Xiangyu's Projects
500 Lines or Less
Alluxio, formerly Tachyon, Memory Speed Virtual Distributed Storage System
experiment code for our NIPS'18 paper
My emacs config file with support for C/C++, Matlab, Haskell, LaTeX etc.
Private computation framework library allows developers to perform randomized controlled trials, without leaking information about who participated or what action an individual took. It uses secure multiparty computation to guarantee this privacy. It is suitable for conducting A/B testing, or measuring advertising lift and learning the aggregate statistics without sharing information on the individual level.
FBPCS (Facebook Private Computation Solutions) leverages secure multi-party computation (MPC) to output aggregated data without making unencrypted, readable data available to the other party or any third parties. Facebook provides impression & opportunity data, and the advertiser provides conversion / outcome data. Both parties have dedicated cloud computing instances living on separate Virtual Private Clouds (VPCs) that are connected to allow network communication. The FBPMP products that have been implemented are Private Lift and Private Attribution. It’s expected that more products will be implemented and added to the Private Measurement suite.
An open-source C++ library developed and used at Facebook.
Haskell MOOC University of Helsinki
linux kernel version 0.11, compiled on Debian sid 64-bit, ran in the bochs.
Microarchitectural attack development frameworks for prototyping attacks in native code (C, C++, ASM) and in the browser
南京大学学位论文XeLaTeX模板
Implementation of the local search method for online (k,z)-median problem
scikit-learn: machine learning in Python
A practical attack framework for precise enclave execution control
Backup copy of shadowsocks before clowwindy had to clean it up, salute to clowwindy and ss developers.
Code implementation for our AAAI-20 paper on Scaled Least Square Estimator
experiment code for the robust EM paper
page hosting some notes