1,880 research outputs found
Bayesian Inference of the Multi-Period Optimal Portfolio for an Exponential Utility
We consider the estimation of the multi-period optimal portfolio obtained by
maximizing an exponential utility. Employing Jeffreys' non-informative prior
and the conjugate informative prior, we derive stochastic representations for
the optimal portfolio weights at each time point of portfolio reallocation.
This provides a direct access not only to the posterior distribution of the
portfolio weights but also to their point estimates together with uncertainties
and their asymptotic distributions. Furthermore, we present the posterior
predictive distribution for the investor's wealth at each time point of the
investment period in terms of a stochastic representation for the future wealth
realization. This in turn makes it possible to use quantile-based risk measures
or to calculate the probability of default. We apply the suggested Bayesian
approach to assess the uncertainty in the multi-period optimal portfolio by
considering assets from the FTSE 100 in the weeks after the British referendum
to leave the European Union. The behaviour of the novel portfolio estimation
method in a precarious market situation is illustrated by calculating the
predictive wealth, the risk associated with the holding portfolio, and the
default probability in each period.Comment: 38 pages, 5 figure
Analyzing Input and Output Representations for Speech-Driven Gesture Generation
This paper presents a novel framework for automatic speech-driven gesture
generation, applicable to human-agent interaction including both virtual agents
and robots. Specifically, we extend recent deep-learning-based, data-driven
methods for speech-driven gesture generation by incorporating representation
learning. Our model takes speech as input and produces gestures as output, in
the form of a sequence of 3D coordinates. Our approach consists of two steps.
First, we learn a lower-dimensional representation of human motion using a
denoising autoencoder neural network, consisting of a motion encoder MotionE
and a motion decoder MotionD. The learned representation preserves the most
important aspects of the human pose variation while removing less relevant
variation. Second, we train a novel encoder network SpeechE to map from speech
to a corresponding motion representation with reduced dimensionality. At test
time, the speech encoder and the motion decoder networks are combined: SpeechE
predicts motion representations based on a given speech signal and MotionD then
decodes these representations to produce motion sequences. We evaluate
different representation sizes in order to find the most effective
dimensionality for the representation. We also evaluate the effects of using
different speech features as input to the model. We find that mel-frequency
cepstral coefficients (MFCCs), alone or combined with prosodic features,
perform the best. The results of a subsequent user study confirm the benefits
of the representation learning.Comment: Accepted at IVA '19. Shorter version published at AAMAS '19. The code
is available at
https://github.com/GestureGeneration/Speech_driven_gesture_generation_with_autoencode
A non-standard analysis of a cultural icon: The case of Paul Halmos
We examine Paul Halmos' comments on category theory, Dedekind cuts, devil
worship, logic, and Robinson's infinitesimals. Halmos' scepticism about
category theory derives from his philosophical position of naive set-theoretic
realism. In the words of an MAA biography, Halmos thought that mathematics is
"certainty" and "architecture" yet 20th century logic teaches us is that
mathematics is full of uncertainty or more precisely incompleteness. If the
term architecture meant to imply that mathematics is one great solid castle,
then modern logic tends to teach us the opposite lession, namely that the
castle is floating in midair. Halmos' realism tends to color his judgment of
purely scientific aspects of logic and the way it is practiced and applied. He
often expressed distaste for nonstandard models, and made a sustained effort to
eliminate first-order logic, the logicians' concept of interpretation, and the
syntactic vs semantic distinction. He felt that these were vague, and sought to
replace them all by his polyadic algebra. Halmos claimed that Robinson's
framework is "unnecessary" but Henson and Keisler argue that Robinson's
framework allows one to dig deeper into set-theoretic resources than is common
in Archimedean mathematics. This can potentially prove theorems not accessible
by standard methods, undermining Halmos' criticisms.
Keywords: Archimedean axiom; bridge between discrete and continuous
mathematics; hyperreals; incomparable quantities; indispensability; infinity;
mathematical realism; Robinson.Comment: 15 pages, to appear in Logica Universali
Throwing the dice for the diagnosis of vaginal complaints?
BACKROUND: Vaginitis is among the most common conditions women are seeking medical care for. Although these infections can easily be treated, the relapse rate is high. This may be due to inadequate use of the diagnostic potential. METHODS: We evaluated the misjudgement rate of the aetiology of vaginal complaints. A total of 220 vaginal samples from women with a vaginal complaint were obtained and analysed for numbers of total lactobacilli, H(2)O(2)-producing lactobacilli, total aerobic cell counts and total anaerobic cell counts including bifidobacteria, Bacteroides spp., Prevotella spp. Additionally, the presence of Atopobium vaginae, Gardnerella vaginalis, Candida spp. and Trichomonas vaginalis was evaluated by DNA-hybridisation using the PCR and Affirm VPIII Microbial Identification Test, respectively. RESULTS: The participating physicians diagnosed Bacterial vaginosis (BV) as origin of discomfort in 80 cases, candidiasis in 109 cases and mixed infections in 8 cases. However, a present BV, defined as lack of H(2)O(2)-lactobacilli, presence of marker organisms, such as G. vaginalis, Bacteroides spp. or Atopobium vaginae, and an elevated pH were identified in only 45 cases of the women examined. Candida spp. were detected in 46 cases. Interestingly, an elevated pH corresponded solely to the presence of Atopobium vaginae, which was detected in 11 cases. CONCLUSION: Errors in the diagnosis of BV and candida vulvovaginitis (CV) were high. Interestingly, the cases of misjudgement of CV (77%) were more numerous than that of BV (61%). The use of Amsel criteria or microscopy did not reduce the number of misinterpretations. The study reveals that the misdiagnosis of vaginal complaints is rather high
Cauchy, infinitesimals and ghosts of departed quantifiers
Procedures relying on infinitesimals in Leibniz, Euler and Cauchy have been
interpreted in both a Weierstrassian and Robinson's frameworks. The latter
provides closer proxies for the procedures of the classical masters. Thus,
Leibniz's distinction between assignable and inassignable numbers finds a proxy
in the distinction between standard and nonstandard numbers in Robinson's
framework, while Leibniz's law of homogeneity with the implied notion of
equality up to negligible terms finds a mathematical formalisation in terms of
standard part. It is hard to provide parallel formalisations in a
Weierstrassian framework but scholars since Ishiguro have engaged in a quest
for ghosts of departed quantifiers to provide a Weierstrassian account for
Leibniz's infinitesimals. Euler similarly had notions of equality up to
negligible terms, of which he distinguished two types: geometric and
arithmetic. Euler routinely used product decompositions into a specific
infinite number of factors, and used the binomial formula with an infinite
exponent. Such procedures have immediate hyperfinite analogues in Robinson's
framework, while in a Weierstrassian framework they can only be reinterpreted
by means of paraphrases departing significantly from Euler's own presentation.
Cauchy gives lucid definitions of continuity in terms of infinitesimals that
find ready formalisations in Robinson's framework but scholars working in a
Weierstrassian framework bend over backwards either to claim that Cauchy was
vague or to engage in a quest for ghosts of departed quantifiers in his work.
Cauchy's procedures in the context of his 1853 sum theorem (for series of
continuous functions) are more readily understood from the viewpoint of
Robinson's framework, where one can exploit tools such as the pointwise
definition of the concept of uniform convergence.
Keywords: historiography; infinitesimal; Latin model; butterfly modelComment: 45 pages, published in Mat. Stu
Can we trust online crowdworkers? Comparing online and offline participants in a preference test of virtual agents
Conducting user studies is a crucial component in many scientific fields.
While some studies require participants to be physically present, other studies
can be conducted both physically (e.g. in-lab) and online (e.g. via
crowdsourcing). Inviting participants to the lab can be a time-consuming and
logistically difficult endeavor, not to mention that sometimes research groups
might not be able to run in-lab experiments, because of, for example, a
pandemic. Crowdsourcing platforms such as Amazon Mechanical Turk (AMT) or
Prolific can therefore be a suitable alternative to run certain experiments,
such as evaluating virtual agents. Although previous studies investigated the
use of crowdsourcing platforms for running experiments, there is still
uncertainty as to whether the results are reliable for perceptual studies. Here
we replicate a previous experiment where participants evaluated a gesture
generation model for virtual agents. The experiment is conducted across three
participant pools -- in-lab, Prolific, and AMT -- having similar demographics
across the in-lab participants and the Prolific platform. Our results show no
difference between the three participant pools in regards to their evaluations
of the gesture generation models and their reliability scores. The results
indicate that online platforms can successfully be used for perceptual
evaluations of this kind.Comment: Accepted to IVA 2020. Patrik Jonell and Taras Kucherenko contributed
equally to this wor
Evolution of Heterogeneous Cellular Automata in Fluctuating Environments
The importance of environmental fluctuations in the evolution of living organisms by natural selection has been widely
noted by biologists and linked to many important characteristics of life such as modularity, plasticity, genotype size, mutation rate, learning, or epigenetic adaptations. In artificial-life simulations, however, environmental fluctuations are usually seen as a nuisance rather than an essential characteristic of evolution. HetCA is a heterogeneous cellular automata characterized by its ability to generate open-ended long-term evolution and “evolutionary progress”. In this paper, we propose to measure the impact of different types of environmental fluctuations in HetCA. Our results indicate that environmental changes induce mechanisms analogous to epigenetic adaptation or multilevel selection. This is particularly prevalent in two of the tested fluctuation schemes, which involve a round-robin inhibition of certain cell types, where phenotypic selection seems to occur.Funding for this work was provided by the Science Foundation Ireland and the ERC Advanced Grant EPNet #340828.
Some of the simulations were run on the MareNostrum supercomputer of the Barcelona Supercomputing Center.Postprint (author's final draft
Embryomorphic Engineering: Emergent innovation through evolutionary development
Embryomorphic Engineering, a particular instance of Morpho-genetic Engineering, takes its inspiration directly from biological development
to create new hardware, software or network architectures by decentralized self-assembly of elementary agents. At its core, it combines three key principles of multicellular embryogenesis: chemical gradient di usion (providing
positional information to the agents), gene regulatory networks (triggering their diferentiation into types, thus patterning), and cell division (creating
structural constraints, thus reshaping). This chapter illustrates the potential
of Embryomorphic Engineering in di erent spaces: 2D/3D physical swarms,
which can nd applications in collective robotics, synthetic biology or nan-
otechnology; and nD graph topologies, which can nd applications in dis-
tributed software and peer-to-peer techno-social networks. In all cases, the
speci c genotype shared by all the agents makes the phenotype's complex
architecture and function modular, programmable and reproducible
Where attention goes, energy flows : enhancing individual sustainability in software engineering
Software engineers are plagued by the same troubles as many others in highly skilled jobs and digitized environments: Ever-expanding to-do lists, time to market pressure from management, deadline- driven development, continuous interruption during working tasks, and the juggle of balancing that with other areas of life (physical, mental and emotional health, family, household, finance, friends, hobbies and community service). These demands of life in combina- tion with a seemingly ever-increasing pace wear or burn out many people in the long run. Specifically, as software engineers, this also leads to decreased creativity and less efficiency in problem-solving. Generally offered solutions are reducing screen time and spending more time outdoors, both of which are hard to do within the work of a software engineer. On a meta level, if the developers of the systems that run most of our world do not develop individual sus- tainability with a balanced pace of life, that imbalance propagates into the systems we develop (similar to Conway’s Law). We argue that mindfulness practices like yoga poses (asanas), breathing prac- tices, and meditation exercises can help individually, and even more effectively in combination. In this exploratory paper, we discuss related work that explores the application of these mitigations in other application domains and propose a research agenda to explore their use within software engineering education and practice.Engaging with mindfulness practices in the context of software engineering promises to enhance creativity and cognitive problem- solving skills, leading to more efficiency and effectiveness during software development and increased individual sustainability. This, in turn, leads to better team spirit as well as increased economic profit, both in terms of maintaining human capital and customer contract deliverables
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