da with GL

Nicolas Courty · Nicolas Courty · commit 530eb0413f9c · 2016-11-09T00:15:10.000+01:00
diff --git a/examples/demo_OTDA_classes.py b/examples/demo_OTDA_classes.py
@@ -58,7 +58,7 @@
 
 # True Group lasso regularization
 reg=1e-1
-eta=1e1
+eta=1e0
 da_l1l2=ot.da.OTDA_l1l2()
 da_l1l2.fit(xs,ys,xt,reg=reg,eta=eta,numItermax=20,verbose=True)
 xstgl=da_l1l2.interp()
diff --git a/ot/optim.py b/ot/optim.py
@@ -304,7 +304,7 @@ def cost(G):
         deltaG=Gc-G
 
         # line search
-        dcost=Mi+reg1*np.sum(deltaG*(1+np.log(G))) #??
+        dcost=Mi+reg1*(1+np.log(G)) #??
         alpha,fc,f_val = line_search_armijo(cost,G,deltaG,dcost,f_val)
 
         G=G+alpha*deltaG
