Pinned Repositories
barebones-react-native-redux
bintester
chiptune-player
Plays a random chiptune through the sonant-x synthesizer library
chrome-push-client
dotfiles
facebook-business-sdk-codegen
Codegen project for our business SDKs
fbpcp
FBPCP (Facebook Private Computation Platform) is a secure, privacy safe and scalable architecture to deploy MPC (Multi Party Computation) applications in a distributed way on virtual private clouds. FBPCF (Facebook Private Computation Framework) is for scaling MPC computation up via threading, while FBPCP is for scaling MPC computation out via Private Scaling architecture.
fbpcs
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.
gpdb
Greenplum Database
marksliva's Repositories
marksliva/chiptune-player
Plays a random chiptune through the sonant-x synthesizer library
marksliva/barebones-react-native-redux
marksliva/bintester
marksliva/chrome-push-client
marksliva/dotfiles
marksliva/facebook-business-sdk-codegen
Codegen project for our business SDKs
marksliva/fbpcp
FBPCP (Facebook Private Computation Platform) is a secure, privacy safe and scalable architecture to deploy MPC (Multi Party Computation) applications in a distributed way on virtual private clouds. FBPCF (Facebook Private Computation Framework) is for scaling MPC computation up via threading, while FBPCP is for scaling MPC computation out via Private Scaling architecture.
marksliva/fbpcs
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.
marksliva/gpdb
Greenplum Database
marksliva/gpupgrade
Greenplum Database major version upgrade utility called gpupgrade
marksliva/human-protein-atlas
Human Protein Atlas Image Classification - Classify subcellular protein patterns in human cells
marksliva/islr
A study group around Tibshirani and Hastie's Introduction to Statistical Learning
marksliva/marksliva.github.io
marksliva/pytorch-visual-geometry-group
marksliva/uncle-foo
a polycode sandbox
marksliva/view-pager-example-android
marksliva/Whale
whale tails classifier