
Additive combinatorics is the theory of counting additive structures in sets. This theory has seen exciting developments and dramatic changes in direction in recent years thanks to its connections with areas such as number theory, ergodic theory and graph theory. This graduate-level 2006 text will allow students and researchers easy entry into this fascinating field. Here, the authors bring together in a self-contained and systematic manner the many different tools and ideas that are used in the modern theory, presenting them in an accessible, coherent, and intuitively clear manner, and providing immediate applications to problems in additive combinatorics. The power of these tools is well demonstrated in the presentation of recent advances such as Szemerédi's theorem on arithmetic progressions, the Kakeya conjecture and Erdos distance problems, and the developing field of sum-product estimates. The text is supplemented by a large number of exercises and new results.
Dummit and Foote's Abstract Algebra is an excellent book -- even if not very directly relevant to additive combinatorics. Analysis background would be useful, such as to be found in Stein and Shakarchi's series. Some introductory combinatorics would also be good (e.g. Stanley's Enumerative Combinatorics, or Van Lint and Wilson).
Finally, analytic number theory would also be good to learn. For example, you might read Davenport's Multiplicative Number Theory. (Especially if you want to see integrals come into the picture.)
Also, most of the books I mentioned have about 50% dedicated to core ideas in the field and 50% dedicated to some specific tools that may not be that useful to you. More often than not the second 50% is the latter part of the book, but in say Concrete Mathematics it is spread throughout the book entirely. I know it's hard to find the balance between reading fast (and then realizing you don't remember anything from the basic tools and you can't even apply them well) and reading slow (and realizing you're trying to memorize some obscure recurrence involving binomial coefficients). Reading is hard.
Now, for the tips for the CS/discrete math students among you. Feel free to add some of yours, I'm hardly the veteran educator here.
Knuth, Graham, Patashnik's Concrete Mathematics, after a few chapters, goes well with Flajolet, Sedgewick's Analytic Combinatorics. You should mix that up with some Discrete Mathematics introductory book, especially one dealing with counting objects, so you can apply the techniques almost immediately on simpler examples.
Papadimitrou, Dasgupta, Vazirani's Algorithms is one of the better books on algorithms out there, in my opinion. As for the graph theory books I read, I liked Bondy, Murty's Graph Theory style the most, so I'd probably go with that, though I haven't really read them in parallel yet.
For the discrete math students out there, after learning the basics of probablistic method (Alon, Spencer's Probabilistic Method being the seminal textbook, I think), you could continue with both some probabilistic algorithm book to apply what you've learned in CS (I did take a course in that, though, so I can't vouch for the best book out there) and you could also grab Tao, Vu's Additive Combinatorics for how to apply probability in number theory (probabilistic method is chapter one in there).
http://www.amazon.com/Additive-Combinatorics-Cambridge-Advan...
the additive combinatorics book by terry tao and van vu give some amazing examples of this