The term "beyond category," from my limited knowledge, was originally coined to describe the music of Duke Ellington. It is a term of praise that acknowledges that one's style is inimitable and transcends barriers.
"Beyond Categories" was the first part of my NIPS 2009 paper's title. To "go beyond" means to transcend, to abandon or do without some limitation and strive higher -- there is nothing magical about my use of the term. I used the term category to refer to object categories, as are commonly used in computer vision, artificial intelligence, machine learning, as well as psychology, philosophy, and other branches of cognitive science. One of my research goals is to go beyond the use of categories as the basis for machine perception and visual reasoning. It has been argued by Machery that the term category is roughly equivalent to the term concept as used in psychology literature. In some sense the title of Machery's recent book, "Doing without concepts," is analogous to the phrase "Beyond categories" but to reassure myself I'll have to finish reading Machery's book.
So far the first chapter has been a delightful exposition into the world of concepts, a term dear to researchers in machine perception (AI) as well as human categorization (psychology). I look forward to reading the rest of the book, which I accidentally found while looking for Estes' book on categorization. I had already digested/assimilated some of Machery's work, in particular his paper titled Concepts are not a natural kind, so seeing his name on a book at the CMU library piqued my interest. In this 2005 paper, Machery argues that the debate between prototypes vs. exemplars vs. theories in the literature on concepts is not well-founded and there is no reason to believe a single theory should prevail. I'll attempt to summarize some of his take-home messages and their relevance to computer vision once I finish this book.