Thu 01 Dec 2011, 6:00pm  Winstanley Lecture Hall, Trinity College
Professor Alex Clark (Royal Holloway, University of London) speaks on

The fundamental problem of linguistics is to find how knowledge of language is represented and how that knowledge is acquired by children learning their first language; understanding or solving this problem would open the door to a new generation of intelligent language processing systems. This is fundamentally a computational problem, which can be studied using the tools of formal language theory and computational learning. Solving it requires reconceptualising some basic concepts  including the relationship between a grammar and the language it defines.
In this talk I will give an overview of this field (assuming no prior knowledge of linguistics or machine learning) and discuss some recent technical results in distributional learning that can potentially provide a solution to this problem. These techniques involve modelling the relationship between substrings and the contexts that they can appear in  these give rise to algorithms for learning classes of context free and context sensitive languages that seem to be a good match for the properties of natural language.
Unsupervised Machine Learning and LinguisticsThe fundamental problem of linguistics is to find how knowledge of language is represented and how that knowledge is acquired by children learning their first language; understanding or solving this problem would open the door to a new generation of intelligent language processing systems. This is fundamentally a computational problem, which can be studied using the tools of formal language theory and computational learning. Solving it requires reconceptualising some basic concepts  including the relationship between a grammar and the language it defines.
In this talk I will give an overview of this field (assuming no prior knowledge of linguistics or machine learning) and discuss some recent technical results in distributional learning that can potentially provide a solution to this problem. These techniques involve modelling the relationship between substrings and the contexts that they can appear in  these give rise to algorithms for learning classes of context free and context sensitive languages that seem to be a good match for the properties of natural language.
Alex ClarkRoyal Holloway, University of London A concept we refer to as the biological constraint is shown to be able where id=11;
to explain the effectiveness of mathematical descriptions of the
universe, as well as accounting for the origin of life and our ability
to think logically. The biological constraint, which can be studied
systematically through the use of appropriate models, refers to
selection in the biological realm in favour of mechanisms that have wide
applicability, a subset of which have mathematical character that can
evolve to ever subtler forms. The precise conformance of physical
phenomena to precise mathematical laws is related to the enforcement of
symmetry.

Miscellanea Speaker's slides (PDF) 