LHQD

code for LHQD project, see our arXiv paper

@Article{Liu-preprint-slq,
  author     = {Meng Liu, Nate Veldt, Haoyu Song, Pan Li and David F. Gleich},
  journal    = {arXiv},
  title      = {Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning},
  year       = {2020},
  pages      = {2011.07752},
  volume     = {cs.SI},
  arxiv      = {http://arxiv.org/abs/2011.07752},
  mysoftware = {https://github.com/MengLiuPurdue/LHQD},
}

To run our code, simply include("local-hyper.jl") This has minimal dependencies. Then to run the code on a small hypergraph, run

include("common.jl")
name = "TinyZoo"
M = matread("small-hypergraphs/"*name*".mat")
H = M["H"]
good = findall(x->x > 0, order)
H = H[good,:]
order = vec(round.(Int64,sum(H,dims=2)))
G = LH.graph(H,1.0) # a hypergraph object with delta=1.0 in its cut function
q = 2.0
L = LH.loss_type(q) # the loss-type, this is a 2-norm)
kappa = 0.01 # value of kappa (sparsity regularization)
gamma = 0.1 # value of gamma (regularization on seed) 
rho = 0.5 # value of rho (KKT apprx-val)
S = [1] $ seed set
x,r,iter = LH.lh_diffusion(G,S,gamma,kappa,rho,L,max_iters=10000)
cond,cluster = hyper_sweepcut(G.H,x,G.deg,G.delta,0.0,G.order)

Datasets

The instructions on obtaining the Yelp dataset is included in the yelp_local_algorithms folder. We refer to reference [33] in our manuscript for instructions on obtaining the Amazon and Stack Overflow datasets. The Amazon and Stack Overflow datasets must be placed into hypergraphs folder.

Experiments

• Yelp experiment: check yelp_local_algorithms folder.
• Experiment on Amazon dataset: run experiment-amazon.jl to generate data, run visualization-amazon.jl to generate plots, run generate-table-amazon.jl to generate tables.
• Experiment on Stack Overflow dataset: run experiment-stackoverflow.jl to generate data, run generate-table-stackoverflow.jl to generate tables, run visualization-stackoverflow.jl to generate plots.
• Experiment on varying seeds: run experiment-vary-seeds.jl to generate data, run visualization-vary-seeds.jl to generate plots.
• Experiment on selecting delta: run experiment-select-delta.jl to generate delta, run visualization-vary-delta.jl to generate plots.