Understanding Fixed Point Theorems

Fixed point theorems are the standard tool used to prove the existence of equilibria in mathematical economics. This paper shows how to prove a slight generalization of Brouwer's and Kakutani's fixed point theorems using the familiar techniques of drawing and shifting curves in the plane and is, therefore, intelligible without advanced knowledge of topology. This makes proofs of fixed point theorems accessible to a broader audience.Kurvenverschieben in der Ebene' beweisen lassen. Das wichtigste Instrument für Existenzsätze in der mathematischen Volkswirtschaftslehre sind Fixpunkttheoreme. Dieses Papier zeigt, wie sich Brouwers Fixpunktsatz und einige geringfügige Verallgemeinerungen durch 'Kurvenverschieben in der Ebene' beweisen lassen. Weil keine tiefen topologischen Vorkenntnisse notwendig sind, ist der grafische Beweis für einen breiten Adressatenkreis zugänglich

The Mermin fixed point

The most efficient known method for solving certain computational problems is to construct an iterated map whose fixed points are by design the problem's solution. Although the origins of this idea go back at least to Newton, the clearest expression of its logical basis is an example due to Mermin. A contemporary application in image recovery demonstrates the power of the method.Comment: Contribution to Mermin Festschrift; 8 pages, 5 figure

Fixed-point Factorized Networks

In recent years, Deep Neural Networks (DNN) based methods have achieved remarkable performance in a wide range of tasks and have been among the most powerful and widely used techniques in computer vision. However, DNN-based methods are both computational-intensive and resource-consuming, which hinders the application of these methods on embedded systems like smart phones. To alleviate this problem, we introduce a novel Fixed-point Factorized Networks (FFN) for pretrained models to reduce the computational complexity as well as the storage requirement of networks. The resulting networks have only weights of -1, 0 and 1, which significantly eliminates the most resource-consuming multiply-accumulate operations (MACs). Extensive experiments on large-scale ImageNet classification task show the proposed FFN only requires one-thousandth of multiply operations with comparable accuracy

Layered Fixed Point Logic

We present a logic for the specification of static analysis problems that goes beyond the logics traditionally used. Its most prominent feature is the direct support for both inductive computations of behaviors as well as co-inductive specifications of properties. Two main theoretical contributions are a Moore Family result and a parametrized worst case time complexity result. We show that the logic and the associated solver can be used for rapid prototyping and illustrate a wide variety of applications within Static Analysis, Constraint Satisfaction Problems and Model Checking. In all cases the complexity result specializes to the worst case time complexity of the classical methods

Fixed Point and Aperiodic Tilings

An aperiodic tile set was first constructed by R.Berger while proving the undecidability of the domino problem. It turned out that aperiodic tile sets appear in many topics ranging from logic (the Entscheidungsproblem) to physics (quasicrystals) We present a new construction of an aperiodic tile set that is based on Kleene's fixed-point construction instead of geometric arguments. This construction is similar to J. von Neumann self-reproducing automata; similar ideas were also used by P. Gacs in the context of error-correcting computations. The flexibility of this construction allows us to construct a "robust" aperiodic tile set that does not have periodic (or close to periodic) tilings even if we allow some (sparse enough) tiling errors. This property was not known for any of the existing aperiodic tile sets.Comment: v5: technical revision (positions of figures are shifted