MyTHWN's Stars
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
azl397985856/leetcode
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解,记录自己的leetcode解题之路。)
google-research/bert
TensorFlow code and pre-trained models for BERT
recommenders-team/recommenders
Best Practices on Recommendation Systems
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
tensorflow/ranking
Learning to Rank in TensorFlow
nidhaloff/deep-translator
A flexible free and unlimited python tool to translate between different languages in a simple way using multiple translators.
pisa-engine/pisa
PISA: Performant Indexes and Search for Academia
amzn/pecos
PECOS - Prediction for Enormous and Correlated Spaces
jma127/pyltr
Python learning to rank (LTR) toolkit
uclanlp/awesome-fairness-papers
Papers on fairness in NLP
ULTR-Community/ULTRA
Unbiased Learning To Rank Algorithms (ULTRA)
Mahdisadjadi/arxivscraper
A python module to scrape arxiv.org for a date range and category
FeeiCN/dict
Chinese and English translation tools in the command line(命令行下中英文翻译工具)
lileipisces/PEPLER
TOIS'23, Personalized Prompt Learning for Explainable Recommendation
QingyaoAi/Unbiased-Learning-to-Rank-with-Unbiased-Propensity-Estimation
This is an implementation of the Dual Learning Algorithm with multi-layer feed-forward neural network for online unbiased learning to rank.
lileipisces/PETER
ACL'21 Oral, Personalized Transformer for Explainable Recommendation
evison/Sentires
Sentires: A Toolkit for Phrase-level Sentiment Analysis
MyTHWN/MTER
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data
HanjieChen/Reading-List
ten-blue-links/fxt
A large scale feature extraction tool for text-based machine learning
niffler92/Bandit
Bandit algorithms
aobo-y/SAER
Explanation as a Defense of Recommendation (WSDM '21)
HCDM/OnlineLearningToRank
HCDM/Graph-Embedding-Algorithms
Louise-LuLin/active-RL
active learning for sequence-to-sequence model using RL
Louise-LuLin/gcn-debias
MyTHWN/The-FacT--Sigir2019
The FacT: Taming Latent Factor Models for Explainability with Factorization Tree
dharahas10/Autoencoder
Denoising Autoencoder Recommeder System
MyTHWN/SAER
Explanation as a Defense of Recommendation (WSDM '21)