4,120 research outputs found
Generating Artificial Data for Private Deep Learning
In this paper, we propose generating artificial data that retain statistical
properties of real data as the means of providing privacy with respect to the
original dataset. We use generative adversarial network to draw
privacy-preserving artificial data samples and derive an empirical method to
assess the risk of information disclosure in a differential-privacy-like way.
Our experiments show that we are able to generate artificial data of high
quality and successfully train and validate machine learning models on this
data while limiting potential privacy loss.Comment: Privacy-Enhancing Artificial Intelligence and Language Technologies,
AAAI Spring Symposium Series, 201
Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge
We study minimal single-task peer prediction mechanisms that have limited
knowledge about agents' beliefs. Without knowing what agents' beliefs are or
eliciting additional information, it is not possible to design a truthful
mechanism in a Bayesian-Nash sense. We go beyond truthfulness and explore
equilibrium strategy profiles that are only partially truthful. Using the
results from the multi-armed bandit literature, we give a characterization of
how inefficient these equilibria are comparing to truthful reporting. We
measure the inefficiency of such strategies by counting the number of dishonest
reports that any minimal knowledge-bounded mechanism must have. We show that
the order of this number is , where is the number of
agents, and we provide a peer prediction mechanism that achieves this bound in
expectation
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints
We study a problem of optimal information gathering from multiple data
providers that need to be incentivized to provide accurate information. This
problem arises in many real world applications that rely on crowdsourced data
sets, but where the process of obtaining data is costly. A notable example of
such a scenario is crowd sensing. To this end, we formulate the problem of
optimal information gathering as maximization of a submodular function under a
budget constraint, where the budget represents the total expected payment to
data providers. Contrary to the existing approaches, we base our payments on
incentives for accuracy and truthfulness, in particular, {\em peer-prediction}
methods that score each of the selected data providers against its best peer,
while ensuring that the minimum expected payment is above a given threshold. We
first show that the problem at hand is hard to approximate within a constant
factor that is not dependent on the properties of the payment function.
However, for given topological and analytical properties of the instance, we
construct two greedy algorithms, respectively called PPCGreedy and
PPCGreedyIter, and establish theoretical bounds on their performance w.r.t. the
optimal solution. Finally, we evaluate our methods using a realistic crowd
sensing testbed.Comment: Longer version of AAAI'18 pape
Learning to cope with an open world
Science has developed detailed and well-founded theories for analyzing the behavior of artifacts. For example, Boeing was able to correctly verify an entirely new airplane, the Boeing 777, before any prototype was even built. However, there are few theories, and no computer systems, that would allow us to design structures with a similar degree of automatio
Pla de salut de Catalunya 2011-2015. Presentació
Pla de salut de Catalunya; Polítiques públiques de salut; Gestió sanitàriaPlan de Salud de Cataluña; Políticas públicas de salud; Gestión sanitariaHealth Plan of Catalonia; Public health policies; Health managementEn el marc del segle xxi, les polítiques sanitàries dels governs han de tenir com a finalitat última procurar més anys de vida per a les persones i que aquests anys siguin viscuts amb salut. I cal aconseguir-ho amb independència de la condició social o econòmica dels ciutadans. Per tal de preservar el dret a la protecció de la salut de què gaudeixen els ciutadans, el Govern ofereix una resposta triple. En primer lloc, protegir la salut individual i col·lectiva, objectiu que canalitzen l’Agència de Salut Pública de Catalunya i les polítiques interdepartamentals. En segon lloc, atendre mèdicament i sanitàriament les persones malaltes, la qual cosa garanteix el Servei Català de la Salut. Per acabar i en tercer lloc, desenvolupar la recerca biomèdica, la qual cosa es duu a terme mitjançant el Programa de recerca i innovació de Catalunya.En el marco del siglo XXI, las políticas sanitarias de los gobiernos deben tener como finalidad última procurar más años de vida para las personas y que estos años sean vividos con salud. Y hay que conseguirlo con independencia de la condición social o económica de los ciudadanos. Con el fin de preservar el derecho a la protección de la salud de que gozan los ciudadanos, el Gobierno ofrece una respuesta triple. En primer lugar, proteger la salud individual y colectiva, objetivo que canalizan la Agencia de Salud Pública de Cataluña y las políticas interdepartamentales. En segundo lugar, atender médicamente y sanitariamente las personas enfermas, lo que garantiza el Servicio Catalán de la Salud. Por último y en tercer lugar, desarrollar la investigación biomédica, lo que se lleva a cabo mediante el Programa de investigación e innovación de Cataluña.Within the framework of the 21st century, the health policies of governments must have as their ultimate purpose to seek more years of life for the people and that these years be lived with health. And we must achieve this regardless of the social or economic condition of the citizens. In order to preserve the right to health protection enjoyed by the citizens, the Government offers a triple response. First of all, protect individual and collective health, an objective channeled by the Public Health Agency of Catalonia and interdepartmental policies. Secondly, medical and health care is given to sick people, which guarantees the Catalan Health Service. To finish and in the third place, develop biomedical research, which is carried out through the Research and Innovation Program of Catalonia
Networks in the early stage risk capital market.
Despite the wide interest in the role of social capital theory in entrepreneurship, there is scarce literature which uses this theoretical framework to study venture capital finance. Indeed, this literature, aiming at describing the investor’s due diligence process, has used methodologies and theoretical framework which most of the times have not considered the sociological aspect. Therefore, the purpose of this study is to investigate how entrepreneurial network theory could be used in the field of entrepreneurial finance. To achieve this, this thesis is made up of three papers which investigate different research questions regarding venture capital finance literature by drawing on sociological theory and entrepreneurial network theory and by using statistical model (Exponential Random Graph Model) and software (R and UCINET). By using this integrated approach, this study explains the importance of network in the early stage equity market both for investors to reduce the uncertainty of the investment, and for the entrepreneurs to increase new venture’s chance to get resources and to survive. This thesis provides a meaningful pathway for future research and insights to practitioners
Measurement of inclusive muon elliptic flow in pp collision at √s=13 TeV with the ALICE Experiment
Heavy-flavour hadrons are produced in hard-scattering processes in hadron collisions before the Quark–Gluon Plasma (QGP) formation. They successively interact with the QGP via inelastic and elastic processes. The elliptic flow v2 is one of the signatures of QGP formation. The ALICE experiment has measured its value in various heavy flavour decay channels in Pb–Pb and p–Pb collisions. Indications of non-zero v2 in pp collisions have been shown by different experiments.
Within this work, the inclusive muon elliptic flow (v^μ_2 ) in the forward rapidity has been measured using ALICE RUN 2 pp at √s = 13 TeV collision data. The elliptic flow has been measured in the 0-5%, 0-10%, 0-15% and 0-20% multiplicity bins using the two-particle correlation method. Intermediate and high transverse momentum (pμT) muons mainly originates from heavy-flavour decays. A non-zero vμ2 has been observed in all the studied multiplicity classes up to a muon pμT = 3 GeV/c with a significance above 5σ. The 3 < pμT < 4 has shown an above 5σ non-zero vμ2 in the 0-5% multiplicity class, while an above 3σ non-zero flow in the other multiplicity classes
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