Multilinear Grammar: Ranks and Interpretations

نویسندگان

  • Dafydd Gibbon
  • Sascha S. Griffiths
چکیده

Multilinear Grammar provides a framework for integrating the many different syntagmatic structures of language into a coherent semiotically based Rank Interpretation Architecture, with default linear grammars at each rank. The architecture defines a Sui Generis Condition on ranks, from discourse through utterance and phrasal structures to the word, with its sub-ranks of morphology and phonology. Each rank has unique structures and its own semantic-pragmatic and prosodic-phonetic interpretation models. Default computational models for each rank are proposed, based on a Procedural Plausibility Condition: incremental processing in linear time with finite working memory. We suggest that the Rank Interpretation Architecture and its multilinear properties provide systematic design features of human languages, contrasting with unordered lists of key properties or single structural properties at one rank, such as recursion, which have previously been been put forward as language design features. The framework provides a realistic background for the gradual development of complexity in the phylogeny and ontogeny of language, and clarifies a range of challenges for the evaluation of realistic linguistic theories and applications. The empirical objective of the paper is to demonstrate unique multilinear properties at each rank and thereby motivate the Multilinear Grammar and Rank Interpretation Architecture framework as a coherent approach to capturing the complexity of human languages in the simplest possible way.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Recompression of Hadamard Products of Tensors in Tucker Format

The Hadamard product features prominently in tensor-based algorithms in scientific computing and data analysis. Due to its tendency to significantly increase ranks, the Hadamard product can represent a major computational obstacle in algorithms based on low-rank tensor representations. It is therefore of interest to develop recompression techniques that mitigate the effects of this rank increas...

متن کامل

Tensor Network Ranks

In problems involving approximation, completion, denoising, dimension reduction, estimation, interpolation, modeling, order reduction, regression, etc, we argue that the near-universal practice of assuming that a function, matrix, or tensor (which we will see are all the same object in this context) has low rank may be ill-justified. There are many natural instances where the object in question...

متن کامل

Random Projections for Low Multilinear Rank Tensors

We proposed two randomized tensor algorithms for reducing multilinear ranks in the Tucker format. The basis of these randomized algorithms is from the randomized SVD of Halko, Martinsson and Tropp [9]. Here we provide randomized versions of the higher order SVD and higher order orthogonal iteration. Moreover, we provide a sharper probabilistic error bounds for the matrix low rank approximation....

متن کامل

Structure-Preserving Low Multilinear Rank Approximation of Antisymmetric Tensors

This paper is concerned with low multilinear rank approximations to antisymmetric tensors, that is, multivariate arrays for which the entries change sign when permuting pairs of indices. We show which ranks can be attained by an antisymmetric tensor and discuss the adaption of existing approximation algorithms to preserve antisymmetry, most notably a Jacobi algorithm. Particular attention is pa...

متن کامل

Learning Modewise Independent Components from Tensor Data Using Multilinear Mixing Model

Independent component analysis (ICA) is a popular unsupervised learning method. This paper extends it to multilinear modewise ICA (MMICA) for tensors and explores two architectures in learning and recognition. MMICA models tensor data as mixtures generated from modewise source matrices that encode statistically independent information. Its sources have more compact representations than the sour...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1609.05511  شماره 

صفحات  -

تاریخ انتشار 2016