Sharif Digital Repository

Learning is the process of transforming experience into expertise. Machine learning is the automation of this process by a machine, where data is received as input and learned expertise is produced as output. This becomes especially important when the volume of input data is large and it is impossible for humans to detect the patterns within it. In this thesis, we study a precise mathematical model of learning, known as Probably Approximately Correct (PAC), that was first introduced by Valiant, who received the Turing Award for his research in this area. Based on the PAC model, the notion of learnability of a problem is formalized, and we observe that not all problems are learnable, and even...