49 research outputs found
Translating and Evolving: Towards a Model of Language Change in DisCoCat
The categorical compositional distributional (DisCoCat) model of meaning
developed by Coecke et al. (2010) has been successful in modeling various
aspects of meaning. However, it fails to model the fact that language can
change. We give an approach to DisCoCat that allows us to represent language
models and translations between them, enabling us to describe translations from
one language to another, or changes within the same language. We unify the
product space representation given in (Coecke et al., 2010) and the functorial
description in (Kartsaklis et al., 2013), in a way that allows us to view a
language as a catalogue of meanings. We formalize the notion of a lexicon in
DisCoCat, and define a dictionary of meanings between two lexicons. All this is
done within the framework of monoidal categories. We give examples of how to
apply our methods, and give a concrete suggestion for compositional translation
in corpora.Comment: In Proceedings CAPNS 2018, arXiv:1811.0270
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Parallels in the sequential organization of birdsong and human speech.
Human speech possesses a rich hierarchical structure that allows for meaning to be altered by words spaced far apart in time. Conversely, the sequential structure of nonhuman communication is thought to follow non-hierarchical Markovian dynamics operating over only short distances. Here, we show that human speech and birdsong share a similar sequential structure indicative of both hierarchical and Markovian organization. We analyze the sequential dynamics of song from multiple songbird species and speech from multiple languages by modeling the information content of signals as a function of the sequential distance between vocal elements. Across short sequence-distances, an exponential decay dominates the information in speech and birdsong, consistent with underlying Markovian processes. At longer sequence-distances, the decay in information follows a power law, consistent with underlying hierarchical processes. Thus, the sequential organization of acoustic elements in two learned vocal communication signals (speech and birdsong) shows functionally equivalent dynamics, governed by similar processes
Decomposing spiking neural networks with Graphical Neural Activity Threads
A satisfactory understanding of information processing in spiking neural
networks requires appropriate computational abstractions of neural activity.
Traditionally, the neural population state vector has been the most common
abstraction applied to spiking neural networks, but this requires artificially
partitioning time into bins that are not obviously relevant to the network
itself. We introduce a distinct set of techniques for analyzing spiking neural
networks that decomposes neural activity into multiple, disjoint, parallel
threads of activity. We construct these threads by estimating the degree of
causal relatedness between pairs of spikes, then use these estimates to
construct a directed acyclic graph that traces how the network activity evolves
through individual spikes. We find that this graph of spiking activity
naturally decomposes into disjoint connected components that overlap in space
and time, which we call Graphical Neural Activity Threads (GNATs). We provide
an efficient algorithm for finding analogous threads that reoccur in large
spiking datasets, revealing that seemingly distinct spike trains are composed
of similar underlying threads of activity, a hallmark of compositionality. The
picture of spiking neural networks provided by our GNAT analysis points to new
abstractions for spiking neural computation that are naturally adapted to the
spatiotemporally distributed dynamics of spiking neural networks
Spike Train Coactivity Encodes Learned Natural Stimulus Invariances in Songbird Auditory Cortex.
A General Theory of the Optimum Plan of Financing
95 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1964.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
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Adolescent influence on household purchases
This study assesses adolescents\u27 influence on household purchase decisions. The data analyzed were from a survey of 281 fourteen and sixteen year old male and female students from three area school districts in Western Massachusetts. The sample represented blue and white collar families in suburban, urban and rural areas. The objectives of this study were: to determine the amount of influence teenagers exert over household purchases of low and high priced consumer durables and non-durables; to identify factors that influence teenagers\u27 choice of consumer goods; and to identify adolescents\u27 sources of consumer information. The study utilized a questionnaire developed by the researcher which in addition to questions related to teenagers\u27 influence on household purchases, included items concerning family composition, ethnic background, employment, individual earnings, and parents\u27 employment status. The study revealed that adolescents have an important role in family decision making and represent a substantial economic force in the U.S