is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.
sjsnjnu's Repositories
sjsnjnu/chicago-taxi-data
Import and analyze Chicago public taxi data
sjsnjnu/d4d-challenge
sjsnjnu/differential-privacy-library
Diffprivlib: The IBM Differential Privacy Library
sjsnjnu/dp-learn
sjsnjnu/dp-sparse-mcs
code for 'Differential Location Privacy for Sparse Mobile Crowdsensing' at ICDM'16
sjsnjnu/FIM_Local_Differential_Privacy
frequent itemset mining with differential privacy in local setting
sjsnjnu/hello-world
test
sjsnjnu/k_annonymity
本科毕设时的代码，用于k匿名栅格化位置隐私保护“群智背景下”
sjsnjnu/Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
sjsnjnu/mlcube
MLCube™ is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.
sjsnjnu/mlcube_examples
MLCube™ examples
sjsnjnu/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
sjsnjnu/PPCF
PPCF: Privacy-Preserving Collaborative Filtering for Web Service Recommendation
sjsnjnu/pyFM
Factorization machines in python
sjsnjnu/Sjs
no
sjsnjnu/test
this a test