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1m_generalization

1M_Generalization is a simple anonymization algorithm for 1:M dataset. It contains two sub-algorithms: Mondrian (for relational part) and Partition (transaction part). Both of them are straight forward, and can be repalced by more powerful algorithm with limtied modification.

algorithms_princeton

Algorithms Princeton exercises

alluxio

Alluxio, formerly Tachyon, Unify Data at Memory Speed

analytics-zoo

Distributed Tensorflow, Keras and BigDL on Apache Spark

analyzing_weibo_data_with_spark

try to analyzing weibo data with Spark

anatomize

This repository is an open source python implement for Anatomy. I implement this algorithm in python for further study.

apa

Anatomize and Partition Anonymization

apriori_based_anonymization

This repository is an python implement of Apriori_based_Anonymization for set-valued dataset anonymization.

arx

ARX is a comprehensive open source data anonymization tool that has been designed from the ground up to provide high scalability and ease of use. It supports risk-based anonymization, methods for analyzing data quality and re-identification risks, as well as privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy

auto_optimization

OpenVINO auto_optimization

basic_mondrian

The raw mondrian is designed for numerical attributes. When comes to categorical attributes, Mondrian needs to transform categorical attributes to numerical ones. This transformations is not good for some applications. In 2006, LeFevre proposed basic Mondrian, which support both categorical and numerical attributes. This repository is an implementation for basic Mondrian.

bigdl-core

Core HW bindings and optimizations for BigDL

bigdl-ppml-azure-occlum-example

chatgpt-next-web

chatgpt-web

clustering_based_k_anon

cluster based generalization for k-anonymity

confidential-computing-zoo

Confidential Computing Zoo provides confidential computing solutions based on Intel SGX, TDX, HEXL, etc. technologies.

confidential-container-samples

Repo of Azure Kubernetes service based sample implementations leveraging Azure Confidential Computing Nodes.

cs234_reinforcement_learning

CS234: Reinforcement Learning Winter 2019

cython_example

A simple Cython example

deep_learning_exercise

Deep Learning Exercise and Notebook

e2e_dl_benchmark

enhanced_mondrian_for_incomplete

Enhanced_Mondrian for incomplete microdata

fate

An Industrial Grade Federated Learning Framework

google_apac

My solution for Google APAC

graphene

Graphene / Graphene-SGX - a library OS for Linux multi-process applications, with Intel SGX support

hdl

Support Deep Learning on Hadoop platform

hilb_idist

HILB and iDIST are two efficient anonymization algorithms proposed by Gabriel Ghinita in his paper. This repository is a python implementation for HILB and iDIST.

how_to_search_and_read_a_paper

本文档适合于刚入学的硕士和博士(计算机专业最好，其他专业可参考)。

image_classification_redis

Image Classification based on Analytics-Zoo and Redis