pwc-archive/papers-with-abstracts huggingface dataset:
Exploring Query Categorisation for Query Expansion: A Study
Authors: Pal Dipasree, Mitra Mandar, Bhattacharya Samar
Date: 2015-09-18 00:00:00
Tasks: Information Retrieval, Retrieval

The vocabulary mismatch problem is one of the important challenges facing
traditional keyword-based Information Retrieval Systems. The aim of query
expansion (QE) is to reduce this query-document mismatch by adding related or
synonymous words or phrases to the query.
  Several existing query expansion algorithms have proved their merit, but they
are not uniformly beneficial for all kinds of queries. Our long-term goal is to
formulate methods for applying QE techniques tailored to individual queries,
rather than applying the same general QE method to all queries. As an initial
step, we have proposed a taxonomy of query classes (from a QE perspective) in
this report. We have discussed the properties of each query class with
examples. We have also discussed some QE strategies that might be effective for
each query category.
  In future work, we intend to test the proposed techniques using standard
datasets, and to explore automatic query categorisation methods.
Stochastic Optimal Growth Model with Risk Sensitive Preferences
Date: 2015-09-18 00:00:00
Tasks: model

This paper studies a one-sector optimal growth model with i.i.d. productivity
shocks that are allowed to be unbounded. The utility function is assumed to be
non-negative and unbounded from above. The novel feature in our framework is
that the agent has risk sensitive preferences in the sense of Hansen and
Sargent (1995). Under mild assumptions imposed on the productivity and utility
functions we prove that the maximal discounted non-expected utility in the
infinite time horizon satisfies the optimality equation and the agent possesses
a stationary optimal policy. A new point used in our analysis is an inequality
for the so-called associated random variables. We also establish the Euler
equation that incorporates the solution to the optimality equation.
User-Curated Image Collections: Modeling and Recommendation
Authors: Li Yuncheng, Cong Yang, Mei Tao, Luo Jiebo
Date: 2015-09-18 00:00:00
Tasks: Image Retrieval, Recommendation Systems, Retrieval

Most state-of-the-art image retrieval and recommendation systems
predominantly focus on individual images. In contrast, socially curated image
collections, condensing distinctive yet coherent images into one set, are
largely overlooked by the research communities. In this paper, we aim to design
a novel recommendation system that can provide users with image collections
relevant to individual personal preferences and interests. To this end, two key
issues need to be addressed, i.e., image collection modeling and similarity
measurement. For image collection modeling, we consider each image collection
as a whole in a group sparse reconstruction framework and extract concise
collection descriptors given the pretrained dictionaries. We then consider
image collection recommendation as a dynamic similarity measurement problem in
response to user's clicked image set, and employ a metric learner to measure
the similarity between the image collection and the clicked image set. As there
is no previous work directly comparable to this study, we implement several
competitive baselines and related methods for comparison. The evaluations on a
large scale Pinterest data set have validated the effectiveness of our proposed
methods for modeling and recommending image collections.
How to Direct the Edges of the Connectomes: Dynamics of the Consensus Connectomes and the Development of the Connections in the Human Brain
Date: 2016-03-13 00:00:00
Tasks: Diffusion  MRI

The human connectome is the object of an intensive research today. In these
graphs, the vertices correspond to the small areas of the gray matter, and two
vertices are connected by an edge, if a diffusion-MRI based workflow finds
connections between those areas. One main question of the field is discovering
the directions of the edges. In a previous work we have reported the
construction of the Budapest Reference Connectome Server
http://connectome.pitgroup.org from the data recorded in the Human Connectome
Project of the NIH. After the server had been published, we recognized a
surprising and unforeseen property of it: The server can generate the
braingraph of connections that are present in at least $k$ graphs out of the
418, for any value of $k=1,2,...,418$. When the value of $k$ is changed from
$k=418$ through 1 by moving a slider at the webserver from right to left, more
and more edges appear in the consensus graph. The astonishing observation is
that the appearance of the new edges is not random: it is similar to a growing
tree. We hypothesize that this movement of the slider in the webserver may copy
the development of the connections in the human brain in the following sense:
the connections that are present in all subjects are the oldest ones, and those
that are present in a decreasing fraction of subjects are gradually the newer
connections in the individual brain development. An animation on the phenomenon
is available at https://youtu.be/EnWwIf_HNjw. Based on this hypothesis, we can
assign directions to the edges of the connectome as follows: Let $G_i$ denote
the consensus connectome where each edge is present in at least $i$ graphs.
Suppose that vertex $v$ is isolated in $G_{k+1}$, and becomes connected to a
vertex $u$ in $G_k$, where $u$ was connected to other vertices already in
$G_{k+1}$. Then we direct this $(v,u)$ edge from $v$ to $u$.
Assortment and the evolution of cooperation in a Moran process with exponential fitness
Date: 2016-04-13 00:00:00

We study the evolution of cooperation in a finite population interacting
according to a simple model of like-with-like assortment. Evolution proceeds as
a Moran process, and payoffs from the underlying cooperator-defector game are
translated to positive fitnesses by an exponential transformation. These
evolutionary dynamics can arise, for example, in a nest-structured population
with rare migration. The use of the exponential transformation, rather than the
usual linear one, is appropriate when interactions have multiplicative fitness
effects, and allows for a tractable characterization of the effect of
assortment on the evolution of cooperation. We define two senses in which a
greater degree of assortment can favour the evolution of cooperation, the first
stronger than the second: (i) greater assortment increases, at all population
states, the probability that the number of cooperators increases, relative to
the probability that the number of defectors increases; and (ii) greater
assortment increases the fixation probability of cooperation, relative to that
of defection. We show that, by the stronger definition, greater assortment
favours the evolution of cooperation for a subset of cooperative dilemmas:
prisoners' dilemmas, snowdrift games, stag-hunt games, and some prisoners'
delight games. For other cooperative dilemmas, greater assortment favours
cooperation by the weak definition, but not by the strong definition. Our
results hold for any strength of selection.
A new hybrid spectral similarity measure for discrimination of Vigna species
Date: 2015-09-18 00:00:00

The reflectance spectrum of the species in a hyperspectral data can be
modelled as an n-dimensional vector. The spectral angle mapper computes the
angle between the vectors which is used to discriminate the species. The
spectral information divergence models the data as a probability distribution
so that the spectral variability between the bands can be extracted using the
stochastic measures. The hybrid approach of spectral angle mapper and spectral
information divergence is found to be better discriminator than spectral angle
mapper or spectral information divergence alone. The spectral correlation angle
is computed as a cosine of the angle of the Pearsonian correlation coefficient
between the vectors. The spectral correlation angle is a better measure than
the spectral angle mapper as it considers only standardized values of the
vectors rather than the absolute values of the vector. In the present paper a
new hybrid measure is proposed which is based on the spectral correlation angle
and the spectral information divergence. The proposed method has been compared
with the hybrid approach of spectral information divergence and spectral angle
mapper for discrimination of crops belonging to Vigna species using measures
like relative spectral discriminatory power, relative discriminatory
probability and relative discriminatory entropy in different spectral regions.
Experimental results using the laboratory spectra show that the proposed method
gives higher relative discriminatory power in 400nm-700nm spectral region.
Lack of appropriate controls leads to mistaking absence seizures for post-traumatic epilepsy
Date: 2015-09-18 00:00:00
Tasks: Diagnostic

Here we provide a thorough discussion of a rebuttal by D'Ambrosio et al to a
study conducted by Rodgers et al. (Rodgers KM, Dudek FE, Barth DS (2015)
Progressive, Seizure-Like, Spike- Wave Discharges Are Common in Both Injured
and Uninjured Sprague-Dawley Rats: Implications for the Fluid Percussion Injury
Model of Post-Traumatic Epilepsy. J Neurosci. 35(24):9194-204. doi:
10.1523/JNEUROSCI.0919-15.2015.) to investigate focal seizures and acquired
epileptogenesis induced by head injury in the rat. This manuscript serves as
supplementary document for our letter to the Editor to appear in the Journal of
Neuroscience. We find the rebuttal is flawed on all points, particularly
concerning use of proper controls, experimental methods, analytical methods,
and epilepsy diagnostic criteria, leading to mistaking absence seizures for
post-traumatic epilepsy.
A note on the distribution of admixture segment lengths and ancestry proportions under pulse and two-wave admixture models
Date: 2015-09-19 00:00:00

Admixed populations are formed by the merging of two or more ancestral
populations, and the ancestry of each locus in an admixed genome derives from
either source. Consider a simple "pulse" admixture model, where populations A
and B merged t generations ago without subsequent gene flow. We derive the
distribution of the proportion of an admixed chromosome that has A (or B)
ancestry, as a function of the chromosome length L, t, and the initial
contribution of the A source, m. We demonstrate that these results can be used
for inference of the admixture parameters. For more complex admixture models,
we derive an expression in Laplace space for the distribution of ancestry
proportions that depends on having the distribution of the lengths of segments
of each ancestry. We obtain explicit results for the special case of a
"two-wave" admixture model, where population A contributed additional migrants
in one of the generations between the present and the initial admixture event.
Specifically, we derive formulas for the distribution of A and B segment
lengths and numerical results for the distribution of ancestry proportions. We
show that for recent admixture, data generated under a two-wave model can
hardly be distinguished from that generated under a pulse model.
Managing Cellular Billing Plan Switchings
Date: 2015-09-19 00:00:00

Here we shall consider a very popular practical applied problem of managing
mode switching (in this work we are considering managing billing plans). Out of
the two parties (service provider and service consumer), participating in the
processes modelled here, we shall consider only a consumer type of a problem.
Herein we provide formal characterization of the problem as well as the
elements necessary for its solution. We shall consider full predicted costs,
originating when switching to a billing plan as a target index. The work
contains an example that provides a detailed view of the application technology
referring to the suggested problem solution algorithm. Using the example's data
we have performed the analysis measuring the problem's sensitivity in relation
to the growth of the traffic volume. Herein we provided a polynomial
approximation of the target index value depending on the traffic volume.
Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application
Date: 2015-09-20 00:00:00
Tasks: Time Series, Time Series Analysis

Many complex systems generate multifractal time series which are long-range
cross-correlated. Numerous methods have been proposed to characterize the
multifractal nature of these long-range cross correlations. However, several
important issues about these methods are not well understood and most methods
consider only one moment order. We study the joint multifractal analysis based
on partition function with two moment orders, which was initially invented to
investigate fluid fields, and derive analytically several important properties.
We apply the method numerically to binomial measures with multifractal cross
correlations and bivariate fractional Brownian motions without multifractal
cross correlations. For binomial multifractal measures, the explicit
expressions of mass function, singularity strength and multifractal spectrum of
the cross correlations are derived, which agree excellently with the numerical
results. We also apply the method to stock market indexes and unveil intriguing
multifractality in the cross correlations of index volatilities.
Mean-Reverting Portfolios: Tradeoffs Between Sparsity and Volatility
Date: 2015-09-20 00:00:00

Mean-reverting assets are one of the holy grails of financial markets: if
such assets existed, they would provide trivially profitable investment
strategies for any investor able to trade them, thanks to the knowledge that
such assets oscillate predictably around their long term mean. The modus
operandi of cointegration-based trading strategies [Tsay, 2005, {\S}8] is to
create first a portfolio of assets whose aggregate value mean-reverts, to
exploit that knowledge by selling short or buying that portfolio when its value
deviates from its long-term mean. Such portfolios are typically selected using
tools from cointegration theory [Engle and Granger, 1987, Johansen, 1991],
whose aim is to detect combinations of assets that are stationary, and
therefore mean-reverting. We argue in this work that focusing on stationarity
only may not suffice to ensure profitability of cointegration-based strategies.
While it might be possible to create syn- thetically, using a large array of
financial assets, a portfolio whose aggre- gate value is stationary and
therefore mean-reverting, trading such a large portfolio incurs in practice
important trade or borrow costs. Looking for stationary portfolios formed by
many assets may also result in portfolios that have a very small volatility and
which require significant leverage to be profitable. We study in this work
algorithmic approaches that can take mitigate these effects by searching for
maximally mean-reverting portfo- lios which are sufficiently sparse and/or
volatile.
Scaling in topological properties of brain networks
Date: 2015-09-20 00:00:00

The organization in brain networks shows highly modular features with weak
inter-modular interaction. The topology of the networks involves emergence of
modules and sub-modules at different levels of constitution governed by fractal
laws. The modular organization, in terms of modular mass, inter-modular, and
intra-modular interaction, also obeys fractal nature. The parameters which
characterize topological properties of brain networks follow one parameter
scaling theory in all levels of network structure which reveals the
self-similar rules governing the network structure. The calculated fractal
dimensions of brain networks of different species are found to decrease when
one goes from lower to higher level species which implicates the more ordered
and self-organized topography at higher level species. The sparsely distributed
hubs in brain networks may be most influencing nodes but their absence may not
cause network breakdown, and centrality parameters characterizing them also
follow one parameter scaling law indicating self-similar roles of these hubs at
different levels of organization in brain networks.
Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting
Date: 2016-02-12 00:00:00

Phylogenetic networks are necessary to represent the tree of life expanded by
edges to represent events such as horizontal gene transfers, hybridizations or
gene flow. Not all species follow the paradigm of vertical inheritance of their
genetic material. While a great deal of research has flourished into the
inference of phylogenetic trees, statistical methods to infer phylogenetic
networks are still limited and under development. The main disadvantage of
existing methods is a lack of scalability. Here, we present a statistical
method to infer phylogenetic networks from multi-locus genetic data in a
pseudolikelihood framework. Our model accounts for incomplete lineage sorting
through the coalescent model, and for horizontal inheritance of genes through
reticulation nodes in the network. Computation of the pseudolikelihood is fast
and simple, and it avoids the burdensome calculation of the full likelihood
which can be intractable with many species. Moreover, estimation at the
quartet-level has the added computational benefit that it is easily
parallelizable. Simulation studies comparing our method to a full likelihood
approach show that our pseudolikelihood approach is much faster without
compromising accuracy. We applied our method to reconstruct the evolutionary
relationships among swordtails and platyfishes ($Xiphophorus$: Poeciliidae),
which is characterized by widespread hybridizations.
When can splits be drawn in the plane?
Date: 2015-09-21 00:00:00

Split networks are a popular tool for the analysis and visualization of
complex evolutionary histories. Every collection of splits (bipartitions) of a
finite set can be represented by a split network. Here we characterize which
collection of splits can be represented using a planar split network. Our main
theorem links these collections of splits with oriented matroids and
arrangements of lines separating points in the plane. As a consequence of our
main theorem, we establish a particularly simple characterization of maximal
collections of these splits.
A sequential approach to calibrate ecosystem models with multiple time series data
Date: 2015-09-21 00:00:00
Tasks: Decision Making, Management, parameter estimation, Time Series, Time Series Analysis

Ecosystem approach to fisheries requires a thorough understanding of fishing
impacts on ecosystem status and processes as well as predictive tools such as
ecosystem models to provide useful information for management. The credibility
of such models is essential when used as decision making tools, and model
fitting to observed data is one major criterion to assess such credibility.
However, more attention has been given to the exploration of model behavior
than to a rigorous confrontation to observations, as the calibration of
ecosystem models is challenging in many ways. First, ecosystem models can only
be simulated numerically and are generally too complex for mathematical
analysis and explicit parameter estimation; secondly, the complex dynamics
represented in ecosystem models allow species-specific parameters to impact
other species parameters through ecological interactions; thirdly, critical
data about non-commercial species are often poor; lastly, technical aspects can
be impediments to the calibration with regard to the high computational cost
potentially involved and the scarce documentation published on fitting complex
ecosystem models to data. This work highlights some issues related to the
confrontation of complex ecosystem models to data and proposes a methodology
for a sequential multi-phases calibration of ecosystem models. We propose
criteria to classify the parameters of a model: model dependency and time
variability of the parameters. These criteria and the availability of
approximate initial estimates are used as decision rules to determine which
parameters need to be estimated, and their precedence order in the sequential
calibration process. The end-to-end ecosystem model ROMS-PISCES-OSMOSE applied
to the Northern Humboldt Current Ecosystem is used as an illustrative case
study.
The pricing of contingent claims and optimal positions in asymptotically complete markets
Date: 2016-09-22 00:00:00

We study utility indifference prices and optimal purchasing quantities for a
contingent claim, in an incomplete semi-martingale market, in the presence of
vanishing hedging errors and/or risk aversion. Assuming that the average
indifference price converges to a well defined limit, we prove that optimally
taken positions become large in absolute value at a specific rate. We draw
motivation from and make connections to Large Deviations theory, and in
particular, the celebrated G\"{a}rtner-Ellis theorem. We analyze a series of
well studied examples where this limiting behavior occurs, such as fixed
markets with vanishing risk aversion, the basis risk model with high
correlation, models of large markets with vanishing trading restrictions and
the Black-Scholes-Merton model with either vanishing default probabilities or
vanishing transaction costs. Lastly, we show that the large claim regime could
naturally arise in partial equilibrium models.
A biophysical model of cell evolution after cytotoxic treatments: damage, repair and cell response
Date: 2015-09-21 00:00:00

We present a theoretical agent-based model of cell evolution under the action
of cytotoxic treatments, such as radioteraphy or chemoteraphy. The major
features of cell cycle and proliferation, cell damage and repair, and chemical
diffusion are included. Cell evolution is based on a discrete Markov chain,
with cells stepping along a sequence of discrete internal states from 'normal'
to 'inactive'. Probabilistic laws are introduced for each type of event a cell
can undergo during its life cycle: duplication, arrest, apoptosis, senescence,
damage, healing. We adjust the model parameters on a series of cell irradiation
experiments, carried out in a clinical LINAC at 20 MV, in which the damage and
repair kinetics of single- and double-strand breaks are followed. Two showcase
applications of the model are then presented. In the first one, we reconstruct
the cell survival curves from a number of published low- and high-dose
irradiation experiments. We reobtain a very good description of the data
without assuming the well-known linear-quadratic model, but instead including a
variable DSB repair probability, which is found to spontaneously saturate with
an exponential decay at increasingly high doses. As a second test, we attempt
to simulate the two extreme possibilities of the so-called 'bystander' effect
in radiotherapy: the 'local' effect versus a 'global' effect, respectively
activated by the short-range or long-range diffusion of some factor, presumably
secreted by the irradiated cells. Even with an oversimplified simulation, we
could demonstrate a sizeable difference in the proliferation rate of
non-irradiated cells, the proliferation acceleration being much larger for the
global than the local effect, for relatively small fractions of irradiated
cells in the colony.