🧮 Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model after All

lda4rec -c configs/default.yaml run

lda4rec -c configs/default.yaml create -ds movielens-100k

tmux
sudo apt-get install -y build-essential
curl https://sh.rustup.rs -sSf | sh
source $HOME/.cargo/env
cargo install pueue
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O
sh Miniconda3-latest-Linux-x86_64.sh
source ~/.bashrc
git clone https://github.com/FlorianWilhelm/lda4rec.git
cd lda4rec
conda env create -f environment.yml
conda activate lda4rec
vim ~/.neptune_api_token # and copy it over

pueued -d # only once to start the daemon
pueue parallel 10
export OMP_NUM_THREADS=4  # to limit then number of threads per model
lda4rec -c configs/default.yaml create # to create the config files
find ./configs -maxdepth 1 -name "exp_*.yaml" -exec pueue add "lda4rec -c {} run" \; -exec sleep 30 \;

├── AUTHORS.md              <- List of developers and maintainers.
├── CHANGELOG.md            <- Changelog to keep track of new features and fixes.
├── LICENSE.txt             <- License as chosen on the command-line.
├── README.md               <- The top-level README for developers.
├── configs                 <- Directory for configurations of model & application.
├── data                    <- Downloaded datasets will be stored here.
├── docs                    <- Directory for Sphinx documentation in rst or md.
├── environment.yml         <- The conda environment file for reproducibility.
├── notebooks               <- Jupyter notebooks. Naming convention is a number (for
│                              ordering), the creator's initials and a description,
│                              e.g. `1.0-fw-initial-data-exploration`.
├── logs                    <- Generated logs are collected here.
├── results                 <- Results as exported from neptune.ai.
├── setup.cfg               <- Declarative configuration of your project.
├── setup.py                <- Use `python setup.py develop` to install for development or
│                              or create a distribution with `python setup.py bdist_wheel`.
├── src
│   └── lda4rec             <- Actual Python package where the main functionality goes.
├── tests                   <- Unit tests which can be run with `py.test`.
├── .coveragerc             <- Configuration for coverage reports of unit tests.
├── .isort.cfg              <- Configuration for git hook that sorts imports.
└── .pre-commit-config.yaml <- Configuration of pre-commit git hooks.

@inproceedings{wilhelm2021lda4rec,
author = {Wilhelm, Florian},
title = {Matrix Factorization for Collaborative Filtering Is Just Solving an Adjoint Latent Dirichlet Allocation Model After All},
year = {2021},
month = sep,
isbn = {978-1-4503-8458-2/21/09},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3460231.3474266},
doi = {10.1145/3460231.3474266},
booktitle = {Fifteenth ACM Conference on Recommender Systems},
numpages = {8},
location = {Amsterdam, Netherlands},
series = {RecSys '21}
}