I have been given the opportunity to work with a phd student to do research. He said that something that he would like to work on with me is a topic on Convex Optimization. He gave me this paper to read chapters 1-6 which I will link here: http://stanford.edu/~boyd/papers/pdf/admm_distr_stats.pdf I read the first two chapters and I had some ideas of what was going on but I didn't have the same mathematical intuition that I have with math that I can fully grasp. He told me to read a textbook called convex optimization first which will help me to better understand what is going on in the research paper. In the text book introduction it says: "The only background required of the reader is a good knowledge of advanced calculus and linear algebra. If the reader has seen basic mathematical analysis (e.g., norms, convergence, elementary topology), and basic probability theory, he or she should be able to follow every argument and discussion in the book. " I'm currently a junior studying computer engineering so I have completed all of the required calculus and liner algebra as well as basic probability. I am not so sure that this is the same math that they are describing here because I am very good with the calculus from school, but a lot of these things go over my head. If someone could give me some advices on what I should know to have a solid understanding of convex optimization that would be very helpful.