DAO-CP

KO | EN

gitlite — search

#ai #llm #android #machine-learning #rust #deep-learning #docker #nodejs #java #awesome #cli #vue #mcp #openai

(★ 8)

DAO-CP: data-adaptive online CP decomposition

DAO-CP 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# [DAO-CP](https://datalab.snu.ac.kr/dao-cp/)
This project is a TensorLy implementation of DAO-CP: data-adaptive online CP decomposition ([PLOS ONE](https://journals.plos.org/plosone/)). <br>
This paper proposes a fast and accurate data-adaptive online CP factorization algorithm for high-order tensors.

![overview](https://raw.githubusercontent.com/snudatalab/DAO-CP/main/docs/overview.svg)

## Prerequisites
- Python 3.6+
- [NumPy 1.19.1](https://numpy.org)
- [TensorLy 0.4.5](http://tensorly.org)
- [Pandas 1.1.1](https://pandas.pydata.org/)
- [SciPy 1.5.2](https://www.scipy.org/)
- [wget 3.2](https://pypi.org/project/wget/)

## Usage
* Install all of the prerequisites with `pip install -r requirements.txt`.
* You can run the demo script by `bash demo.sh <dataset_name>`, <br>
which simply moves to `src/` and runs `python main.py <dataset_name>`.
  * You can choose a dataset for demo (synthetic, video, stock, hall, korea).
* The script creates a tensor stream, performs online decomposition by various methods, and stores estimated tensors at `out/`.
  * Methods includes *Full-CP*, *OnlineCP*, *DTD*, and our proposed method *DAO-CP*.
  * Check decomposition results by loading `.npy` files.
* You can change the dataset and function parameters by modifying `src/main.py`.
* The core functions are implemented in `src/dao-cp`.

## Datasets
| Name | Order | Dimensions | Batch Sizes | Rank | `L_s` | `L_r` |
|:--|:--|:--|:--|:--|:--|:--|
| synthetic	| 4 | (1K, 10, 20, 30) 		| [10] * 100 	| 30 | 1.2 | 1.1 |
| video		| 4 | (205, 240, 320, 3) 	| [5] * 41 		| 30 | 6.0 | 2.0 |
| stock 	| 3 | (3K, 140, 5) 			| [3] * 1K	 	| 20 | 6.0 | 5.0 |
| hall		| 3 | (200, 144, 176) 		| [10] * 20 	| 20 | 0.5 | 0.1 |
| korea 	| 3 | (10K, 323, 6) 		| [100] * 100	| 20 | 2.0 | 1.3 |

## Reference
If you use this code, please cite the following paper.
```bibtex
@article{spc22dao,
	title={DAO-CP: Data-Adaptive Online CP decomposition for tensor stream},
	author={Son, Sangjun and Park, Yong-chan and Cho, Minyong and Kang, U},
	journal={PloS one},
	volume={17},
	number={4},
	pages={e0267091},
	year={2022},
	publisher={Public Library of Science San Francisco, CA USA}
}
~~~

DAO-CP

DAO-CP 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

DAO-CP

DAO-CP 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README