LoRAM (Low-rank Additive Model) for the computation of projection from graphs to DAGs

Implementation of LoRAM. Reference: Dong, S. & Sebag, M. (2022). From graphs to DAGs: a low-complexity model and a scalable algorithm. URL https://arxiv.org/abs/2204.04644.

Core functions

• mf_projdag.py - Implementation of Algorithm 2 (LoRAM-AGD) for the optimization of LoRAM
• splr_expmv.py - Implementation of Algorithm 1 for (A,C,B) -> (exp(A) odot C) B
• spmaskmult.pyx - LoRAM matrix via sparsified low-rank matrix product (Algorithm 3)

Requirements

• Python 3+
• numpy
• scipy
• NOTEARS/utils.py - graph simulation, data simulation, and accuracy evaluation from Zheng et al. 2018
• python-igraph: Install igraph C core and pkg-config first.

Running a demo

Access the code loram_exp/

$ make  # for spmaskmult.pyx 
$ python demo_loram_proj.py