Update README.md

README.md

@@ -43,8 +43,8 @@ def ica(x, **args):
             x: numpy array of images
             args:
                 lr: learning rate (default 1e-3)
-                nsteps: maximum iterations (default 100)
-                k: number of latent variables
+                nsteps: maximum iterations (default 1000)
+                k: number of latent variables (defualt 20)
         
         returns:
             L: numpy array of loss function value for all iterations
@@ -53,9 +53,9 @@ def ica(x, **args):
 
     # default parameters
     if not len(args):
-        args['lr'] = 1e-4
-        args['nsteps'] = 1000
-        args['k'] = 20
+        args['lr'] = 1
+        args['nsteps'] = 200
+        args['k'] = 64
 
     lr=args['lr']
     nsteps = args['nsteps']
@@ -66,6 +66,7 @@ def ica(x, **args):
     '''training loop using graident descent'''
     for step in range(nsteps):
         # ***insert gradient descent code here***
+        ''' use backtracking line search '''
         
         # print loss
         print('step: {} / {}, L: {}'.format(step, nsteps, L[step]))