53,042 research outputs found
Methods for Interpreting and Understanding Deep Neural Networks
This paper provides an entry point to the problem of interpreting a deep
neural network model and explaining its predictions. It is based on a tutorial
given at ICASSP 2017. It introduces some recently proposed techniques of
interpretation, along with theory, tricks and recommendations, to make most
efficient use of these techniques on real data. It also discusses a number of
practical applications.Comment: 14 pages, 10 figure
Towards an Intelligent Tutor for Mathematical Proofs
Computer-supported learning is an increasingly important form of study since
it allows for independent learning and individualized instruction. In this
paper, we discuss a novel approach to developing an intelligent tutoring system
for teaching textbook-style mathematical proofs. We characterize the
particularities of the domain and discuss common ITS design models. Our
approach is motivated by phenomena found in a corpus of tutorial dialogs that
were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor
for textbook-style mathematical proofs can be built on top of an adapted
assertion-level proof assistant by reusing representations and proof search
strategies originally developed for automated and interactive theorem proving.
The resulting prototype was successfully evaluated on a corpus of tutorial
dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453
Stripe fractionalization I: the generation of Ising local symmetry
This is part one in a series of two papers dedicated to the notion that the
destruction of the topological order associated with stripe phases is about the
simplest theory controlled by local symmetry: Ising gauge theory. This first
part is intended to be a tutorial- we will exploit the simple physics of the
stripes to vividly display the mathematical beauty of the gauge theory.
Stripes, as they occur in the cuprates, are clearly `topological' in the sense
that the lines of charges are at the same time domain walls in the
antiferromagnet. Imagine that the stripes quantum melt so that all what seems
to be around is a singlet superconductor. What if this domain wall-ness is
still around in a delocalized form? This turns out to be exactly the kind of
`matter' which is described by the Ising gauge theory. The highlight of the
theory is the confinement phenomenon, meaning that when the domain wall-ness
gives up it will do so in a meat-and-potato phase transition. We suggest that
this transition might be the one responsible for the quantum criticality in the
cuprates. In part two, we will become more practical, arguing that another
phase is possible according to the theory. It might be that this quantum
spin-nematic has already been observed in strongly underdoped LSCO
A Tutorial on Time-Evolving Dynamical Bayesian Inference
In view of the current availability and variety of measured data, there is an
increasing demand for powerful signal processing tools that can cope
successfully with the associated problems that often arise when data are being
analysed. In practice many of the data-generating systems are not only
time-variable, but also influenced by neighbouring systems and subject to
random fluctuations (noise) from their environments. To encompass problems of
this kind, we present a tutorial about the dynamical Bayesian inference of
time-evolving coupled systems in the presence of noise. It includes the
necessary theoretical description and the algorithms for its implementation.
For general programming purposes, a pseudocode description is also given.
Examples based on coupled phase and limit-cycle oscillators illustrate the
salient features of phase dynamics inference. State domain inference is
illustrated with an example of coupled chaotic oscillators. The applicability
of the latter example to secure communications based on the modulation of
coupling functions is outlined. MatLab codes for implementation of the method,
as well as for the explicit examples, accompany the tutorial.Comment: Matlab codes can be found on http://py-biomedical.lancaster.ac.uk
Effects of diagram format and user numeracy on understanding cash flow data
An issue of longstanding concern in accounting information systems is the effective presentation and communication of financial data to users with little accounting background. Cash flow statements in particular have been singled out as difficult to interpret. To increase user understanding of cash flow data, this study explores the potential merits of diagram formats, as well as possible effects of the user’s numeracy skills. The study covers an experiment (N = 100) in which users were queried on their understanding of the cash flows of a real-world company, and in which type of format was either a cash flow statement or a cash flow diagram. Understanding was measured by three different concepts: interpretation accuracy, company diagnosis, and clarity of presentation. The study confirms that, on those measures, diagrams do not necessarily outperform cash flow statements, and that format familiarity (irrespective of the type of format) is a key driver in understanding cash flows. In addition, the study finds that numeric preference, but not numeric ability, helps in understanding cash flow data. The study discusses the sobering implications for designers of accounting information systems
The future of technology enhanced active learning – a roadmap
The notion of active learning refers to the active involvement of learner in the learning process,
capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap,
the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a
best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap
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