forked from andrewssobral/OnlineLRR-ICML2016
-
Notifications
You must be signed in to change notification settings - Fork 0
/
mnist_olrsc.m
81 lines (55 loc) · 1.44 KB
/
mnist_olrsc.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
clear;
config = mnist_config();
method = 'olrsc';
K = config.K;
epochs = config.epoch;
%% add path
addpath('OLRSC/');
addpath('SSC/');
%% load data
data_file = config.data_file;
load(data_file);
result_file = sprintf(config.result_file_format, method, method);
%% compute Acc for OLRSC
fprintf('OLRSC: K = %d\n', K);
[p, n] = size(Z);
lambda1 = 1;
lambda2 = 1/sqrt(p);
lambda3_base = 1/sqrt(p);
d = 5 * K;
M = zeros(p, d);
A = zeros(d, d);
B = zeros(p, d);
U = zeros(n, d);
V = zeros(n, d);
D = randn(p, d);
tic;
for ep=1:epochs
for t=1:n
if mod(t, 1000) == 0
fprintf('OLRSC: access sample %d\n', t);
end
z = Z(:, t);
lambda3 = sqrt(t) * lambda3_base;
[v, e] = OLRR_solve_ve(z, D, lambda1, lambda2);
normz = norm(z);
u = (D - M)' * z / (normz * normz + 1/lambda3);
M = M + z * u';
A = A + v * v';
B = B + (z-e) * v';
D = OLRR_solve_D(D, M, A, B, lambda1, lambda3);
U(t, :) = u';
V(t, :) = v';
end
M = zeros(p, d);
end
T = toc;
tic;
X = U * V';
Xsym = BuildAdjacency(X);
groups = SpectralClustering(Xsym, K);
Acc = 1 - Misclassification(groups, gt);
T_spec = toc;
fprintf('epoch %d, Acc = %g\n', ep, Acc);
save(result_file, 'Acc', 'T', 'T_spec');
fprintf('save to %s\n', result_file);