Simplicial fixed point algorithms
نویسندگان
چکیده
منابع مشابه
Focusing on the Fixed Point of 4d Simplicial Gravity
Our earlier renormalization group study of simplicial gravity is extended and the evidence for the existence of an isolated ultra-violet fixed point is strengthened. A high statistics study of the volume and coupling constant dependence of the cumulants of the node distribution is carried out. It appears that the phase transition of the theory is of first order, contrary to what is generally be...
متن کاملThe fixed point theorem for simplicial nonpositive curvature
We prove that for an action of a finite group G on a systolic complex X there exists a G–invariant subcomplex of X of diameter 5. For 7–systolic locally finite complexes we prove there is a fixed point for the action of any finite G. This implies that free products with amalgamation (and HNN extensions) of 7–systolic groups over finite subgroups are also 7–systolic.
متن کاملApplications of Fixed Point and Approximate Algorithms
As very powerful and important tools in the study of nonlinear sciences, fixed point methods have attracted so much attention. Over the last decades, fixed point techniques have been applied extensively in such diverse fields as biology, chemistry, economics, engineering, game theory, physics, and so on. The thorough study of the fixed point theory and its approach methods contained in the lite...
متن کاملSQNR Estimation of Fixed-Point DSP Algorithms
A fast and accurate quantization noise estimator aiming at fixed-point implementations of Digital Signal Processing (DSP) algorithms is presented. The estimator enables significant reduction in the computation time required to perform complex wordlength optimizations. The proposed estimator is based on the use of Affine Arithmetic (AA) and it is presented in two versions: (i) a general version ...
متن کاملFixed-point algorithms for learning determinantal point processes
Determinantal point processes (DPPs) offer an elegant tool for encoding probabilities over subsets of a ground set. Discrete DPPs are parametrized by a positive semidefinite matrix (called the DPP kernel), and estimating this kernel is key to learning DPPs from observed data. We consider the task of learning the DPP kernel, and develop for it a surprisingly simple yet effective new algorithm. O...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistica Neerlandica
سال: 1981
ISSN: 0039-0402,1467-9574
DOI: 10.1111/j.1467-9574.1981.tb00712.x