2,376 research outputs found
Populations in statistical genetic modelling and inference
What is a population? This review considers how a population may be defined
in terms of understanding the structure of the underlying genetics of the
individuals involved. The main approach is to consider statistically
identifiable groups of randomly mating individuals, which is well defined in
theory for any type of (sexual) organism. We discuss generative models using
drift, admixture and spatial structure, and the ancestral recombination graph.
These are contrasted with statistical models for inference, principle component
analysis and other `non-parametric' methods. The relationships between these
approaches are explored with both simulated and real-data examples. The
state-of-the-art practical software tools are discussed and contrasted. We
conclude that populations are a useful theoretical construct that can be well
defined in theory and often approximately exist in practice
A Sectoral Model of the Australian Economy
We use a structural vector autoregression (SVAR) to examine the effect of unanticipated changes in monetary policy on the expenditure and production components of GDP over the period from 1983 to 2007. We find that dwelling investment and machinery & equipment investment are the most interest-sensitive expenditure components of activity, and that construction and retail trade are the most interest-sensitive production components of activity. We subject our model to a range of sensitivity checks and find that our results are robust to omitted variables, alternative identification schemes and the time period over which our model is estimated.Australian economy; sectoral macroeconomic model; monetary policy
Distributive inverse semigroups and non-commutative Stone dualities
We develop the theory of distributive inverse semigroups as the analogue of
distributive lattices without top element and prove that they are in a duality
with those etale groupoids having a spectral space of identities, where our
spectral spaces are not necessarily compact. We prove that Boolean inverse
semigroups can be characterized as those distributive inverse semigroups in
which every prime filter is an ultrafilter; we also provide a topological
characterization in terms of Hausdorffness. We extend the notion of the patch
topology to distributive inverse semigroups and prove that every distributive
inverse semigroup has a Booleanization. As applications of this result, we give
a new interpretation of Paterson's universal groupoid of an inverse semigroup
and by developing the theory of what we call tight coverages, we also provide a
conceptual foundation for Exel's tight groupoid.Comment: arXiv admin note: substantial text overlap with arXiv:1107.551
Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN
Over the past few years machine learning has seen a renewed explosion of
interest, following a number of studies showing the effectiveness of neural
networks in a range of tasks which had previously been considered incredibly
hard. Neural networks' effectiveness in the fields of image recognition and
natural language processing stems primarily from the vast amounts of data
available to companies and researchers, coupled with the huge amounts of
compute power available in modern accelerators such as GPUs, FPGAs and ASICs.
There are a number of approaches available to developers for utilizing GPGPU
technologies such as SYCL, OpenCL and CUDA, however many applications require
the same low level mathematical routines. Libraries dedicated to accelerating
these common routines allow developers to easily make full use of the available
hardware without requiring low level knowledge of the hardware themselves,
however such libraries are often provided by hardware manufacturers for
specific hardware such as cuDNN for Nvidia hardware or MIOpen for AMD hardware.
SYCL-DNN is a new open-source library dedicated to providing accelerated
routines for neural network operations which are hardware and vendor agnostic.
Built on top of the SYCL open standard and written entirely in standard C++,
SYCL-DNN allows a user to easily accelerate neural network code for a wide
range of hardware using a modern C++ interface. The library is tested on AMD's
OpenCL for GPU, Intel's OpenCL for CPU and GPU, ARM's OpenCL for Mali GPUs as
well as ComputeAorta's OpenCL for R-Car CV engine and host CPU. In this talk we
will present performance figures for SYCL-DNN on this range of hardware, and
discuss how high performance was achieved on such a varied set of accelerators
with such different hardware features.Comment: 4 pages, 3 figures. In International Workshop on OpenCL (IWOCL '19),
May 13-15, 2019, Bosto
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Peer Observation, Reflection, and evaluation Practices in the Writing Center: A Genre Pedagogy Approach
In this essay, the author shares the results of a local assessment
conducted on his centerâs peer observation, reflection, and
evaluation practices for graduate assistants (GAs), focusing
especially on the form used to facilitate these practices. The author
interviewed the participants and analyzed completed âWriting
Center Graduate Assistant Observationâ forms. The interviews
focused on three major areas: 1) what they perceived the purpose
of the observation and reflection exercise to be, 2) how they felt
and what they learned about observing their peers and being
observed, and 3) how they felt the form affected the observation
and reflection. In brief, the author argues that melding evaluation
and consultant self-reflection is fraught because the rhetorical
situation of each requires markedly different social action. Two
critical lenses guide this examination: reflective practice and genre
pedagogy. Ultimately, the author cautions those who use
observation and reflection in their assessments to consider
carefully the documents and genres surrounding those assessments
because these genres may (intentionally or not) draw on antecedent
genres that are inappropriate for the social action they intend to
facilitate. Perhaps more troubling, some of these genres may
implicitly draw on and/or perpetuate ideologies that are
fundamentally at odds with reflective practice.University Writing Cente
Invariant means on Boolean inverse monoids
The classical theory of invariant means, which plays an important role in the
theory of paradoxical decompositions, is based upon what are usually termed
`pseudogroups'. Such pseudogroups are in fact concrete examples of the Boolean
inverse monoids which give rise to etale topological groupoids under
non-commutative Stone duality. We accordingly initiate the theory of invariant
means on arbitrary Boolean inverse monoids. Our main theorem is a
characterization of when a Boolean inverse monoid admits an invariant mean.
This generalizes the classical Tarski alternative proved, for example, by de la
Harpe and Skandalis, but using different methods
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