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Designed for use in a four, five or six unit Property course, this casebook applies traditional property concepts in a distinctly modern context. The book begins with fundamental Property principles and concepts, followed by personal property with an introduction to intellectual property. Subsequent chapters cover present and future interests, concurrent estates, landlord and tenant law, real estate transactions, easements, covenants, and public land use regulation (including zoning, eminent domain and regulatory takings, and constitutional challenges based on due process, equal protection, freedom of speech and freedom of religion). The book is accompanied by a detailed Teacher's Manual.
Property Testing: A Learning Theory Perspective takes the learning-theory point of view of property testing and focuses on results for testing properties of functions that are of interest to the learning theory community. In particular it covers results for testing algebraic properties of functions such as linearity, testing properties defined by concise representations, such as having a small DNF representation, and more. Property Testing: A Learning Theory Perspective starts with some preliminaries, including a precise statement and proof of the simple but important observation that testing is no harder than learning. It goes on to consider the first type of properties that were studied in the context of property testing: algebraic properties. These include testing whether a function is (multi-)linear and more generally whether it is a polynomial of bounded degree. It then turns to the study of function class that have a concise (propositional logic) representation such as singletons, monomials and small DNF formula. It proceeds to discuss distribution free testing, and testing from random examples alone. Finally, it contains a brief survey of other results in property testing. These include testing monotonicity, testing of clustering, testing properties of distributions, and more. Property Testing: A Learning Theory Perspective is an ideal text for anybody with an interest in property testing and how it connects to topics in machine learning.
The rule of lex specialis serves as an interpretative method to determine which of two contesting norms should be used to govern. In this book, the lex specialis label is broadly applied to intellectual property and connects a series of questions: What is the scope of intellectual property law? What is the relationship between intellectual property law and general legal principles? To what extent are intellectual property laws exceptional? Intellectual property assumes a prominent social and economic role worldwide and considering the costs and benefits of treating it separately from general principles of law is a salient area of enquiry. This thought-provoking book addresses the essence of intellectual property law and the role of intellectual property within broader legal institutions. Expert contributors explore lines of enquiry from a variety of more general perspectives and engage with and contribute to an area of law that is too significant socially and commercially to be considered only by specialists. Intellectual Property and General Legal Principles is a challenging book which scholars in intellectual property law will find a discerning contribution to their field.
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