StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

Related tags

Deep LearningStackRec
Overview

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

Datasets

You can download datasets that have been pre-processed:

We construct a large-scale session-based recommendation dataset (denoted as Video-6M) by collecting the interactiton behaviors of nearly 6 million users in a week from a commercial recommender system. The dataset can be used to evaluate very deep recommendation models (up to 100 layers), such as NextItNet (as shown in our paper StackRec（SIGIR2021)). If you use this dataset in your paper, you should cite our NextItNet and StackRec for publish permission.

@article{yuan2019simple,
	title={A simple convolutional generative network for next item recommendation},
	author={Yuan, Fajie and Karatzoglou, Alexandros and Arapakis, Ioannis and Jose, Joemon M and He, Xiangnan},
	journal={Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining},
	year={2019}
}

@article{wang2020stackrec,
  title={StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking},
  author={Wang, Jiachun and Yuan, Fajie and Chen, Jian and Wu, Qingyao and Li, Chengmin and Yang, Min and Sun, Yang and Zhang, Guoxiao},
  journal={Proceedings of the 44th International ACM SIGIR conference on Research and Development in Information Retrieval},
  year={2021}
}

File Description

requirements.txt: the experiment environment

train_nextitnet_sc1.sh: the shell script to train StackRec with NextItNet in CL scenario
train_nextitnet_sc2.sh: the shell script to train StackRec with NextItNet in TF scenario
train_nextitnet_sc3.sh: the shell script to train StackRec with NextItNet in TS scenario
deep_nextitnet.py: the training file of NextItNet
deep_nextitnet_coldrec.py: the training file of NextItNet customized for coldrec source dataset
data_loader.py: the dataset loading file of NextItNet and GRec
data_loader_finetune.py: the dataset loading file of NextItNet and GRec customized for coldrec dataset
generator_deep.py: the model file of NextItNet
ops.py: the module file of NextItNet and GRec with stacking methods doubling blocks
ops_copytop.py: the module file of NextItNet with stacking methods allowed to stack top blocks
ops_original.py: the module file of NextItNet with stacking methods without alpha
fineall.py: the training file of NextItNet customized for coldrec target dataset

train_grec_sc1.sh: the shell script to train StackRec with GRec in CL scenario
deep_GRec: the training file of GRec
generator_deep_GRec.py: the model file of GRec
utils_GRec.py: some tools for GRec

train_sasrec_sc1.sh: the shell script to train StackRec with SASRec in CL scenario
baseline_SASRec.py: the training file of SASRec
Data_loader_SASRec.py: the dataset loading file of SASRec
SASRec_Alpha.py: the model file of SASRec

train_ssept_sc1.sh: the shell script to train StackRec with SSEPT in CL scenario
baseline_SSEPT.py: the training file of SSEPT
Data_loader_SSEPT.py: the dataset loading file of SSEPT
SSEPT_Alpha.py: the model file of SSEPT
utils.py: some tools for SASRec and SSEPT
Modules.py: the module file of SASRec and SSEPT with stacking methods

Stacking with NextItNet

Train in the CL scenario

Execute example:

sh train_nextitnet_sc1.sh

Train in the TS scenario

Execute example:

sh train_nextitnet_sc2.sh

Train in the TF scenario

Execute example:

sh train_nextitnet_sc3.sh

Stacking with GRec

Execute example:

sh train_grec_sc1.sh

Stacking with SASRec

Execute example:

sh train_sasrec_sc1.sh

Stacking with SSEPT

Execute example:

sh train_ssept_sc1.sh

Key Configuration

  • method: five stacking methods including from_scratch, stackC, stackA, stackR and stackE
  • data_ratio: the percentage of training data
  • dilation_count: the number of dilation factors {1,2,4,8}
  • num_blocks: the number of residual blocks
  • load_model: whether load pre-trained model or not
Owner
GitHub Repository
Zero-shot Synthesis with Group-Supervised Learning (ICLR 2021 paper)

GSL - Zero-shot Synthesis with Group-Supervised Learning Figure: Zero-shot synthesis performance of our method with different dataset (iLab-20M, RaFD,

Andy_Ge 62 Dec 21, 2022
Official implementation for paper Knowledge Bridging for Empathetic Dialogue Generation (AAAI 2021).

Knowledge Bridging for Empathetic Dialogue Generation This is the official implementation for paper Knowledge Bridging for Empathetic Dialogue Generat

Qintong Li 50 Dec 20, 2022
Official Pytorch implementation of Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (ICLR 2022)

The Official Implementation of CLIB (Continual Learning for i-Blurry) Online Continual Learning on Class Incremental Blurry Task Configuration with An

NAVER AI 34 Oct 26, 2022
PyTorch implementation of neural style randomization for data augmentation

README Augment training images for deep neural networks by randomizing their visual style, as described in our paper: https://arxiv.org/abs/1809.05375

84 Nov 23, 2022
A geometric deep learning pipeline for predicting protein interface contacts.

A geometric deep learning pipeline for predicting protein interface contacts.

44 Dec 30, 2022
Lightweight, Python library for fast and reproducible experimentation :microscope:

Steppy What is Steppy? Steppy is a lightweight, open-source, Python 3 library for fast and reproducible experimentation. Steppy lets data scientist fo

minerva.ml 134 Jul 10, 2022
Video Autoencoder: self-supervised disentanglement of 3D structure and motion

Video Autoencoder: self-supervised disentanglement of 3D structure and motion This repository contains the code (in PyTorch) for the model introduced

157 Dec 22, 2022
TalkingHead-1KH is a talking-head dataset consisting of YouTube videos

TalkingHead-1KH Dataset TalkingHead-1KH is a talking-head dataset consisting of YouTube videos, originally created as a benchmark for face-vid2vid: On

173 Dec 29, 2022
A general-purpose encoder-decoder framework for Tensorflow

READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz

Google 5.5k Jan 07, 2023
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation

Multimedia Technology and Telecommunication Lab 42 Nov 09, 2022
Pytorch implement of 'Unmixing based PAN guided fusion network for hyperspectral imagery'

Pgnet There's a improved version compared with the publication in Tgrs with the modification in the deduction of the PDIN block: https://arxiv.org/abs

5 Jul 01, 2022
AntroPy: entropy and complexity of (EEG) time-series in Python

AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to e

Raphael Vallat 153 Dec 27, 2022
Code for Multinomial Diffusion

Code for Multinomial Diffusion Abstract Generative flows and diffusion models have been predominantly trained on ordinal data, for example natural ima

104 Jan 04, 2023
Tianshou - An elegant PyTorch deep reinforcement learning library.

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on

Tsinghua Machine Learning Group 5.5k Jan 05, 2023
a pytorch implementation of auto-punctuation learned character by character

Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult

Ge Yang 137 Nov 09, 2022
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving This is the source code for our paper Frequency Domain Image Tran

Mu Cai 52 Dec 23, 2022
Simulated garment dataset for virtual try-on

Simulated garment dataset for virtual try-on This repository contains the dataset used in the following papers: Self-Supervised Collision Handling via

33 Dec 20, 2022
Repositório criado para abrigar os notebooks com a listas de exercícios propostos pelo professor Gustavo Guanabara do canal Curso em Vídeo do YouTube durante o Curso de Python 3

Curso em Vídeo - Exercícios de Python 3 Sobre o repositório Este repositório contém os notebooks com a listas de exercícios propostos pelo professor G

João Pedro Pereira 9 Oct 15, 2022
joint detection and semantic segmentation, based on ultralytics/yolov5,

Multi YOLO V5——Detection and Semantic Segmentation Overeview This is my undergraduate graduation project which based on ultralytics YOLO V5 tag v5.0.

477 Jan 06, 2023
A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon.

PokeGAN A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon. Dataset The model has been trained on dataset that includes 8

19 Jul 26, 2022