Discover rk2900/DLF Open Source project by Kan Ren (@rk2900)

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Rank 452,630 (Top 9 %)
Language
Python
License
MIT License
Created over 5 years ago
Updated about 4 years ago

rk2900

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Deep learning for flexible market price modeling (landscape forecasting) in real-time bidding advertising. An implementation of our KDD 2019 paper with some other (Python) implemented prediction models.

DRSA

Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper and a benchmark for several (Python) implemented survival analysis methods.

Python

138

deep-conv-attr

An implementation of our CIKM 2018 paper "Deep Conversion Attribution with Dual-attention Recurrent Neural Network"

Python

bidding-machine

An implementation of the TKDE paper "Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising"

Python

optimal-ctr-bidding

A training and testing framework supporting experiments in CIKM 2016 paper "User Response Learning for Directly Optimizing Campaign Performance in Display Advertising"

Python

spam-filter

A spam filter in Python

mr-bid

Real-time Bidding framework in distributed systems

Python

value-based-reinforcement-learning

Introduction to advances of value-based reinforcement learning

TeX

ngramtools

Automatically exported from code.google.com/p/ngramtools

C++

rk2900/DLF

rk2900

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