# exp-trmf-nips16

**Repository Path**: ccfgtt/exp-trmf-nips16

## Basic Information

- **Project Name**: exp-trmf-nips16
- **Description**: Experimental Codes for Temporal Regularized Matrix Factoriztion for High-dimensional Time Series Prediction.
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-01-31
- **Last Updated**: 2024-06-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

This is the experimental code for the following paper:

	* H.-F. Yu, N. Rao, and I. S. Dhillon. Temporal Regularized 
	  Matrix Factoriztion for High-dimensional Time Series Prediction. Advances 
      in Neural Information Processing Systems (NIPS) 29, 2016.

Interfaces
==========
The core codes of TRMF are implemented in C++. The original experiments are done using a Matlab interface. 
Upon the requests, I refactored the core C++ codes and created an easy-to-use Python interface (with Scipy/Numpy).


Citation
========
    Please acknowledge the use of the code with a citation.
	* H.-F. Yu, N. Rao, and I. S. Dhillon. Temporal Regularized 
	  Matrix Factoriztion for High-dimensional Time Series Prediction. Advances 
      in Neural Information Processing Systems (NIPS) 29, 2016.
```
@inproceedings{hfy16a,
  title={Temporal Regularized Matrix Factoriztion for High-dimensional Time Series Prediction},
  author={Yu, Hsiang-Fu and Rao, Nikhil and Dhillon, Inderjit S.},
  booktitle = {Advances in Neural Information Processing Systems 28},
  year={2016}
}
```

If you have any questions regarding the code, feel free to contact Hsiang-Fu Yu (rofuyu at cs utexas edu).