I am looking for an algorithms book that covers material beyond Corman's book.
This can be answered in numerous different ways, depending on what you want "beyond". I would recommend asking much more specific directions, as you are more likely to get specific answers that are helpful. As for some general guidance though:
- You may find a handful of general books that explore general algorithmic topics in more depth than Corman, but for the most part, you need to start specialising if the book is going to be significantly more in depth. Otherwise it is likely to be bloated and lacking in usefulness.
- So, instead look for specific topics. There is plenty of advanced material if you focus on specific topics. Are you intersted in:
- sorting algorithms?
- string algorithms?
- number theoretic algorithms?
- matrix algorithms?
- graph algorithms?
- geometric algorithms?
- quantum algorithms?
- stochastic/randomised algorithms?
- linear programming?
- models of computation?
- foundational complexity theory and algorithmics?
- If you want to understand how to derive your own algorithms, focus on understanding the known data structures used in the problem space you are investgating (so, get good depth of existing knowledge) and look to have a good understanding of complexity theory and models of computation. These will give good intuitive feeling of what is possible for a given problem, and what approaches will likely have better success, even if you have a hard time proving lower bounds formally.
Books like Papadimitriou's several or Arora/Barak on Complexity Theory would be my suggestion for follow up to Corman to understand better what algorithms are possible and build up some intuition, but I would just look to modern overview papers on particular areas and look to graduate and research level books on more specific topics if you want familiarity with the modern level of understanding.