title stringlengths 7 239 | abstract stringlengths 7 2.76k | cs int64 0 1 | phy int64 0 1 | math int64 0 1 | stat int64 0 1 | quantitative biology int64 0 1 | quantitative finance int64 0 1 |
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Autonomy in the interactive music system VIVO | Interactive Music Systems (IMS) have introduced a new world of music-making
modalities. But can we really say that they create music, as in true autonomous
creation? Here we discuss Video Interactive VST Orchestra (VIVO), an IMS that
considers extra-musical information by adopting a simple salience based model
of use... | 1 | 0 | 0 | 0 | 0 | 0 |
Information and estimation in Fokker-Planck channels | We study the relationship between information- and estimation-theoretic
quantities in time-evolving systems. We focus on the Fokker-Planck channel
defined by a general stochastic differential equation, and show that the time
derivatives of entropy, KL divergence, and mutual information are characterized
by estimation... | 1 | 0 | 1 | 1 | 0 | 0 |
The role of industry, occupation, and location specific knowledge in the survival of new firms | How do regions acquire the knowledge they need to diversify their economic
activities? How does the migration of workers among firms and industries
contribute to the diffusion of that knowledge? Here we measure the industry,
occupation, and location-specific knowledge carried by workers from one
establishment to the ... | 0 | 0 | 0 | 0 | 0 | 1 |
Bayes-Optimal Entropy Pursuit for Active Choice-Based Preference Learning | We analyze the problem of learning a single user's preferences in an active
learning setting, sequentially and adaptively querying the user over a finite
time horizon. Learning is conducted via choice-based queries, where the user
selects her preferred option among a small subset of offered alternatives.
These querie... | 1 | 0 | 0 | 1 | 0 | 0 |
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes | It is widely observed that deep learning models with learned parameters
generalize well, even with much more model parameters than the number of
training samples. We systematically investigate the underlying reasons why deep
neural networks often generalize well, and reveal the difference between the
minima (with the... | 1 | 0 | 0 | 1 | 0 | 0 |
Benchmarking Decoupled Neural Interfaces with Synthetic Gradients | Artifical Neural Networks are a particular class of learning systems modeled
after biological neural functions with an interesting penchant for Hebbian
learning, that is "neurons that wire together, fire together". However, unlike
their natural counterparts, artificial neural networks have a close and
stringent coupl... | 1 | 0 | 0 | 1 | 0 | 0 |
Macquarie University at BioASQ 5b -- Query-based Summarisation Techniques for Selecting the Ideal Answers | Macquarie University's contribution to the BioASQ challenge (Task 5b Phase B)
focused on the use of query-based extractive summarisation techniques for the
generation of the ideal answers. Four runs were submitted, with approaches
ranging from a trivial system that selected the first $n$ snippets, to the use
of deep ... | 1 | 0 | 0 | 0 | 0 | 0 |
Network Topology Modulation for Energy and Data Transmission in Internet of Magneto-Inductive Things | Internet-of-things (IoT) architectures connecting a massive number of
heterogeneous devices need energy efficient, low hardware complexity, low cost,
simple and secure mechanisms to realize communication among devices. One of the
emerging schemes is to realize simultaneous wireless information and power
transfer (SWI... | 1 | 0 | 1 | 0 | 0 | 0 |
Core structure of two-dimensional Fermi gas vortices in the BEC-BCS crossover region | We report $T=0$ diffusion Monte Carlo results for the ground-state and vortex
excitation of unpolarized spin-1/2 fermions in a two-dimensional disk. We
investigate how vortex core structure properties behave over the BEC-BCS
crossover. We calculate the vortex excitation energy, density profiles, and
vortex core prope... | 0 | 1 | 0 | 0 | 0 | 0 |
One can hear the Euler characteristic of a simplicial complex | We prove that that the number p of positive eigenvalues of the connection
Laplacian L of a finite abstract simplicial complex G matches the number b of
even dimensional simplices in G and that the number n of negative eigenvalues
matches the number f of odd-dimensional simplices in G. The Euler
characteristic X(G) of... | 1 | 0 | 1 | 0 | 0 | 0 |
A new complete Calabi-Yau metric on $\mathbb{C}^3$ | Motivated by the study of collapsing Calabi-Yau threefolds with a Lefschetz
K3 fibration, we construct a complete Calabi-Yau metric on $\mathbb{C}^3$ with
maximal volume growth, which in the appropriate scale is expected to model the
collapsing metric near the nodal point. This new Calabi-Yau metric has singular
tang... | 0 | 0 | 1 | 0 | 0 | 0 |
Weighted density fields as improved probes of modified gravity models | When it comes to searches for extensions to general relativity, large efforts
are being dedicated to accurate predictions for the power spectrum of density
perturbations. While this observable is known to be sensitive to the
gravitational theory, its efficiency as a diagnostic for gravity is
significantly reduced whe... | 0 | 1 | 0 | 0 | 0 | 0 |
Nonlinear control for an uncertain electromagnetic actuator | This paper presents the design of a nonlinear control law for a typical
electromagnetic actuator system. Electromagnetic actuators are widely
implemented in industrial applications, and especially as linear positioning
system. In this work, we aim at taking into account a magnetic phenomenon that
is usually neglected... | 1 | 0 | 0 | 0 | 0 | 0 |
Adaptation and Robust Learning of Probabilistic Movement Primitives | Probabilistic representations of movement primitives open important new
possibilities for machine learning in robotics. These representations are able
to capture the variability of the demonstrations from a teacher as a
probability distribution over trajectories, providing a sensible region of
exploration and the abi... | 1 | 0 | 0 | 1 | 0 | 0 |
Transverse spinning of light with globally unique handedness | Access to the transverse spin of light has unlocked new regimes in
topological photonics and optomechanics. To achieve the transverse spin of
nonzero longitudinal fields, various platforms that derive transversely
confined waves based on focusing, interference, or evanescent waves have been
suggested. Nonetheless, be... | 0 | 1 | 0 | 0 | 0 | 0 |
A general class of quasi-independence tests for left-truncated right-censored data | In survival studies, classical inferences for left-truncated data require
quasi-independence, a property that the joint density of truncation time and
failure time is factorizable into their marginal densities in the observable
region. The quasi-independence hypothesis is testable; many authors have
developed tests f... | 0 | 0 | 0 | 1 | 0 | 0 |
EPIC 220204960: A Quadruple Star System Containing Two Strongly Interacting Eclipsing Binaries | We present a strongly interacting quadruple system associated with the K2
target EPIC 220204960. The K2 target itself is a Kp = 12.7 magnitude star at
Teff ~ 6100 K which we designate as "B-N" (blue northerly image). The host of
the quadruple system, however, is a Kp = 17 magnitude star with a composite
M-star spectr... | 0 | 1 | 0 | 0 | 0 | 0 |
On the higher Cheeger problem | We develop the notion of higher Cheeger constants for a measurable set
$\Omega \subset \mathbb{R}^N$. By the $k$-th Cheeger constant we mean the value
\[h_k(\Omega) = \inf \max \{h_1(E_1), \dots, h_1(E_k)\},\] where the infimum is
taken over all $k$-tuples of mutually disjoint subsets of $\Omega$, and
$h_1(E_i)$ is t... | 0 | 0 | 1 | 0 | 0 | 0 |
Petri Nets and Machines of Things That Flow | Petri nets are an established graphical formalism for modeling and analyzing
the behavior of systems. An important consideration of the value of Petri nets
is their use in describing both the syntax and semantics of modeling
formalisms. Describing a modeling notation in terms of a formal technique such
as Petri nets ... | 1 | 0 | 0 | 0 | 0 | 0 |
Fundamental Conditions for Low-CP-Rank Tensor Completion | We consider the problem of low canonical polyadic (CP) rank tensor
completion. A completion is a tensor whose entries agree with the observed
entries and its rank matches the given CP rank. We analyze the manifold
structure corresponding to the tensors with the given rank and define a set of
polynomials based on the ... | 1 | 0 | 1 | 1 | 0 | 0 |
Multiplex Network Regression: How do relations drive interactions? | We introduce a statistical method to investigate the impact of dyadic
relations on complex networks generated from repeated interactions. It is based
on generalised hypergeometric ensembles, a class of statistical network
ensembles developed recently. We represent different types of known relations
between system ele... | 1 | 1 | 0 | 1 | 0 | 0 |
Hall-Littlewood-PushTASEP and its KPZ limit | We study a new model of interactive particle systems which we call the
randomly activated cascading exclusion process (RACEP). Particles wake up
according to exponential clocks and then take a geometric number of steps. If
another particle is encountered during these steps, the first particle goes to
sleep at that lo... | 0 | 0 | 1 | 1 | 0 | 0 |
Pricing for Online Resource Allocation: Intervals and Paths | We present pricing mechanisms for several online resource allocation problems
which obtain tight or nearly tight approximations to social welfare. In our
settings, buyers arrive online and purchase bundles of items; buyers' values
for the bundles are drawn from known distributions. This problem is closely
related to ... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning best K analogies from data distribution for case-based software effort estimation | Case-Based Reasoning (CBR) has been widely used to generate good software
effort estimates. The predictive performance of CBR is a dataset dependent and
subject to extremely large space of configuration possibilities. Regardless of
the type of adaptation technique, deciding on the optimal number of similar
cases to b... | 1 | 0 | 0 | 0 | 0 | 0 |
Optimal designs for enzyme inhibition kinetic models | In this paper we present a new method for determining optimal designs for
enzyme inhibition kinetic models, which are used to model the influence of the
concentration of a substrate and an inhibition on the velocity of a reaction.
The approach uses a nonlinear transformation of the vector of predictors such
that the ... | 0 | 0 | 1 | 1 | 0 | 0 |
Highly Granular Calorimeters: Technologies and Results | The CALICE collaboration is developing highly granular calorimeters for
experiments at a future lepton collider primarily to establish technologies for
particle flow event reconstruction. These technologies also find applications
elsewhere, such as detector upgrades for the LHC. Meanwhile, the large data
sets collect... | 0 | 1 | 0 | 0 | 0 | 0 |
Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods | Hamiltonian Monte Carlo has emerged as a standard tool for posterior
computation. In this article, we present an extension that can efficiently
explore target distributions with discontinuous densities, which in turn
enables efficient sampling from ordinal parameters though embedding of
probability mass functions int... | 0 | 0 | 0 | 1 | 0 | 0 |
Optimal boundary gradient estimates for Lamé systems with partially infinite coefficients | In this paper, we derive the pointwise upper bounds and lower bounds on the
gradients of solutions to the Lamé systems with partially infinite
coefficients as the surface of discontinuity of the coefficients of the system
is located very close to the boundary. When the distance tends to zero, the
optimal blow-up rate... | 0 | 0 | 1 | 0 | 0 | 0 |
On a variable step size modification of Hines' method in computational neuroscience | For simulating large networks of neurons Hines proposed a method which uses
extensively the structure of the arising systems of ordinary differential
equations in order to obtain an efficient implementation. The original method
requires constant step sizes and produces the solution on a staggered grid. In
the present... | 0 | 0 | 1 | 0 | 0 | 0 |
Neural Question Answering at BioASQ 5B | This paper describes our submission to the 2017 BioASQ challenge. We
participated in Task B, Phase B which is concerned with biomedical question
answering (QA). We focus on factoid and list question, using an extractive QA
model, that is, we restrict our system to output substrings of the provided
text snippets. At t... | 1 | 0 | 0 | 0 | 0 | 0 |
Implementation of Smart Contracts Using Hybrid Architectures with On- and Off-Blockchain Components | Recently, decentralised (on-blockchain) platforms have emerged to complement
centralised (off-blockchain) platforms for the implementation of automated,
digital (smart) contracts. However, neither alternative can individually
satisfy the requirements of a large class of applications. On-blockchain
platforms suffer fr... | 1 | 0 | 0 | 0 | 0 | 0 |
Electro-mechanical control of an on-chip optical beam splitter containing an embedded quantum emitter | We demonstrate electro-mechanical control of an on-chip GaAs optical beam
splitter containing a quantum dot single-photon source. The beam splitter
consists of two nanobeam waveguides, which form a directional coupler (DC). The
splitting ratio of the DC is controlled by varying the out-of-plane separation
of the two ... | 0 | 1 | 0 | 0 | 0 | 0 |
Data Distillation for Controlling Specificity in Dialogue Generation | People speak at different levels of specificity in different situations.
Depending on their knowledge, interlocutors, mood, etc.} A conversational agent
should have this ability and know when to be specific and when to be general.
We propose an approach that gives a neural network--based conversational agent
this abi... | 1 | 0 | 0 | 0 | 0 | 0 |
Non-locality of the meet levels of the Trotter-Weil Hierarchy | We prove that the meet level $m$ of the Trotter-Weil, $\mathsf{V}_m$ is not
local for all $m \geq 1$, as conjectured in a paper by Kufleitner and Lauser.
In order to show this, we explicitly provide a language whose syntactic
semigroup is in $L \mathsf{V}_m$ and not in $\mathsf{V}_m*\mathsf{D}$.
| 1 | 0 | 1 | 0 | 0 | 0 |
Particle-based and Meshless Methods with Aboria | Aboria is a powerful and flexible C++ library for the implementation of
particle-based numerical methods. The particles in such methods can represent
actual particles (e.g. Molecular Dynamics) or abstract particles used to
discretise a continuous function over a domain (e.g. Radial Basis Functions).
Aboria provides a... | 1 | 0 | 0 | 0 | 0 | 0 |
Backlund transformations and divisor doubling | In classical mechanics well-known cryptographic algorithms and protocols can
be very useful for construction canonical transformations preserving form of
Hamiltonians. We consider application of a standard generic divisor doubling
for construction of new auto Bäcklund transformations for the Lagrange top
and Hénon-He... | 0 | 1 | 1 | 0 | 0 | 0 |
KATE: K-Competitive Autoencoder for Text | Autoencoders have been successful in learning meaningful representations from
image datasets. However, their performance on text datasets has not been widely
studied. Traditional autoencoders tend to learn possibly trivial
representations of text documents due to their confounding properties such as
high-dimensionali... | 1 | 0 | 0 | 1 | 0 | 0 |
Stochastic evolution equations for large portfolios of stochastic volatility models | We consider a large market model of defaultable assets in which the asset
price processes are modelled as Heston-type stochastic volatility models with
default upon hitting a lower boundary. We assume that both the asset prices and
their volatilities are correlated through systemic Brownian motions. We are
interested... | 0 | 0 | 1 | 0 | 0 | 0 |
Learning to Address Health Inequality in the United States with a Bayesian Decision Network | Life-expectancy is a complex outcome driven by genetic, socio-demographic,
environmental and geographic factors. Increasing socio-economic and health
disparities in the United States are propagating the longevity-gap, making it a
cause for concern. Earlier studies have probed individual factors but an
integrated pict... | 0 | 0 | 0 | 1 | 0 | 0 |
Asynchronous parallel primal-dual block update methods | Recent several years have witnessed the surge of asynchronous (async-)
parallel computing methods due to the extremely big data involved in many
modern applications and also the advancement of multi-core machines and
computer clusters. In optimization, most works about async-parallel methods are
on unconstrained prob... | 0 | 0 | 1 | 1 | 0 | 0 |
Towards Noncommutative Topological Quantum Field Theory: New invariants for 3-manifolds | We define some new invariants for 3-manifolds using the space of taut codim-1
foliations along with various techniques from noncommutative geometry. These
invariants originate from our attempt to generalise Topological Quantum Field
Theories in the Noncommutative geometry / topology realm.
| 0 | 0 | 1 | 0 | 0 | 0 |
Chaotic Dynamic S Boxes Based Substitution Approach for Digital Images | In this paper, we propose an image encryption algorithm based on the chaos,
substitution boxes, nonlinear transformation in Galois field and Latin square.
Initially, the dynamic S boxes are generated using Fisher Yates shuffle method
and piece wise linear chaotic map. The algorithm utilizes advantages of keyed
Latin ... | 1 | 0 | 0 | 0 | 0 | 0 |
Randomized Optimal Transport on a Graph: Framework and New Distance Measures | The recently developed bag-of-paths framework consists in setting a
Gibbs-Boltzmann distribution on all feasible paths of a graph. This probability
distribution favors short paths over long ones, with a free parameter (the
temperature $T > 0$) controlling the entropic level of the distribution. This
formalism enables... | 1 | 0 | 0 | 1 | 0 | 0 |
A Generative Model for Natural Sounds Based on Latent Force Modelling | Recent advances in analysis of subband amplitude envelopes of natural sounds
have resulted in convincing synthesis, showing subband amplitudes to be a
crucial component of perception. Probabilistic latent variable analysis is
particularly revealing, but existing approaches don't incorporate prior
knowledge about the ... | 0 | 0 | 0 | 1 | 0 | 0 |
Linear and Nonlinear Heat Equations on a p-Adic Ball | We study the Vladimirov fractional differentiation operator $D^\alpha_N$,
$\alpha >0, N\in \mathbb Z$, on a $p$-adic ball $B_N=\{ x\in \mathbb Q_p:\
|x|_p\le p^N\}$. To its known interpretations via restriction from a similar
operator on $\mathbb Q_p$ and via a certain stochastic process on $B_N$, we add
an interpret... | 0 | 0 | 1 | 0 | 0 | 0 |
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations | We propose position-velocity encoders (PVEs) which learn---without
supervision---to encode images to positions and velocities of task-relevant
objects. PVEs encode a single image into a low-dimensional position state and
compute the velocity state from finite differences in position. In contrast to
autoencoders, posi... | 1 | 0 | 0 | 0 | 0 | 0 |
Few-shot Learning by Exploiting Visual Concepts within CNNs | Convolutional neural networks (CNNs) are one of the driving forces for the
advancement of computer vision. Despite their promising performances on many
tasks, CNNs still face major obstacles on the road to achieving ideal machine
intelligence. One is that CNNs are complex and hard to interpret. Another is
that standa... | 1 | 0 | 0 | 1 | 0 | 0 |
Noise Statistics Oblivious GARD For Robust Regression With Sparse Outliers | Linear regression models contaminated by Gaussian noise (inlier) and possibly
unbounded sparse outliers are common in many signal processing applications.
Sparse recovery inspired robust regression (SRIRR) techniques are shown to
deliver high quality estimation performance in such regression models.
Unfortunately, mo... | 0 | 0 | 0 | 1 | 0 | 0 |
Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation | This paper addresses the problem of depth estimation from a single still
image. Inspired by recent works on multi- scale convolutional neural networks
(CNN), we propose a deep model which fuses complementary information derived
from multiple CNN side outputs. Different from previous methods, the
integration is obtain... | 1 | 0 | 0 | 0 | 0 | 0 |
On the relation between representations and computability | One of the fundamental results in computability is the existence of
well-defined functions that cannot be computed. In this paper we study the
effects of data representation on computability; we show that, while for each
possible way of representing data there exist incomputable functions, the
computability of a spec... | 1 | 0 | 0 | 0 | 0 | 0 |
Towards Proxemic Mobile Collocated Interactions | Research on mobile collocated interactions has been exploring situations
where collocated users engage in collaborative activities using their personal
mobile devices (e.g., smartphones and tablets), thus going from
personal/individual toward shared/multiuser experiences and interactions. The
proliferation of ever-sm... | 1 | 0 | 0 | 0 | 0 | 0 |
Adjusting for bias introduced by instrumental variable estimation in the Cox Proportional Hazards Model | Instrumental variable (IV) methods are widely used for estimating average
treatment effects in the presence of unmeasured confounders. However, the
capability of existing IV procedures, and most notably the two-stage residual
inclusion (2SRI) procedure recommended for use in nonlinear contexts, to
account for unmeasu... | 0 | 0 | 0 | 1 | 0 | 0 |
On the length of perverse sheaves and D-modules | We prove that the length function for perverse sheaves and algebraic regular
holonomic D-modules on a smooth complex algebraic variety Y is an absolute
Q-constructible function. One consequence is: for "any" fixed natural (derived)
functor F between constructible complexes or perverse sheaves on two smooth
varieties ... | 0 | 0 | 1 | 0 | 0 | 0 |
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks | Deep neural networks are commonly developed and trained in 32-bit floating
point format. Significant gains in performance and energy efficiency could be
realized by training and inference in numerical formats optimized for deep
learning. Despite advances in limited precision inference in recent years,
training of neu... | 1 | 0 | 0 | 1 | 0 | 0 |
Bounds on the expected size of the maximum agreement subtree for a given tree shape | We show that the expected size of the maximum agreement subtree of two
$n$-leaf trees, uniformly random among all trees with the shape, is
$\Theta(\sqrt{n})$. To derive the lower bound, we prove a global structural
result on a decomposition of rooted binary trees into subgroups of leaves
called blobs. To obtain the u... | 0 | 0 | 0 | 0 | 1 | 0 |
Magnetic ground state of SrRuO$_3$ thin film and applicability of standard first-principles approximations to metallic magnetism | A systematic first-principles study has been performed to understand the
magnetism of thin film SrRuO$_3$ which lots of research efforts have been
devoted to but no clear consensus has been reached about its ground state
properties. The relative t$_{2g}$ level difference, lattice distortion as well
as the layer thick... | 0 | 1 | 0 | 0 | 0 | 0 |
No minimal tall Borel ideal in the Katětov order | Answering a question of the second listed author we show that there is no
tall Borel ideal minimal among all tall Borel ideals in the Katětov order.
| 0 | 0 | 1 | 0 | 0 | 0 |
RelNN: A Deep Neural Model for Relational Learning | Statistical relational AI (StarAI) aims at reasoning and learning in noisy
domains described in terms of objects and relationships by combining
probability with first-order logic. With huge advances in deep learning in the
current years, combining deep networks with first-order logic has been the
focus of several rec... | 1 | 0 | 0 | 1 | 0 | 0 |
$ΔN_{\text{eff}}$ and entropy production from early-decaying gravitinos | Gravitinos are a fundamental prediction of supergravity, their mass ($m_{G}$)
is informative of the value of the SUSY breaking scale, and, if produced during
reheating, their number density is a function of the reheating temperature
($T_{\text{rh}}$). As a result, constraining their parameter space provides in
turn s... | 0 | 1 | 0 | 0 | 0 | 0 |
Game-Theoretic Choice of Curing Rates Against Networked SIS Epidemics by Human Decision-Makers | We study networks of human decision-makers who independently decide how to
protect themselves against Susceptible-Infected-Susceptible (SIS) epidemics.
Motivated by studies in behavioral economics showing that humans perceive
probabilities in a nonlinear fashion, we examine the impacts of such
misperceptions on the e... | 1 | 0 | 0 | 0 | 0 | 0 |
A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins | Membrane proteins constitute a large portion of the human proteome and
perform a variety of important functions as membrane receptors, transport
proteins, enzymes, signaling proteins, and more. The computational studies of
membrane proteins are usually much more complicated than those of globular
proteins. Here we pr... | 0 | 1 | 0 | 0 | 0 | 0 |
An ALMA survey of submillimetre galaxies in the Extended Chandra Deep Field South: Spectroscopic redshifts | We present spectroscopic redshifts of S(870)>2mJy submillimetre galaxies
(SMGs) which have been identified from the ALMA follow-up observations of 870um
detected sources in the Extended Chandra Deep Field South (the ALMA-LESS
survey). We derive spectroscopic redshifts for 52 SMGs, with a median of
z=2.4+/-0.1. Howeve... | 0 | 1 | 0 | 0 | 0 | 0 |
On the structure of Hausdorff moment sequences of complex matrices | The paper treats several aspects of the truncated matricial
$[\alpha,\beta]$-Hausdorff type moment problems. It is shown that each
$[\alpha,\beta]$-Hausdorff moment sequence has a particular intrinsic
structure. More precisely, each element of this sequence varies within a closed
bounded matricial interval. The case ... | 0 | 0 | 1 | 0 | 0 | 0 |
Lower bounds on the Bergman metric near points of infinite type | Let $\Omega$ be a pseudoconvex domain in $\mathbb C^n$ satisfying an
$f$-property for some function $f$. We show that the Bergman metric associated
to $\Omega$ has the lower bound $\tilde g(\delta_\Omega(z)^{-1})$ where
$\delta_\Omega(z)$ is the distance from $z$ to the boundary $\partial\Omega$
and $\tilde g$ is a s... | 0 | 0 | 1 | 0 | 0 | 0 |
Minimal Approximately Balancing Weights: Asymptotic Properties and Practical Considerations | In observational studies and sample surveys, and regression settings,
weighting methods are widely used to adjust for or balance observed covariates.
Recently, a few weighting methods have been proposed that focus on directly
balancing the covariates while minimizing the dispersion of the weights. In
this paper, we c... | 0 | 0 | 1 | 1 | 0 | 0 |
Phonetic-attention scoring for deep speaker features in speaker verification | Recent studies have shown that frame-level deep speaker features can be
derived from a deep neural network with the training target set to discriminate
speakers by a short speech segment. By pooling the frame-level features,
utterance-level representations, called d-vectors, can be derived and used in
the automatic s... | 1 | 0 | 0 | 0 | 0 | 0 |
MobInsight: A Framework Using Semantic Neighborhood Features for Localized Interpretations of Urban Mobility | Collective urban mobility embodies the residents' local insights on the city.
Mobility practices of the residents are produced from their spatial choices,
which involve various considerations such as the atmosphere of destinations,
distance, past experiences, and preferences. The advances in mobile computing
and the ... | 1 | 0 | 0 | 0 | 0 | 0 |
The Broad Consequences of Narrow Banking | We investigate the macroeconomic consequences of narrow banking in the
context of stock-flow consistent models. We begin with an extension of the
Goodwin-Keen model incorporating time deposits, government bills, cash, and
central bank reserves to the base model with loans and demand deposits and use
it to describe a ... | 0 | 0 | 0 | 0 | 0 | 1 |
Sitatapatra: Blocking the Transfer of Adversarial Samples | Convolutional Neural Networks (CNNs) are widely used to solve classification
tasks in computer vision. However, they can be tricked into misclassifying
specially crafted `adversarial' samples -- and samples built to trick one model
often work alarmingly well against other models trained on the same task. In
this pape... | 1 | 0 | 0 | 1 | 0 | 0 |
Neurofeedback: principles, appraisal and outstanding issues | Neurofeedback is a form of brain training in which subjects are fed back
information about some measure of their brain activity which they are
instructed to modify in a way thought to be functionally advantageous. Over the
last twenty years, NF has been used to treat various neurological and
psychiatric conditions, a... | 0 | 0 | 0 | 0 | 1 | 0 |
Automating Image Analysis by Annotating Landmarks with Deep Neural Networks | Image and video analysis is often a crucial step in the study of animal
behavior and kinematics. Often these analyses require that the position of one
or more animal landmarks are annotated (marked) in numerous images. The process
of annotating landmarks can require a significant amount of time and tedious
labor, whi... | 1 | 0 | 0 | 0 | 0 | 0 |
Weak-strong uniqueness in fluid dynamics | We give a survey of recent results on weak-strong uniqueness for compressible
and incompressible Euler and Navier-Stokes equations, and also make some new
observations. The importance of the weak-strong uniqueness principle stems, on
the one hand, from the instances of non-uniqueness for the Euler equations
exhibited... | 0 | 1 | 1 | 0 | 0 | 0 |
Cognitive Subscore Trajectory Prediction in Alzheimer's Disease | Accurate diagnosis of Alzheimer's Disease (AD) entails clinical evaluation of
multiple cognition metrics and biomarkers. Metrics such as the Alzheimer's
Disease Assessment Scale - Cognitive test (ADAS-cog) comprise multiple
subscores that quantify different aspects of a patient's cognitive state such
as learning, mem... | 1 | 0 | 0 | 1 | 0 | 0 |
Variance Regularizing Adversarial Learning | We introduce a novel approach for training adversarial models by replacing
the discriminator score with a bi-modal Gaussian distribution over the
real/fake indicator variables. In order to do this, we train the Gaussian
classifier to match the target bi-modal distribution implicitly through
meta-adversarial training.... | 1 | 0 | 0 | 1 | 0 | 0 |
Improving fairness in machine learning systems: What do industry practitioners need? | The potential for machine learning (ML) systems to amplify social inequities
and unfairness is receiving increasing popular and academic attention. A surge
of recent work has focused on the development of algorithmic tools to assess
and mitigate such unfairness. If these tools are to have a positive impact on
industr... | 1 | 0 | 0 | 0 | 0 | 0 |
PICOSEC: Charged particle Timing to 24 picosecond Precision with MicroPattern Gas Detectors | The prospect of pileup induced backgrounds at the High Luminosity LHC
(HL-LHC) has stimulated intense interest in technology for charged particle
timing at high rates. In contrast to the role of timing for particle
identification, which has driven incremental improvements in timing, the LHC
timing challenge dictates ... | 0 | 1 | 0 | 0 | 0 | 0 |
The first result on 76Ge neutrinoless double beta decay from CDEX-1 experiment | We report the first result on Ge-76 neutrinoless double beta decay from
CDEX-1 experiment at China Jinping Underground Laboratory. A mass of 994 g
p-type point-contact high purity germanium detector has been installed to
search the neutrinoless double beta decay events, as well as to directly detect
dark matter parti... | 0 | 1 | 0 | 0 | 0 | 0 |
Measuring scientific buzz | Keywords are important for information retrieval. They are used to classify
and sort papers. However, these terms can also be used to study trends within
and across fields. We want to explore the lifecycle of new keywords. How often
do new terms come into existence and how long till they fade out? In this
paper, we p... | 1 | 0 | 0 | 0 | 0 | 0 |
Fully Optical Spacecraft Communications: Implementing an Omnidirectional PV-Cell Receiver and 8Mb/s LED Visible Light Downlink with Deep Learning Error Correction | Free space optical communication techniques have been the subject of numerous
investigations in recent years, with multiple missions expected to fly in the
near future. Existing methods require high pointing accuracies, drastically
driving up overall system cost. Recent developments in LED-based visible light
communi... | 1 | 0 | 0 | 0 | 0 | 0 |
Linear compartmental models: input-output equations and operations that preserve identifiability | This work focuses on the question of how identifiability of a mathematical
model, that is, whether parameters can be recovered from data, is related to
identifiability of its submodels. We look specifically at linear compartmental
models and investigate when identifiability is preserved after adding or
removing model... | 0 | 0 | 0 | 0 | 1 | 0 |
On Nonlinear Dimensionality Reduction, Linear Smoothing and Autoencoding | We develop theory for nonlinear dimensionality reduction (NLDR). A number of
NLDR methods have been developed, but there is limited understanding of how
these methods work and the relationships between them. There is limited basis
for using existing NLDR theory for deriving new algorithms. We provide a novel
framewor... | 0 | 0 | 0 | 1 | 0 | 0 |
Asymmetric Deep Supervised Hashing | Hashing has been widely used for large-scale approximate nearest neighbor
search because of its storage and search efficiency. Recent work has found that
deep supervised hashing can significantly outperform non-deep supervised
hashing in many applications. However, most existing deep supervised hashing
methods adopt ... | 1 | 0 | 0 | 1 | 0 | 0 |
Pseudo-Separation for Assessment of Structural Vulnerability of a Network | Based upon the idea that network functionality is impaired if two nodes in a
network are sufficiently separated in terms of a given metric, we introduce two
combinatorial \emph{pseudocut} problems generalizing the classical min-cut and
multi-cut problems. We expect the pseudocut problems will find broad relevance
to ... | 1 | 0 | 0 | 0 | 0 | 0 |
A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes | In this paper we use Gaussian Process (GP) regression to propose a novel
approach for predicting volatility of financial returns by forecasting the
envelopes of the time series. We provide a direct comparison of their
performance to traditional approaches such as GARCH. We compare the forecasting
power of three appro... | 1 | 0 | 0 | 1 | 0 | 0 |
Out-of-Sample Testing for GANs | We propose a new method to evaluate GANs, namely EvalGAN. EvalGAN relies on a
test set to directly measure the reconstruction quality in the original sample
space (no auxiliary networks are necessary), and it also computes the
(log)likelihood for the reconstructed samples in the test set. Further, EvalGAN
is agnostic... | 1 | 0 | 0 | 1 | 0 | 0 |
Quantum periodicity in the critical current of superconducting rings with asymmetric link-up of current leads | We use superconducting rings with asymmetric link-up of current leads for
experimental investigation of winding number change at magnetic field
corresponding to the half of the flux quantum inside the ring. According to the
conventional theory, the critical current of such rings should change by jump
due to this chan... | 0 | 1 | 0 | 0 | 0 | 0 |
Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version) | Human societies around the world interact with each other by developing and
maintaining social norms, and it is critically important to understand how such
norms emerge and change. In this work, we define an evolutionary game-theoretic
model to study how norms change in a society, based on the idea that different
str... | 1 | 0 | 0 | 0 | 0 | 0 |
A Story of Parametric Trace Slicing, Garbage and Static Analysis | This paper presents a proposal (story) of how statically detecting
unreachable objects (in Java) could be used to improve a particular runtime
verification approach (for Java), namely parametric trace slicing. Monitoring
algorithms for parametric trace slicing depend on garbage collection to (i)
cleanup data-structur... | 1 | 0 | 0 | 0 | 0 | 0 |
Extended TQFT arising from enriched multi-fusion categories | We define a symmetric monoidal (4,3)-category with duals whose objects are
certain enriched multi-fusion categories. For every modular tensor category
$\mathcal{C}$, there is a self enriched multi-fusion category $\mathfrak{C}$
giving rise to an object of this symmetric monoidal (4,3)-category. We
conjecture that the... | 0 | 0 | 1 | 0 | 0 | 0 |
Multipermutation Ulam Sphere Analysis Toward Characterizing Maximal Code Size | Permutation codes, in the form of rank modulation, have shown promise for
applications such as flash memory. One of the metrics recently suggested as
appropriate for rank modulation is the Ulam metric, which measures the minimum
translocation distance between permutations. Multipermutation codes have also
been propos... | 1 | 0 | 1 | 0 | 0 | 0 |
Thermophysical characteristics of the large main-belt asteroid (349) Dembowska | (349) Dembowska, a large, bright main-belt asteroid, has a fast rotation and
oblique spin axis. It may have experienced partial melting and differentiation.
We constrain Dembowska's thermophysical properties, e.g., thermal inertia,
roughness fraction, geometric albedo and effective diameter within 3$\sigma$
uncertain... | 0 | 1 | 0 | 0 | 0 | 0 |
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning | We propose CM3, a new deep reinforcement learning method for cooperative
multi-agent problems where agents must coordinate for joint success in
achieving different individual goals. We restructure multi-agent learning into
a two-stage curriculum, consisting of a single-agent stage for learning to
accomplish individua... | 0 | 0 | 0 | 1 | 0 | 0 |
Adaptive twisting sliding mode control for quadrotor unmanned aerial vehicles | This work addresses the problem of robust attitude control of quadcopters.
First, the mathematical model of the quadcopter is derived considering factors
such as nonlinearity, external disturbances, uncertain dynamics and strong
coupling. An adaptive twisting sliding mode control algorithm is then developed
with the ... | 1 | 0 | 0 | 0 | 0 | 0 |
Dynamic Laplace: Efficient Centrality Measure for Weighted or Unweighted Evolving Networks | With its origin in sociology, Social Network Analysis (SNA), quickly emerged
and spread to other areas of research, including anthropology, biology,
information science, organizational studies, political science, and computer
science. Being it's objective the investigation of social structures through
the use of netw... | 1 | 0 | 0 | 0 | 0 | 0 |
Fighting Accounting Fraud Through Forensic Data Analytics | Accounting fraud is a global concern representing a significant threat to the
financial system stability due to the resulting diminishing of the market
confidence and trust of regulatory authorities. Several tricks can be used to
commit accounting fraud, hence the need for non-static regulatory interventions
that tak... | 0 | 0 | 0 | 1 | 0 | 0 |
Doubly Stochastic Variational Inference for Deep Gaussian Processes | Gaussian processes (GPs) are a good choice for function approximation as they
are flexible, robust to over-fitting, and provide well-calibrated predictive
uncertainty. Deep Gaussian processes (DGPs) are multi-layer generalisations of
GPs, but inference in these models has proved challenging. Existing approaches
to in... | 0 | 0 | 0 | 1 | 0 | 0 |
Electric properties of carbon nano-onion/polyaniline composites: a combined electric modulus and ac conductivity study | The complex electric modulus and the ac conductivity of carbon
nanoonion/polyaniline composites were studied from 1 mHz to 1 MHz at isothermal
conditions ranging from 15 K to room temperature. The temperature dependence of
the electric modulus and the dc conductivity analyses indicate a couple of
hopping mechanisms. ... | 0 | 1 | 0 | 0 | 0 | 0 |
Uniform Rates of Convergence of Some Representations of Extremes : a first approach | Uniform convergence rates are provided for asymptotic representations of
sample extremes. These bounds which are universal in the sense that they do not
depend on the extreme value index are meant to be extended to arbitrary samples
extremes in coming papers.
| 0 | 0 | 0 | 1 | 0 | 0 |
Predicting regional and pan-Arctic sea ice anomalies with kernel analog forecasting | Predicting Arctic sea ice extent is a notoriously difficult forecasting
problem, even for lead times as short as one month. Motivated by Arctic
intraannual variability phenomena such as reemergence of sea surface
temperature and sea ice anomalies, we use a prediction approach for sea ice
anomalies based on analog for... | 0 | 1 | 0 | 0 | 0 | 0 |
Eigensolutions and spectral analysis of a model for vertical gene transfer of plasmids | Plasmids are autonomously replicating genetic elements in bacteria. At cell
division plasmids are distributed among the two daughter cells. This gene
transfer from one generation to the next is called vertical gene transfer. We
study the dynamics of a bacterial population carrying plasmids and are in
particular inter... | 0 | 0 | 0 | 0 | 1 | 0 |
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