title | layout |
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Network Matrix Exponentials for link-prediction, centrality, and more |
project |
These are research codes and may not work for you.
- nexpokit.tar.gz (2013-08-05)
compile % compile the mex files
G = load_graph('dolphins');
P = normout(G)';
x = gexpmq_mex(P,1,11,1e-5,10*size(P,1));
gexpm_mex
a C++ mex implementation of Gauss-Southwell with a heapgexpmq_mex
a C++ mex implemetation of pseudo-Gauss-Southwell (rounded Gauss-Seidel) with a queue.expmimv_mex
a C++ mex implemetation of an N step Taylor polynomial via Horner rule and "incomplete" matrix-vector products a queue.kmatexp
a matlab implementation of an N+1 step Taylor polynomial via Horner ruletaydeg.hpp
: contains function for selecting Taylor degree appropriate for input error of “tol”heap.hpp
: contains heap functions used in gexpm_mex
mexpv
from expokitexpv
from expokit For Higham & Al-Mohy's "expmv":expmv
expmv_tspan
normAm
- `select_taylor_degree
theta_taylor_half.mat
theta_taylor_single.mat
theta_taylor.mat
To reproduce figures 1 and 2, run:
experiment/localization_demo/example_localization_ljournal.m
To reproduce figure 4, first generate the data by running:
experiments/accuracy_vs_error/compute_tol_accuracy_data.m
Then, to produce the plots for figure 4, run:
experiments/accuracy_vs_error/plot_tol_accuracy.m
To generate the data for figure 5, run:
experiments/accuracy_vs_work/compute_steps_accuracy_order.m
To reproduce figure 5, run:
experiments/accuracy_vs_work/plot_tol_steps_accuracy.m
To reproduce figure 6, first generate the data by running:
experiments/acc_vs_maxnnz/maxnnz_experiment.m
experiments/acc_vs_maxnnz/maxnnz_experiment_web.m
experiments/acc_vs_maxnnz/maxnnz_experiment_friend.m
experiments/acc_vs_maxnnz/maxnnz_experiment_twitter.m
Then, to produce the plots for figure 6, run
experiments/acc_vs_maxnnz/maxnnz_plots_finalized.m
To reproduce figure 7, first generate the data by running:
experiments/runtimes/runtime_experiment.m
experiments/runtimes/runtime_experiment_web.m
experiments/runtimes/runtime_experiment_friend.m
experiments/runtimes/runtime_experiment_twitter.m
experiments/runtimes/runtime_process.m
Then, to produce the plots for figure 7, run:
experiments/runtimes/runtime_plot.m
To reproduce figure 8, first generate the data by running:
experiments/scaling/scaling_study_1.m
experiments/scaling/scaling_study_s.m
Then, to produce the plots for figure 8, run:
experiments/scaling/scaling_plots.m