Title
Ordering information on distributions.
Abstract
This thesis details a class of partial orders on the space of probability distributions and the space of density operators which capture the idea of information content. Some links to domain theory and computational linguistics are also discussed. Chapter 1 details some useful theorems from order theory. In Chapter 2 we define a notion of an information ordering on the space of probability distributions and see that this gives rise to a large class of orderings. In Chapter 3 we extend the idea of an information ordering to the space of density operators and in particular look at the maximum eigenvalue order. We will discuss whether this order might be unique given certain restrictions. In Chapter 4 we discuss a possible application in distributional language models, namely in the study of entailment and disambiguation.
Year
Venue
Field
2017
arXiv: Logic in Computer Science
Discrete mathematics,Logical consequence,Computer science,Computational linguistics,Order theory,Algorithm,Domain theory,Probability distribution,Operator (computer programming),Maximum eigenvalue,Language model
DocType
Volume
Citations 
Journal
abs/1701.06924
0
PageRank 
References 
Authors
0.34
0
1
Name
Order
Citations
PageRank
John van de Wetering102.03