def power_iteration(m, iterations, v0):
v = CuckooVector({})
v.add(v0)
for i in range(iterations):
v = m.mult_vec(v)
mu = v.norm(2)
v.scale(1.0/mu)
return mu,v
def power_iteration_mmt(m, iterations, v0):
v = CuckooVector({})
v.add(v0)
for i in range(iterations):
vp = CuckooVector({})
for c in m:
vp.add_scale(c, c.dot(v))
mu = vp.norm(2)
vp.scale(1.0/mu)
v = vp
return mu,v
def svm_primal_sgd(X, Y, lam, T):
w = CuckooVector({})
x = CuckooVector({})
m = len(Y)
for t in range(T):
step = 1 / (lam * (t+1))
i = np.random.randint(m)
y = Y[i]
x.reset(X[i])
w.scale(1 - step * lam)
if y * w.dot(x) < 1:
w.add_scale(x, step * y)
return w
def pegasos(lam):
w = CuckooVector({})
wx = 0
t = 0
# while True:
# example = yield (w,wx)
# if example == None: break
# x,y = example
for xy in (yield (w, wx)):
x, y = xy
print(x)
print(y)
step = 1 / (lam * (t + 1))
w.scale(1 - step * lam)
wx = w.dot(x)
if y * wx < 1:
w.add_scale(x, step * y)
t = t + 1
def power_iteration_4(Y, X, U, S, iterations, v0):
v = CuckooVector({})
v.add(v0)
for i in range(iterations):
v1 = CuckooVector({})
for (x,y) in zip(X,Y):
v1.add_scale_dict(x, v.dot_dict(y))
v2 = CuckooVector({})
for (x,y) in zip(X,Y):
v2.add_scale_dict(y, v1.dot_dict(x))
for (u,s) in zip(U,S):
print(-s * u.dot(v))
v2.add_scale(u, -s * u.dot(v))
mu = v2.norm(2)
v2.scale(1.0/mu)
v = v2
return mu,v
