Tower multiplexing and slow weak mixing

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Topological Weak Mixing and Quasi-bohr Systems

A minimal dynamical system (X,T ) is called quasi-Bohr if it is a nontrivial equicontinuous extension of a proximal system. We show that if (X,T ) is a minimal dynamical system which is not weakly mixing then some minimal proximal extension of (X, T ) admits a nontrivial quasi-Bohr factor. (In terms of Ellis groups the corresponding statement is: AG′ = G implies weak mixing.) The converse does ...

متن کامل

Community Detection Using Slow Mixing Markov Models

The task of community detection in a graph formalizes the intuitive task of grouping together subsets of vertices such that vertices within clusters are connected tighter than those in disparate clusters. This paper approaches community detection in graphs by constructing Markov random walks on the graphs. The mixing properties of the random walk are then used to identify communities. We use co...

متن کامل

Slow mixing for Latent Dirichlet allocation

Markov chain Monte Carlo (MCMC) algorithms are ubiquitous in probability theory in general and in machine learning in particular. A Markov chain is devised so that its stationary distribution is some probability distribution of interest. Then one samples from the given distribution by running the Markov chain for a ”long time” until it appears to be stationary and then collects the sample. Howe...

متن کامل

Weak Mixing Properties for Nonsingular Actions

For a general group G we consider various weak mixing properties of nonsingular actions. In the case where the action is actually measure preserving all these properties coincide, and our purpose here is to check which implications persist in the nonsingular case.

متن کامل

Mixing Weak Learners In Semantic Parsing

We apply a novel variant of Random Forests (Breiman, 2001) to the shallow semantic parsing problem and show extremely promising results. The final system has a semantic role classification accuracy of 88.3% using PropBank gold-standard parses. These results are better than all others published except those of the Support Vector Machine (SVM) approach implemented by Pradhan et al. (2003) and Ran...

متن کامل

ذخیره 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: Colloquium Mathematicum

سال: 2015

ISSN: 0010-1354,1730-6302

DOI: 10.4064/cm138-1-4