00bfbf96d7c9bcd8653edff6749556719115f3ee,lib/CoLin.py,AsyCoLinUCBUserSharedStruct,updateParameters,#AsyCoLinUCBUserSharedStruct#Any#Any#Any#Any#,50

Before Change

		//self.currentW = np.dot(self.currentW, self.W)
		//X = vectorize(np.outer(articlePicked.contextFeatureVector, self.currentW.T[userID])) 	
		
		X = vectorize(np.outer(articlePicked.contextFeatureVector, self.W.T[userID])) 
		self.A += np.outer(X, X)	
		self.b += click*X
		if update == "Inv":
			self.AInv =  np.linalg.inv(self.A)
		else:
			self.AInv = self.AInv - float(np.dot(self.AInv, np.dot(outer, self.AInv)))/(1.0+np.dot(np.transpose(X), np.dot(self.AInv, X)  ))
		

		self.UserTheta = matrixize(np.dot(self.AInv, self.b), len(articlePicked.contextFeatureVector)) 
		self.CoTheta = np.dot(self.UserTheta, self.W)

After Change

		self.BigW = np.kron(np.transpose(W), np.identity(n=featureDimension))

		self.CCA = np.dot(np.dot(self.BigW , self.AInv), np.transpose(self.BigW))

		self.alpha_t = 0.0
		self.sigma = 1.e-200   //Used in the high probability bound, i.e, with probability at least (1 - sigma) the confidence bound. So sigma should be very small
		self.lambda_ = lambda_
	def updateParameters(self, articlePicked, click,  userID, update="Inv"):
		X = vectorize(np.outer(articlePicked.contextFeatureVector, self.W.T[userID]))

Instances