2,534 research outputs found
The invisible power of fairness. How machine learning shapes democracy
Many machine learning systems make extensive use of large amounts of data
regarding human behaviors. Several researchers have found various
discriminatory practices related to the use of human-related machine learning
systems, for example in the field of criminal justice, credit scoring and
advertising. Fair machine learning is therefore emerging as a new field of
study to mitigate biases that are inadvertently incorporated into algorithms.
Data scientists and computer engineers are making various efforts to provide
definitions of fairness. In this paper, we provide an overview of the most
widespread definitions of fairness in the field of machine learning, arguing
that the ideas highlighting each formalization are closely related to different
ideas of justice and to different interpretations of democracy embedded in our
culture. This work intends to analyze the definitions of fairness that have
been proposed to date to interpret the underlying criteria and to relate them
to different ideas of democracy.Comment: 12 pages, 1 figure, preprint version, submitted to The 32nd Canadian
Conference on Artificial Intelligence that will take place in Kingston,
Ontario, May 28 to May 31, 201
Academic freedom in Europe: reviewing UNESCO’s recommendation
This paper examines the compliance of universities in the European Union with the UNESCO Recommendation concerning the Status of Higher–Education Teaching Personnel, which deals primarily with protection for academic freedom. The paper briefly surveys the European genesis of the modern research university and academic freedom, before evaluating compliance with the UNESCO recommendation on institutional autonomy, academic freedom, university governance and tenure. Following from this, the paper examines the reasons for the generally low level of compliance with the UNESCO Recommendation within the EU states, and considers how such compliance could be improved
A threshold phenomenon for embeddings of into Orlicz spaces
We consider a sequence of positive smooth critical points of the
Adams-Moser-Trudinger embedding of into Orlicz spaces. We study its
concentration-compactness behavior and show that if the sequence is not
precompact, then the liminf of the -norms of the functions is greater
than or equal to a positive geometric constant.Comment: 14 Page
Implementation of Multidimensional Databases with Document-Oriented NoSQL
International audienceNoSQL (Not Only SQL) systems are becoming popular due to known advantages such as horizontal scalability and elasticity. In this paper, we study the implementation of data warehouses with document-oriented NoSQL systems. We propose mapping rules that transform the multidimensional data model to logical document-oriented models. We consider three different logical models and we use them to instantiate data warehouses. We focus on data loading, model-to-model conversion and OLAP cuboid computation
Spitzer Observations of Low Luminosity Isolated and Low Surface Brightness Galaxies
We examine the infrared properties of five low surface brightness galaxies
(LSBGs) and compare them with related but higher surface brightness galaxies,
using Spitzer Space Telescope images and spectra. All the LSBGs are detected in
the 3.6 and 4.5um bands, representing the stellar population. All but one are
detected at 5.8 and 8.0um, revealing emission from hot dust and aromatic
molecules, though many are faint or point-like at these wavelengths. Detections
of LSBGs at the far-infrared wavelengths, 24, 70, and 160um, are varied in
morphology and brightness, with only two detections at 160um, resulting in
highly varied spectral energy distributions. Consistent with previous
expectations for these galaxies, we find that detectable dust components exist
for only some LSBGs, with the strength of dust emission dependent on the
existence of bright star forming regions. However, the far-infrared emission
may be relatively weak compared with normal star-forming galaxies.Comment: 20 pages, 8 figures, accepted to Ap
Do low surface brightness galaxies have dense disks?
The disk masses of four low surface brightness galaxies (LSB) were estimated
using marginal gravitational stability criterion and the stellar velocity
dispersion data which were taken from Pizzella et al., 2008 [1]. The
constructed mass models appear to be close to the models of maximal disk. The
results show that the disks of LSB galaxies may be significantly more massive
than it is usually accepted from their brightnesses. In this case their surface
densities and masses appear to be rather typical for normal spirals. Otherwise,
unlike the disks of many spiral galaxies, the LSB disks are dynamically
overheated.Comment: 14 pages, 10 figures, submitted to Astronomy Report
Long-time discrete particle effects versus kinetic theory in the self-consistent single-wave model
The influence of the finite number N of particles coupled to a monochromatic
wave in a collisionless plasma is investigated. For growth as well as damping
of the wave, discrete particle numerical simulations show an N-dependent long
time behavior resulting from the dynamics of individual particles. This
behavior differs from the one due to the numerical errors incurred by Vlasov
approaches. Trapping oscillations are crucial to long time dynamics, as the
wave oscillations are controlled by the particle distribution inhomogeneities
and the pulsating separatrix crossings drive the relaxation towards thermal
equilibrium.Comment: 11 pages incl. 13 figs. Phys. Rev. E, in pres
The Invisible Power of Fairness. How Machine Learning Shapes Democracy
Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the field of criminal justice, credit scoring and advertising. Fair machine learning is therefore emerging as a new field of study to mitigate biases that are inadvertently incorporated into algorithms. Data scientists and computer engineers are making various efforts to provide definitions of fairness. In this paper, we provide an overview of the most widespread definitions of fairness in the field of machine learning, arguing that the ideas highlighting each formalization are closely related to different ideas of justice and to different interpretations of democracy embedded in our culture. This work intends to analyze the definitions of fairness that have been proposed to date to interpret the underlying criteria and to relate them to different ideas of democracy
Four Lessons in Versatility or How Query Languages Adapt to the Web
Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”
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