pwc-archive/papers-with-abstracts huggingface dataset:
A Framework for Iterative Frequency Domain EP-based Receiver Design
Date: 2018-06-30 00:00:00
Tasks: Decoder

An original expectation propagation (EP) based message passing framework is
introduced, wherein transmitted symbols are considered to belong to the
multivariate white Gaussian distribution family. This approach allows deriving
a novel class of single-tap frequency domain (FD) receivers with a quasi-linear
computational complexity in block length, thanks to Fast-Fourier transform
(FFT) based implementation. This framework is exposed in detail, through the
design of a novel double-loop single-carrier frequency domain equalizer
(SC-FDE), where self-iterations of the equalizer with the demapper, and turbo
iterations with the decoder, provide numerous combinations for the performance
and complexity trade-off. Furthermore, the flexibility of this framework is
illustrated with the derivation of an overlap FDE, used for time-varying
channel equalization, among others, and with the design of a FD multiple-input
multiple-output (MIMO) detector, used for spatial multiplexing. Through these
different receiver design problems, this framework is shown to improve the
mitigation of inter-symbol, inter-block and multi-antenna interferences,
compared to alternative single-tap FD structures of previous works. Thanks to
finite-length and asymptotic analysis, supported by numerical results, the
improvement brought by the proposed structures is assessed, and then completed
by also accounting for computational costs.
A Bayesian panel VAR model to analyze the impact of climate change on high-income economies
Authors: Florian Huber, Tamás Krisztin, Michael Pfarrhofer
Date: 2018-04-04 00:00:00

In this paper, we assess the impact of climate shocks on futures markets for agricultural commodities and a set of macroeconomic quantities for multiple high-income economies. To capture relations among countries, markets, and climate shocks, this paper proposes parsimonious methods to estimate high-dimensional panel VARs. We assume that coefficients associated with domestic lagged endogenous variables arise from a Gaussian mixture model while further parsimony is achieved using suitable global-local shrinkage priors on several regions of the parameter space. Our results point towards pronounced global reactions of key macroeconomic quantities to climate shocks. Moreover, the empirical findings highlight substantial linkages between regionally located climate shifts and global commodity markets.
A Mixed-Signal Structured AdEx Neuron for Accelerated Neuromorphic Cores
Date: 2018-05-29 00:00:00

Here we describe a multi-compartment neuron circuit based on the
Adaptive-Exponential I&F (AdEx) model, developed for the second-generation
BrainScaleS hardware. Based on an existing modular Leaky Integrate-and-Fire
(LIF) architecture designed in 65 nm CMOS, the circuit features exponential
spike generation, neuronal adaptation, inter-compartmental connections as well
as a conductance-based reset. The design reproduces a diverse set of firing
patterns observed in cortical pyramidal neurons. Further, it enables the
emulation of sodium and calcium spikes, as well as N-Methyl-D-Aspartate (NMDA)
plateau potentials known from apical and thin dendrites. We characterize the
AdEx circuit extensions and exemplify how the interplay between passive and
non-linear active signal processing enhances the computational capabilities of
single (but structured) on-chip neurons.
An Accelerated LIF Neuronal Network Array for a Large Scale Mixed-Signal Neuromorphic Architecture
Date: 2018-05-23 00:00:00

We present an array of leaky integrate-and-fire (LIF) neuron circuits
designed for the second-generation BrainScaleS mixed-signal 65-nm CMOS
neuromorphic hardware. The neuronal array is embedded in the analog network
core of a scaled-down prototype HICANN-DLS chip. Designed as continuous-time
circuits, the neurons are highly tunable and reconfigurable elements with
accelerated dynamics. Each neuron integrates input current from a multitude of
incoming synapses and evokes a digital spike event output. The circuit offers a
wide tuning range for synaptic and membrane time constants, as well as for
refractory periods to cover a number of computational models. We elucidate our
design methodology, underlying circuit design, calibration and measurement
results from individual sub-circuits across multiple dies. The circuit dynamics
match with the behavior of the LIF mathematical model. We further demonstrate a
winner-take-all network on the prototype chip as a typical element of cortical
processing.
Iterative Equalization with Decision Feedback based on Expectation Propagation
Date: 2018-06-30 00:00:00

This paper investigates the design and analysis of minimum mean square error
(MMSE) turbo decision feedback equalization (DFE), with expectation propagation
(EP), for single carrier modulations. Classical non iterative DFE structures
have substantial advantages at high data rates, even compared to turbo linear
equalizers - interference cancellers (LE-IC), hence making turbo DFE-IC schemes
an attractive solution. In this paper, we derive an iterative DFE-IC,
capitalizing on the use of soft feedback based on expectation propagation,
along with the use of prior information for improved filtering and interference
cancellation. This DFE-IC significantly outperforms exact turbo LE-IC,
especially at high spectral efficiency, and also exhibits various advantages
and performance improvements over existing variants of DFE-IC. The proposed
scheme can also be self-iterated, as done in the recent trend on EP-based
equalizers, and it is shown to be an attractive alternative to linear
self-iterated receivers. For time-varying (TV) filter equalizers, an efficient
matrix inversion scheme is also proposed, considerably reducing the
computational complexity relative to existing methods. Using finite-length and
asymptotic analysis on a severely selective channel, the proposed DFE-IC is
shown to achieve higher rates than known alternatives, with better waterfall
thresholds and faster convergence, while keeping a similar computational
complexity.
A Wikipedia-based approach to profiling activities on social media
Authors: Torrero Christian, Caprini Carlo, Miorandi Daniele
Date: 2018-09-26 00:00:00

Online user profiling is a very active research field, catalyzing great
interest by both scientists and practitioners. In this paper, in particular, we
look at approaches able to mine social media activities of users to create a
rich user profile. We look at the case in which the profiling is meant to
characterize the user's interests along a set of predefined dimensions (that we
refer to as categories). A conventional way to do so is to use semantic
analysis techniques to (i) extract relevant entities from the online
conversations of users (ii) mapping said entities to the predefined categories
of interest. While entity extraction is a well-understood topic, the mapping
part lacks a reference standardized approach. In this paper we propose using
graph navigation techniques on the Wikipedia tree to achieve such a mapping. A
prototypical implementation is presented and some preliminary results are
reported.
Corruption-free scheme of entering into contract: mathematical model
Date: 2018-04-24 00:00:00

The main purpose of this paper is to formalize the modelling process,
analysis and mathematical definition of corruption when entering into a
contract between principal agent and producers. The formulation of the problem
and the definition of concepts for the general case are considered. For
definiteness, all calculations and formulas are given for the case of three
producers, one principal agent and one intermediary. Economic analysis of
corruption allowed building a mathematical model of interaction between agents.
Financial resources distribution problem in a contract with a corrupted
intermediary is considered.Then proposed conditions for corruption emergence
and its possible consequences. Optimal non-corruption schemes of financial
resources distribution in a contract are formed, when principal agent's choice
is limited first only by asymmetrical information and then also by external
influences.Numerical examples suggesting optimal corruption-free agents'
behaviour are presented.
Water Bridging Dynamics of Polymerase Chain Reaction in the Gauge Theory Paradigm of Quantum Fields
Authors: Luc Montagnier, Jamal Aïssa, Antonio Capolupo, Travis J. A. Craddock, Philip Kurian, Claude Lavallee, Albino Polcari, Paola Romano, Alberto Tedeschi, Giuseppe Vitiello
Date: 2018-03-29 00:00:00

We discuss the role of water bridging the DNA-enzyme interaction by resorting to recent results showing that London dispersion forces between delocalized electrons of base pairs of DNA are responsible for the formation of dipole modes that can be recognized by \textit{Taq} polymerase. We describe the dynamic origin of the high efficiency and precise targeting of \textit{Taq} activity in PCR. The spatiotemporal distribution of interaction couplings, frequencies, amplitudes, and phase modulations comprise a pattern of fields which constitutes the electromagnetic image of DNA in the surrounding water, which is what the polymerase enzyme actually recognizes in the DNA water environment. The experimental realization of PCR amplification, achieved through replacement of the DNA template by the treatment of pure water with electromagnetic signals recorded from viral and bacterial DNA solutions, is found consistent with the gauge theory paradigm of quantum fields.
The impact of electrical couplings on the sequential bursting activity in the ensemble of inhibitory coupled Van der Pol elements
Date: 2018-03-29 00:00:00

The new phenomenological model of the ensemble of three neurons with chemical
(synaptic) and electrical couplings has been studied. One neuron is modeled by
a single Van der Pol oscillator. The influence of the electrical coupling
strength and the frequency mismatch between the elements to the regime of
sequential activity is investigated.
Affinity-based extension of non-extensive entropy and statistical mechanics
Authors: Keisuke Okamura
Date: 2018-03-29 00:00:00
Tasks: Diversity

Tsallis' non-extensive entropy is extended to incorporate the dependence on affinities between the microstates of a system. At the core of our construction of the extended entropy ($\mathcal{H}$) is the concept of the effective number of dissimilar states, termed the effective diversity ($\mathit{\Delta}$). It is a unique integrated measure derived from the probability distribution among states and the affinities between states. The effective diversity is related to the extended entropy through the Boltzmann's-equation-like relation, $\mathcal{H}=\ln_{q}\mathit{\Delta}$, in terms of the Tsallis' $q$-logarithm. A new principle called the Nesting Principle is established, stating that the effective diversity remains invariant under an arbitrary grouping of the constituent states. It is shown that this invariance property holds only for $q=2$; however, the invariance is recovered for general $q$ in the zero-affinity limit (i.e. the Tsallis and Boltzmann-Gibbs case). Using the affinity-based extended Tsallis entropy, the microcanonical and the canonical ensembles are constructed in the presence of general between-state affinities. It is shown that the classic postulate of equal a priori probabilities no longer holds but is modified by affinity-dependent terms. As an illustration, a two-level system is investigated by the extended canonical method, which manifests that the thermal behaviours of the thermodynamic quantities at equilibrium are affected by the between-state affinity. Furthermore, some applications and implications of the affinity-based extended diversity/entropy for information theory and biodiversity theory are addressed in appendices.
A primary insight into the molecular phylogeny of Colias FABRICIUS, 1807 (Pieridae, Coliadinae) complex of South America
Date: 2018-04-14 00:00:00

The data on molecular phylogeny of the Colias complex of South America (SA),
obtained via barcoding a mitochondrial part of genome, are reported. Barcoding
was trialed employing the Barcoding of Life Database platform and comprised 93
specimens of SA Colias sp. plus 2 outgroup specimens (C. philodice guatemalena
from North America). It is established that Colias sp. from SA form a single
monophyletic clade, characterized by notable interspecific mutational
divergences (3.5-4.5%) and moderate intraspecific ones (0.3-0.9%). It also
reveals the occurrence of 3 well-established (notably diverged genetically)
species (C. dimera, C. vauthierii, and C. alticola, the latter re-raised to sp.
level), plus a complex of 3 'emerging' species (C. lesbia, C. euxanthe, and C.
flaveola) which are weakly differentiated genetically. Furthermore, it
disregards the sp. status of taxa weberbaueri, mossi, nigerrima, erika,
blameyi, and mendozina, as certain evidences are being brought to consider them
ssp. of a clinal type of super-sp. C. flaveola s. lat. Importantly, the clade
formed by SA Colias is found to be sister to the one comprising Colias sp.
occurring outside the region (in Eurasia, North America, and Africa). A direct
comparison of the results obtained for SA Colias with those for worldwide
Colias (GenBank data) leads to the conclusion that these are largely divergent
autochtonous subcomplexes, being in fact subgenera s. lat. of genus Colias. The
first subgenus comprising all SA Colias sp. and named Aucolias (Austral Colias,
or of southern hemisphere stem) is sister to the second one (comprising all
Colias sp. from the Old and New Worlds), for which the name Colias (Colias) s.
str. is preserved.
A Directed Graph Fourier Transform with Spread Frequency Components
Date: 2018-09-23 00:00:00
Tasks: Denoising

We study the problem of constructing a graph Fourier transform (GFT) for
directed graphs (digraphs), which decomposes graph signals into different modes
of variation with respect to the underlying network. Accordingly, to capture
low, medium and high frequencies we seek a digraph (D)GFT such that the
orthonormal frequency components are as spread as possible in the graph
spectral domain. To that end, we advocate a two-step design whereby we: (i)
find the maximum directed variation (i.e., a novel notion of frequency on a
digraph) a candidate basis vector can attain; and (ii) minimize a smooth
spectral dispersion function over the achievable frequency range to obtain the
desired spread DGFT basis. Both steps involve non-convex,
orthonormality-constrained optimization problems, which are efficiently tackled
via a provably convergent, feasible optimization method on the Stiefel
manifold. We also propose a heuristic to construct the DGFT basis from
Laplacian eigen-vectors of an undirected version of the digraph. We show that
the spectral-dispersion minimization problem can be cast as supermodular
optimization over the set of candidate frequency components, whose
orthonormality can be enforced via a matroid basis constraint. This motivates
adopting a scalable greedy algorithm to obtain an approximate solution with
quantifiable worst-case spectral dispersion. We illustrate the effectiveness of
our DGFT algorithms through numerical tests on synthetic and real-world
networks. We also carry out a graph-signal denoising task, whereby the DGFT
basis is used to decompose and then low-pass filter temperatures recorded
across the United States.
Portfolio Optimization under Fast Mean-reverting and Rough Fractional Stochastic Environment
Date: 2019-01-24 00:00:00
Tasks: Portfolio Optimization, Time Series, Time Series Analysis

Fractional stochastic volatility models have been widely used to capture the
non-Markovian structure revealed from financial time series of realized
volatility. On the other hand, empirical studies have identified scales in
stock price volatility: both fast-time scale on the order of days and
slow-scale on the order of months. So, it is natural to study the portfolio
optimization problem under the effects of dependence behavior which we will
model by fractional Brownian motions with Hurst index $H$, and in the fast or
slow regimes characterized by small parameters $\eps$ or $\delta$. For the
slowly varying volatility with $H \in (0,1)$, it was shown that the first order
correction to the problem value contains two terms of order $\delta^H$, one
random component and one deterministic function of state processes, while for
the fast varying case with $H > \half$, the same form holds at order
$\eps^{1-H}$. This paper is dedicated to the remaining case of a fast-varying
rough environment ($H < \half$) which exhibits a different behavior. We show
that, in the expansion, only one deterministic term of order $\sqrt{\eps}$
appears in the first order correction.
Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge at the 2017 INFORMS RM & Pricing Conference
Date: 2018-03-20 00:00:00
Tasks: Management

This paper presents the results of the Dynamic Pricing Challenge, held on the
occasion of the 17th INFORMS Revenue Management and Pricing Section Conference
on June 29-30, 2017 in Amsterdam, The Netherlands. For this challenge,
participants submitted algorithms for pricing and demand learning of which the
numerical performance was analyzed in simulated market environments. This
allows consideration of market dynamics that are not analytically tractable or
can not be empirically analyzed due to practical complications. Our findings
implicate that the relative performance of algorithms varies substantially
across different market dynamics, which confirms the intrinsic complexity of
pricing and learning in the presence of competition.
A derivation of the Black-Scholes option pricing model using a central limit theorem argument
Date: 2018-08-13 00:00:00

The Black-Scholes model (sometimes known as the Black-Scholes-Merton model)
gives a theoretical estimate for the price of European options. The price
evolution under this model is described by the Black-Scholes formula, one of
the most well-known formulas in mathematical finance. For their discovery,
Merton and Scholes have been awarded the 1997 Nobel prize in Economics. The
standard method of deriving the Black-Scholes European call option pricing
formula involves stochastic differential equations. This approach is out of
reach for most students learning the model for the first time. We provide an
alternate derivation using the Lindeberg-Feller central limit theorem under
suitable assumptions. Our approach is elementary and can be understood by
undergraduates taking a standard undergraduate course in probability.
Efficient illumination angle self-calibration in Fourier ptychography
Date: 2018-04-10 00:00:00
Tasks: General Knowledge

Fourier ptychography captures intensity images with varying source patterns
(illumination angles) in order to computationally reconstruct large
space-bandwidth-product images. Accurate knowledge of the illumination angles
is necessary for good image quality; hence, calibration methods are crucial,
despite often being impractical or slow. Here, we propose a fast, robust, and
accurate self-calibration algorithm that uses only experimentally-collected
data and general knowledge of the illumination setup. First, our algorithm
makes a direct estimate of the brightfield illumination angles based on image
processing. Then, a more computationally-intensive spectral correlation method
is used inside the iterative solver to further refine the angle estimates of
both brightfield and darkfield images. We demonstrate our method for correcting
large and small misalignment artifacts in both 2D and 3D Fourier ptychography
with different source types: an LED array, a galvo-steered laser, and a high-NA
quasi-dome LED illuminator.
Thermodynamics and evolutionary biology through optimal control
Date: 2018-04-10 00:00:00

We consider a particular instance of the lift of controlled systems recently
proposed in the theory of irreversible thermodynamics and show that it leads to
a variational principle for an optimal control in the sense of Pontryagin. Then
we focus on two important applications: in thermodynamics and in evolutionary
biology. In the thermodynamic context, we show that this principle provides a
dynamical implementation of the Second Law, which stabilizes the equilibrium
manifold of a system. In the evolutionary context, we discuss several
interesting features: it provides a robust scheme for the coevolution of the
population and its fitness landscape; it has a clear informational
interpretation; it recovers Price equation naturally; and finally, it extends
standard evolutionary dynamics to include phenomena such as the emergence of
cooperation and the coexistence of qualitatively different phases of evolution,
which we speculate can be associated with Darwinism and punctuated equilibria.
Inference on Local Average Treatment Effects for Misclassified Treatment
Date: 2018-04-10 00:00:00
Tasks: valid

We develop point-identification for the local average treatment effect when
the binary treatment contains a measurement error. The standard instrumental
variable estimator is inconsistent for the parameter since the measurement
error is non-classical by construction. We correct the problem by identifying
the distribution of the measurement error based on the use of an exogenous
variable that can even be a binary covariate. The moment conditions derived
from the identification lead to generalized method of moments estimation with
asymptotically valid inferences. Monte Carlo simulations and an empirical
illustration demonstrate the usefulness of the proposed procedure.
Evaluating the role of data quality when sharing information in hierarchical multi-stock assessment models, with an application to Dover Sole
Date: 2018-10-20 00:00:00
Tasks: Management, Survey

An emerging approach to data-limited fisheries stock assessment uses
hierarchical multi-stock assessment models to group stocks together, sharing
information from data-rich to data-poor stocks. In this paper, we simulate
data-rich and data-poor fishery and survey data scenarios for a complex of
dover sole stocks. Simulated data for individual stocks were used to compare
estimation performance for single-stock and hierarchical multi-stock versions
of a Schaefer production model. The single-stock and best performing
multi-stock models were then used in stock assessments for the real dover sole
data. Multi-stock models often had lower estimation errors than single-stock
models when assessment data had low statistical power. Relative errors for
productivity and relative biomass parameters were lower for multi-stock
assessment model configurations. In addition, multi-stock models that estimated
hierarchical priors for survey catchability performed the best under data-poor
scenarios. We conclude that hierarchical multi-stock assessment models are
useful for data-limited stocks and could provide a more flexible alternative to
data-pooling and catch only methods; however, these models are subject to
non-linear side-effects of parameter shrinkage. Therefore, we recommend testing
hierarchical multi-stock models in closed-loop simulations before application
to real fishery management systems.
X-ray ghost tomography: denoising, dose fractionation and mask considerations
Date: 2018-04-10 00:00:00
Tasks: Denoising

Ghost imaging has recently been successfully achieved in the X-ray regime;
due to the penetrating power of X-rays this immediately opens up the
possibility of X-ray ghost tomography. No research into this topic currently
exists in the literature. Here we present adaptations of conventional
tomography techniques to this new ghost imaging scheme. Several numerical
implementations for tomography through X-ray ghost imaging are considered.
Specific attention is paid to schemes for denoising of the resulting
tomographic reconstruction, issues related to dose fractionation, and
considerations regarding the ensemble of illuminating masks used for ghost
imaging. Each theme is explored through a series of numerical simulations, and
several suggestions offered for practical realisations of X-ray ghost
tomography.