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authorClement Farabet <clement.farabet@gmail.com>2012-01-22 04:27:45 +0400
committerClement Farabet <clement.farabet@gmail.com>2012-01-22 04:27:45 +0400
commit8614d4f89d53345dc9b4f4038c18d104e041b77c (patch)
treefbc8670cad24158d70e3390ca82268f30661c267 /README.md
parentf5d451b39a70e44896ba691e7455d4030d99e788 (diff)
fixed README layout
Diffstat (limited to 'README.md')
-rw-r--r--README.md12
1 files changed, 6 insertions, 6 deletions
diff --git a/README.md b/README.md
index 0524941..2f93ea4 100644
--- a/README.md
+++ b/README.md
@@ -18,9 +18,9 @@ Each optimization algorithm is based on the same interface:
x*, {f}, ... = optim.method(func, x, state)
with:
-func : a user-defined closure that respects this API: f,df/dx = func(x)
-x : the current parameter vector (a 1d torch tensor)
-state : a table of parameters, and state variables, dependent upon the algorithm
-x* : the new parameter vector that minimizes f, x* = argmin_x f(x)
-{f} : a table of all f values, in the order they've been evaluated
- (for some simple algorithms, like SGD, #f == 1)
+* func : a user-defined closure that respects this API: f,df/dx = func(x)
+* x : the current parameter vector (a 1d torch tensor)
+* state : a table of parameters, and state variables, dependent upon the algorithm
+* x* : the new parameter vector that minimizes f, x* = argmin_x f(x)
+* {f} : a table of all f values, in the order they've been evaluated
+ (for some simple algorithms, like SGD, #f == 1)