A machine learning compiler for GPUs, CPUs, and ML accelerators

A high-performance framework for training wide-and-deep recommender systems on heterogeneous cluster

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

A tiny CPU profiler for Java written completely in Java 17.

LibAUC: A Deep Learning Library for X-Risk Optimization

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

AuctionGym is a simulation environment that enables reproducible evaluation of bandit and reinforcement learning methods for online advertising auctions.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Transformer related optimization, including BERT, GPT

SASRec: Self-Attentive Sequential Recommendation

The release repo for "Vicuna: An Open Chatbot Impressing GPT-4"

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

gpt4all: an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue

(ICTIR2020) "Unbiased Pairwise Learning from Biased Implicit Feedback"

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR prediction, CVR prediction), Post Ranking, Transfer, Reinforcemen…

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets.

A unified, comprehensive and efficient recommendation library

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".

Recommender System Papers

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper accepted by KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversion…

A Real-World Benchmark for Reinforcement Learning based Recommender System

A Simple Convolutional Generative Network for Next Item Recommendation

(WSDM2020) "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback"

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.