shfy97

AutoProductEvalution

基于淘宝、京东爬虫及商品评论情感分析的商品评价系统

crawler_JD_what_worthy_buying

爬取京东商品所有评论，利用情感分析，判断商品是否值得买

ChineseTextClassifier

中文商品评论短文本分类器，可用于情感分析

JD-comments-sentiment-analysis

利用Python网络爬虫对京东商城中指定商品下的用户评论进行爬取，对数据预处理操作后进行文本情感分析并可视化显示。

SORL-for-Auto-bidding

codes for SORL framework for auto-bidding

TD3_BC

Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

RLBid_EA

This is a repository of the experiment code supporting the paper Real-time Bidding Strategy in Display Advertising: An Empirical Analysis.

DeepFM_with_PyTorch

A PyTorch implementation of DeepFM for CTR prediction problem.

FAB_expr

The codes for 《A Dynamic Bidding Strategy Based on Model-free Reinforcement Learning in Display Advertising》

maab

Code for "A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising" WSDM 2022

Arbitrary_Distribution_Modeling

Arbitrary Distribution Modeling with Censorship in Real Time Bidding Advertising for KDD'22

DLF

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.

make-ipinyou-data

This project is to formalise the iPinYou RTB data into a standard format for further researches.

MLBC-DQN

code for paper 《Advertising Impression Resource Allocation Strategy with Multilevel Budget Constraint DQN in Real-Time Bidding》

rtb-papers

A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.

Book-Mathematical-Foundation-of-Reinforcement-Learning

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

rlb-dp

Real-Time Bidding by Reinforcement Learning in Display Advertising

rnn_controller

RNN controller code used in paper "Recurrent Neural Networks for Stochastic Control in Real-Time Bidding" in The 25th ACM SIGKDD Conference

qlib

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Q-Learning-for-Non-Competitive-Bridge-Bidding

Automatic-Bridge-Bidding-by-Deep-Reinforcement-Learning

The released model of the paper 'Automatic Bridge Bidding by Deep Reinforcement Learning' in ECAI 2016

deep_learning_and_the_game_of_go

Code and other material for the book "Deep Learning and the Game of Go"