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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Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa | This paper presents a generic Bayesian framework that enables any deep
learning model to actively learn from targeted crowds. Our framework inherits
from recent advances in Bayesian deep learning, and extends existing work by
considering the targeted crowdsourcing approach, where multiple annotators with
unknown expe... | 1 | 0 | 0 | 1 | 0 | 0 |
Using Convolutional Neural Networks to Count Palm Trees in Satellite Images | In this paper we propose a supervised learning system for counting and
localizing palm trees in high-resolution, panchromatic satellite imagery
(40cm/pixel to 1.5m/pixel). A convolutional neural network classifier trained
on a set of palm and no-palm images is applied across a satellite image scene
in a sliding windo... | 1 | 0 | 0 | 0 | 0 | 0 |
The sharp for the Chang model is small | Woodin has shown that if there is a measurable Woodin cardinal then there is,
in an appropriate sense, a sharp for the Chang model. We produce, in a weaker
sense, a sharp for the Chang model using only the existence of a cardinal
$\kappa$ having an extender of length $\kappa^{+\omega_1}$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Weak quadrupole moments | Collective effects in deformed atomic nuclei present possible avenues of
study on the non-spherical distribution of neutrons and the violation of the
local Lorentz invariance. We introduce the weak quadrupole moment of nuclei,
related to the quadrupole distribution of the weak charge in the nucleus. The
weak quadrupo... | 0 | 1 | 0 | 0 | 0 | 0 |
Fast and Accurate Semantic Mapping through Geometric-based Incremental Segmentation | We propose an efficient and scalable method for incrementally building a
dense, semantically annotated 3D map in real-time. The proposed method assigns
class probabilities to each region, not each element (e.g., surfel and voxel),
of the 3D map which is built up through a robust SLAM framework and
incrementally segme... | 1 | 0 | 0 | 0 | 0 | 0 |
Pumping Lemma for Higher-order Languages | We study a pumping lemma for the word/tree languages generated by
higher-order grammars. Pumping lemmas are known up to order-2 word languages
(i.e., for regular/context-free/indexed languages), and have been used to show
that a given language does not belong to the classes of
regular/context-free/indexed languages. ... | 1 | 0 | 0 | 0 | 0 | 0 |
Generative Bridging Network in Neural Sequence Prediction | In order to alleviate data sparsity and overfitting problems in maximum
likelihood estimation (MLE) for sequence prediction tasks, we propose the
Generative Bridging Network (GBN), in which a novel bridge module is introduced
to assist the training of the sequence prediction model (the generator
network). Unlike MLE ... | 1 | 0 | 0 | 1 | 0 | 0 |
A Rule-Based Computational Model of Cognitive Arithmetic | Cognitive arithmetic studies the mental processes used in solving math
problems. This area of research explores the retrieval mechanisms and
strategies used by people during a common cognitive task. Past research has
shown that human performance in arithmetic operations is correlated to the
numerical size of the prob... | 1 | 0 | 0 | 0 | 0 | 0 |
Modular categories are not determined by their modular data | Arbitrarily many pairwise inequivalent modular categories can share the same
modular data. We exhibit a family of examples that are module categories over
twisted Drinfeld doubles of finite groups, and thus in particular integral
modular categories.
| 0 | 0 | 1 | 0 | 0 | 0 |
Change Detection in a Dynamic Stream of Attributed Networks | While anomaly detection in static networks has been extensively studied, only
recently, researchers have focused on dynamic networks. This trend is mainly
due to the capacity of dynamic networks in representing complex physical,
biological, cyber, and social systems. This paper proposes a new methodology
for modeling... | 0 | 0 | 0 | 1 | 0 | 0 |
Local Differential Privacy for Physical Sensor Data and Sparse Recovery | In this work we explore the utility of locally differentially private thermal
sensor data. We design a locally differentially private recovery algorithm for
the 1-dimensional, discrete heat source location problem and analyse its
performance in terms of the Earth Mover Distance error. Our work indicates that
it is po... | 1 | 0 | 0 | 0 | 0 | 0 |
Kernel Feature Selection via Conditional Covariance Minimization | We propose a method for feature selection that employs kernel-based measures
of independence to find a subset of covariates that is maximally predictive of
the response. Building on past work in kernel dimension reduction, we show how
to perform feature selection via a constrained optimization problem involving
the t... | 1 | 0 | 0 | 1 | 0 | 0 |
2s exciton-polariton revealed in an external magnetic field | We demonstrate the existence of the excited state of an exciton-polariton in
a semiconductor microcavity. The strong coupling of the quantum well heavy-hole
exciton in an excited 2s state to the cavity photon is observed in non-zero
magnetic field due to surprisingly fast increase of Rabi energy of the 2s
exciton-pol... | 0 | 1 | 0 | 0 | 0 | 0 |
Weight hierarchy of a class of linear codes relating to non-degenerate quadratic forms | In this paper, we discuss the generalized Hamming weights of a class of
linear codes associated with non-degenerate quadratic forms. In order to do so,
we study the quadratic forms over subspaces of finite field and obtain some
interesting results about subspaces and their dual spaces. On this basis, we
solve all the... | 0 | 0 | 1 | 0 | 0 | 0 |
Cosmological discordances II: Hubble constant, Planck and large-scale-structure data sets | We examine systematically the (in)consistency between cosmological
constraints as obtained from various current data sets of the expansion
history, Large Scale Structure (LSS), and Cosmic Microwave Background (CMB)
from Planck. We run (dis)concordance tests within each set and across the sets
using a recently introdu... | 0 | 1 | 0 | 0 | 0 | 0 |
The perfect spin injection in silicene FS/NS junction | We theoretically investigate the spin injection from a ferromagnetic silicene
to a normal silicene (FS/NS), where the magnetization in the FS is assumed from
the magnetic proximity effect. Based on a silicene lattice model, we
demonstrated that the pure spin injection could be obtained by tuning the Fermi
energy of t... | 0 | 1 | 0 | 0 | 0 | 0 |
Distance-based Protein Folding Powered by Deep Learning | Contact-assisted protein folding has made very good progress, but two
challenges remain. One is accurate contact prediction for proteins lack of many
sequence homologs and the other is that time-consuming folding simulation is
often needed to predict good 3D models from predicted contacts. We show that
protein distan... | 0 | 0 | 0 | 0 | 1 | 0 |
Double Threshold Digraphs | A semiorder is a model of preference relations where each element $x$ is
associated with a utility value $\alpha(x)$, and there is a threshold $t$ such
that $y$ is preferred to $x$ iff $\alpha(y) > \alpha(x)+t$. These are motivated
by the notion that there is some uncertainty in the utility values we assign an
object... | 1 | 0 | 0 | 0 | 0 | 0 |
Directed unions of local quadratic transforms of regular local rings and pullbacks | Let $\{ R_n, {\mathfrak m}_n \}_{n \ge 0}$ be an infinite sequence of regular
local rings with $R_{n+1}$ birationally dominating $R_n$ and ${\mathfrak
m}_nR_{n+1}$ a principal ideal of $R_{n+1}$ for each $n$. We examine properties
of the integrally closed local domain $S = \bigcup_{n \ge 0}R_n$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Lipschitz regularity of deep neural networks: analysis and efficient estimation | Deep neural networks are notorious for being sensitive to small well-chosen
perturbations, and estimating the regularity of such architectures is of utmost
importance for safe and robust practical applications. In this paper, we
investigate one of the key characteristics to assess the regularity of such
methods: the ... | 0 | 0 | 0 | 1 | 0 | 0 |
Preference-based Teaching | We introduce a new model of teaching named "preference-based teaching" and a
corresponding complexity parameter---the preference-based teaching dimension
(PBTD)---representing the worst-case number of examples needed to teach any
concept in a given concept class. Although the PBTD coincides with the
well-known recurs... | 1 | 0 | 0 | 0 | 0 | 0 |
Unified description of dynamics of a repulsive two-component Fermi gas | We study a binary spin-mixture of a zero-temperature repulsively interacting
$^6$Li atoms using both the atomic-orbital and the density functional
approaches. The gas is initially prepared in a configuration of two magnetic
domains and we determine the frequency of the spin-dipole oscillations which
are emerging afte... | 0 | 1 | 0 | 0 | 0 | 0 |
Effective inertial frame in an atom interferometric test of the equivalence principle | In an ideal test of the equivalence principle, the test masses fall in a
common inertial frame. A real experiment is affected by gravity gradients,
which introduce systematic errors by coupling to initial kinematic differences
between the test masses. We demonstrate a method that reduces the sensitivity
of a dual-spe... | 0 | 1 | 0 | 0 | 0 | 0 |
Phonon-mediated spin-flipping mechanism in the spin ices Dy$_2$Ti$_2$O$_7$ and Ho$_2$Ti$_2$O$_7$ | To understand emergent magnetic monopole dynamics in the spin ices
Ho$_2$Ti$_2$O$_7$ and Dy$_2$Ti$_2$O$_7$, it is necessary to investigate the
mechanisms by which spins flip in these materials. Presently there are thought
to be two processes: quantum tunneling at low and intermediate temperatures and
thermally activa... | 0 | 1 | 0 | 0 | 0 | 0 |
A hexatic smectic phase with algebraically decaying bond-orientational order | The hexatic phase predicted by the theories of two-dimensional melting is
characterised by the power law decay of the orientational correlations whereas
the in-layer bond orientational order in all the hexatic smectic phases
observed so far was found to be long-range. We report a hexatic smectic phase
where the in-la... | 0 | 1 | 0 | 0 | 0 | 0 |
Pebble accretion at the origin of water in Europa | Despite the fact that the observed gradient in water content among the
Galilean satellites is globally consistent with a formation in a circum-Jovian
disk on both sides of the snowline, the mechanisms that led to a low water mass
fraction in Europa ($\sim$$8\%$) are not yet understood. Here, we present new
modeling r... | 0 | 1 | 0 | 0 | 0 | 0 |
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting | Traffic forecasting is a particularly challenging application of
spatiotemporal forecasting, due to the complicated spatial dependencies on
roadway networks and the time-varying traffic patterns. To address this
challenge, we learn the traffic network as a graph and propose a novel deep
learning framework, Traffic Gr... | 0 | 0 | 0 | 1 | 0 | 0 |
Intrinsic Analysis of the Sample Fréchet Mean and Sample Mean of Complex Wishart Matrices | We consider two types of averaging of complex covariance matrices, a sample
mean (average) and the sample Fréchet mean. We analyse the performance of
these quantities as estimators for the true covariance matrix via `intrinsic'
versions of bias and mean square error, a methodology which takes account of
geometric str... | 0 | 0 | 1 | 1 | 0 | 0 |
Alternating Optimization for Capacity Region of Gaussian MIMO Broadcast Channels with Per-antenna Power Constraint | This paper characterizes the capacity region of Gaussian MIMO broadcast
channels (BCs) with per-antenna power constraint (PAPC). While the capacity
region of MIMO BCs with a sum power constraint (SPC) was extensively studied,
that under PAPC has received less attention. A reason is that efficient
solutions for this p... | 1 | 0 | 0 | 0 | 0 | 0 |
Tales of Two Cities: Using Social Media to Understand Idiosyncratic Lifestyles in Distinctive Metropolitan Areas | Lifestyles are a valuable model for understanding individuals' physical and
mental lives, comparing social groups, and making recommendations for improving
people's lives. In this paper, we examine and compare lifestyle behaviors of
people living in cities of different sizes, utilizing freely available social
media d... | 1 | 0 | 0 | 0 | 0 | 0 |
Randomized Iterative Reconstruction for Sparse View X-ray Computed Tomography | With the availability of more powerful computers, iterative reconstruction
algorithms are the subject of an ongoing work in the design of more efficient
reconstruction algorithms for X-ray computed tomography. In this work, we show
how two analytical reconstruction algorithms can be improved by correcting the
corresp... | 1 | 0 | 0 | 0 | 0 | 0 |
Finding Local Minima via Stochastic Nested Variance Reduction | We propose two algorithms that can find local minima faster than the
state-of-the-art algorithms in both finite-sum and general stochastic nonconvex
optimization. At the core of the proposed algorithms is
$\text{One-epoch-SNVRG}^+$ using stochastic nested variance reduction (Zhou et
al., 2018a), which outperforms the... | 0 | 0 | 0 | 1 | 0 | 0 |
Growth rate of the state vector in a generalized linear stochastic system with symmetric matrix | The mean growth rate of the state vector is evaluated for a generalized
linear stochastic second-order system with a symmetric matrix. Diagonal entries
of the matrix are assumed to be independent and exponentially distributed with
different means, while the off-diagonal entries are equal to zero.
| 1 | 0 | 0 | 0 | 0 | 0 |
Bayesian Patchworks: An Approach to Case-Based Reasoning | Doctors often rely on their past experience in order to diagnose patients.
For a doctor with enough experience, almost every patient would have
similarities to key cases seen in the past, and each new patient could be
viewed as a mixture of these key past cases. Because doctors often tend to
reason this way, an effic... | 0 | 0 | 0 | 1 | 0 | 0 |
Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models | Machine Learning (ML) and Deep Learning (DL) models have achieved
state-of-the-art performance on multiple learning tasks, from vision to natural
language modelling. With the growing adoption of ML and DL to many areas of
computer science, recent research has also started focusing on the security
properties of these ... | 1 | 0 | 0 | 1 | 0 | 0 |
Formal affine Demazure and Hecke algebras of Kac-Moody root systems | We define the formal affine Demazure algebra and formal affine Hecke algebra
associated to a Kac-Moody root system. We prove the structure theorems of these
algebras, hence, extending several result and construction (presentation in
terms of generators and relations, coproduct and product structures, filtration
by co... | 0 | 0 | 1 | 0 | 0 | 0 |
Handling Homographs in Neural Machine Translation | Homographs, words with different meanings but the same surface form, have
long caused difficulty for machine translation systems, as it is difficult to
select the correct translation based on the context. However, with the advent
of neural machine translation (NMT) systems, which can theoretically take into
account g... | 1 | 0 | 0 | 0 | 0 | 0 |
Simple Length Rigidity for Hitchin Representations | We show that a Hitchin representation is determined by the spectral radii of
the images of simple, non-separating closed curves. As a consequence, we
classify isometries of the intersection function on Hitchin components of
dimension 3 and on the self-dual Hitchin components in all dimensions. As an
important tool in... | 0 | 0 | 1 | 0 | 0 | 0 |
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology | Digital pathology is not only one of the most promising fields of diagnostic
medicine, but at the same time a hot topic for fundamental research. Digital
pathology is not just the transfer of histopathological slides into digital
representations. The combination of different data sources (images, patient
records, and... | 1 | 0 | 0 | 1 | 0 | 0 |
Morse Code Datasets for Machine Learning | We present an algorithm to generate synthetic datasets of tunable difficulty
on classification of Morse code symbols for supervised machine learning
problems, in particular, neural networks. The datasets are spatially
one-dimensional and have a small number of input features, leading to high
density of input informat... | 0 | 0 | 0 | 1 | 0 | 0 |
Guarantees for Spectral Clustering with Fairness Constraints | Given the widespread popularity of spectral clustering (SC) for partitioning
graph data, we study a version of constrained SC in which we try to incorporate
the fairness notion proposed by Chierichetti et al. (2017). According to this
notion, a clustering is fair if every demographic group is approximately
proportion... | 1 | 0 | 0 | 1 | 0 | 0 |
Using Maximum Entry-Wise Deviation to Test the Goodness-of-Fit for Stochastic Block Models | The stochastic block model is widely used for detecting community structures
in network data. How to test the goodness-of-fit of the model is one of the
fundamental problems and has gained growing interests in recent years. In this
paper, we propose a novel goodness-of-fit test based on the maximum entry of
the cente... | 0 | 0 | 0 | 1 | 0 | 0 |
Twitter and the Press: an Ego-Centred Analysis | Ego networks have proved to be a valuable tool for understanding the
relationships that individuals establish with their peers, both in offline and
online social networks. Particularly interesting are the cognitive constraints
associated with the interactions between the ego and the members of their ego
network, wher... | 1 | 0 | 0 | 0 | 0 | 0 |
Majorana quasiparticles in condensed matter | In the space of less than one decade, the search for Majorana quasiparticles
in condensed matter has become one of the hottest topics in physics. The aim of
this review is to provide a brief perspective of where we are with strong focus
on artificial implementations of one-dimensional topological superconductivity.
A... | 0 | 1 | 0 | 0 | 0 | 0 |
Proper orthogonal decomposition vs. Fourier analysis for extraction of large-scale structures of thermal convection | We performed a comparative study of extraction of large-scale flow structures
in Rayleigh Bénard convection using proper orthogonal decomposition (POD) and
{\em Fourier analysis}. We show that the free-slip basis functions capture the
flow profiles successfully for the no-slip boundary conditions. We observe that
the... | 0 | 1 | 0 | 0 | 0 | 0 |
On Gromov--Witten invariants of $\mathbb{P}^1$ | We propose a conjectural explicit formula of generating series of a new type
for Gromov--Witten invariants of $\mathbb{P}^1$ of all degrees in full genera.
| 0 | 1 | 1 | 0 | 0 | 0 |
Downwash-Aware Trajectory Planning for Large Quadrotor Teams | We describe a method for formation-change trajectory planning for large
quadrotor teams in obstacle-rich environments. Our method decomposes the
planning problem into two stages: a discrete planner operating on a graph
representation of the workspace, and a continuous refinement that converts the
non-smooth graph pla... | 1 | 0 | 0 | 0 | 0 | 0 |
Flow simulation in a 2D bubble column with the Euler-Lagrange and Euler-Euler method | Bubbly flows, as present in bubble column reactors, can be simulated using a
variety of simulation techniques. In order to gain high resolution CFD methods
are used to simulate a pseudo 2D bubble column using EL and EE techniques. The
forces on bubble dynamics are solved within open access software OpenFOAM with
bubb... | 0 | 1 | 0 | 0 | 0 | 0 |
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient | In this paper, we study the problem of sampling from a given probability
density function that is known to be smooth and strongly log-concave. We
analyze several methods of approximate sampling based on discretizations of the
(highly overdamped) Langevin diffusion and establish guarantees on its error
measured in the... | 1 | 0 | 1 | 1 | 0 | 0 |
Attacking the Madry Defense Model with $L_1$-based Adversarial Examples | The Madry Lab recently hosted a competition designed to test the robustness
of their adversarially trained MNIST model. Attacks were constrained to perturb
each pixel of the input image by a scaled maximal $L_\infty$ distortion
$\epsilon$ = 0.3. This discourages the use of attacks which are not optimized
on the $L_\i... | 1 | 0 | 0 | 1 | 0 | 0 |
Quantum sensors for the generating functional of interacting quantum field theories | Difficult problems described in terms of interacting quantum fields evolving
in real time or out of equilibrium are abound in condensed-matter and
high-energy physics. Addressing such problems via controlled experiments in
atomic, molecular, and optical physics would be a breakthrough in the field of
quantum simulati... | 0 | 1 | 0 | 0 | 0 | 0 |
Sockeye: A Toolkit for Neural Machine Translation | We describe Sockeye (version 1.12), an open-source sequence-to-sequence
toolkit for Neural Machine Translation (NMT). Sockeye is a production-ready
framework for training and applying models as well as an experimental platform
for researchers. Written in Python and built on MXNet, the toolkit offers
scalable training... | 1 | 0 | 0 | 1 | 0 | 0 |
Bayesian shape modelling of cross-sectional geological data | Shape information is of great importance in many applications. For example,
the oil-bearing capacity of sand bodies, the subterranean remnants of ancient
rivers, is related to their cross-sectional shapes. The analysis of these
shapes is therefore of some interest, but current classifications are
simplistic and ad ho... | 0 | 0 | 0 | 1 | 0 | 0 |
Analysing Relations involving small number of Monomials in AES S- Box | In the present day, AES is one the most widely used and most secure
Encryption Systems prevailing. So, naturally lots of research work is going on
to mount a significant attack on AES. Many different forms of Linear and
differential cryptanalysis have been performed on AES. Of late, an active area
of research has bee... | 1 | 0 | 0 | 0 | 0 | 0 |
q-Virasoro algebra and affine Kac-Moody Lie algebras | We establish a natural connection of the $q$-Virasoro algebra $D_{q}$
introduced by Belov and Chaltikian with affine Kac-Moody Lie algebras. More
specifically, for each abelian group $S$ together with a one-to-one linear
character $\chi$, we define an infinite-dimensional Lie algebra $D_{S}$ which
reduces to $D_{q}$ ... | 0 | 0 | 1 | 0 | 0 | 0 |
The Noise Handling Properties of the Talbot Algorithm for Numerically Inverting the Laplace Transform | This paper examines the noise handling properties of three of the most widely
used algorithms for numerically inverting the Laplace Transform. After
examining the genesis of the algorithms, the regularization properties are
evaluated through a series of standard test functions in which noise is added
to the inverse t... | 0 | 0 | 1 | 0 | 0 | 0 |
Short-term Motion Prediction of Traffic Actors for Autonomous Driving using Deep Convolutional Networks | Despite its ubiquity in our daily lives, AI is only just starting to make
advances in what may arguably have the largest societal impact thus far, the
nascent field of autonomous driving. In this work we discuss this important
topic and address one of crucial aspects of the emerging area, the problem of
predicting fu... | 1 | 0 | 0 | 1 | 0 | 0 |
Tropicalization, symmetric polynomials, and complexity | D. Grigoriev-G. Koshevoy recently proved that tropical Schur polynomials have
(at worst) polynomial tropical semiring complexity. They also conjectured
tropical skew Schur polynomials have at least exponential complexity; we
establish a polynomial complexity upper bound. Our proof uses results about
(stable) Schubert... | 1 | 0 | 0 | 0 | 0 | 0 |
The normal closure of big Dehn twists, and plate spinning with rotating families | We study the normal closure of a big power of one or several Dehn twists in a
Mapping Class Group. We prove that it has a presentation whose relators
consists only of commutators between twists of disjoint support, thus answering
a question of Ivanov. Our method is to use the theory of projection complexes
of Bestvin... | 0 | 0 | 1 | 0 | 0 | 0 |
Secure Minimum Time Planning Under Environmental Uncertainty: an Extended Treatment | Cyber Physical Systems (CPS) are becoming ubiquitous and affect the physical
world, yet security is seldom at the forefront of their design. This is
especially true of robotic control algorithms which seldom consider the effect
of a cyber attack on mission objectives and success. This work presents a
secure optimal c... | 1 | 0 | 0 | 0 | 0 | 0 |
Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions | Treatment effects can be estimated from observational data as the difference
in potential outcomes. In this paper, we address the challenge of estimating
the potential outcome when treatment-dose levels can vary continuously over
time. Further, the outcome variable may not be measured at a regular frequency.
Our prop... | 1 | 0 | 0 | 1 | 0 | 0 |
Reduced Electron Exposure for Energy-Dispersive Spectroscopy using Dynamic Sampling | Analytical electron microscopy and spectroscopy of biological specimens,
polymers, and other beam sensitive materials has been a challenging area due to
irradiation damage. There is a pressing need to develop novel imaging and
spectroscopic imaging methods that will minimize such sample damage as well as
reduce the d... | 1 | 0 | 0 | 0 | 0 | 0 |
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates | We consider the problem of global optimization of an unknown non-convex
smooth function with zeroth-order feedback. In this setup, an algorithm is
allowed to adaptively query the underlying function at different locations and
receives noisy evaluations of function values at the queried points (i.e. the
algorithm has ... | 0 | 0 | 0 | 1 | 0 | 0 |
Raw Waveform-based Speech Enhancement by Fully Convolutional Networks | This study proposes a fully convolutional network (FCN) model for raw
waveform-based speech enhancement. The proposed system performs speech
enhancement in an end-to-end (i.e., waveform-in and waveform-out) manner, which
dif-fers from most existing denoising methods that process the magnitude
spectrum (e.g., log powe... | 1 | 0 | 0 | 1 | 0 | 0 |
Kinetic Theory for Finance Brownian Motion from Microscopic Dynamics | Recent technological development has enabled researchers to study social
phenomena scientifically in detail and financial markets has particularly
attracted physicists since the Brownian motion has played the key role as in
physics. In our previous report (arXiv:1703.06739; to appear in Phys. Rev.
Lett.), we have pre... | 0 | 0 | 0 | 0 | 0 | 1 |
Assessing Uncertainties in X-ray Single-particle Three-dimensional reconstructions | Modern technology for producing extremely bright and coherent X-ray laser
pulses provides the possibility to acquire a large number of diffraction
patterns from individual biological nanoparticles, including proteins, viruses,
and DNA. These two-dimensional diffraction patterns can be practically
reconstructed and re... | 1 | 1 | 0 | 1 | 0 | 0 |
Learning Hawkes Processes from Short Doubly-Censored Event Sequences | Many real-world applications require robust algorithms to learn point
processes based on a type of incomplete data --- the so-called short
doubly-censored (SDC) event sequences. We study this critical problem of
quantitative asynchronous event sequence analysis under the framework of Hawkes
processes by leveraging th... | 0 | 0 | 1 | 1 | 0 | 0 |
Unveiling the Role of Dopant Polarity on the Recombination, and Performance of Organic Light-Emitting Diodes | The recombination of charges is an important process in organic photonic
devices because the process influences the device characteristics such as the
driving voltage, efficiency and lifetime. By combining the dipole trap theory
with the drift-diffusion model, we report that the stationary dipole moment
({\mu}0) of t... | 0 | 1 | 0 | 0 | 0 | 0 |
Sliced Wasserstein Distance for Learning Gaussian Mixture Models | Gaussian mixture models (GMM) are powerful parametric tools with many
applications in machine learning and computer vision. Expectation maximization
(EM) is the most popular algorithm for estimating the GMM parameters. However,
EM guarantees only convergence to a stationary point of the log-likelihood
function, which... | 1 | 0 | 0 | 1 | 0 | 0 |
How constant shifts affect the zeros of certain rational harmonic functions | We study the effect of constant shifts on the zeros of rational harmomic
functions $f(z) = r(z) - \conj{z}$. In particular, we characterize how shifting
through the caustics of $f$ changes the number of zeros and their respective
orientations. This also yields insight into the nature of the singular zeros of
$f$. Our... | 0 | 1 | 1 | 0 | 0 | 0 |
Discovery and usage of joint attention in images | Joint visual attention is characterized by two or more individuals looking at
a common target at the same time. The ability to identify joint attention in
scenes, the people involved, and their common target, is fundamental to the
understanding of social interactions, including others' intentions and goals.
In this w... | 1 | 0 | 0 | 0 | 1 | 0 |
Singular p-Laplacian parabolic system in exterior domains: higher regularity of solutions and related properties of extinction and asymptotic behavior in time | We consider the IBVP in exterior domains for the p-Laplacian parabolic
system. We prove regularity up to the boundary, extinction properties for p \in
( 2n/(n+2) , 2n/(n+1) ) and exponential decay for p= 2n/(n+1) .
| 0 | 0 | 1 | 0 | 0 | 0 |
Size distribution of galaxies in SDSS DR7: weak dependence on halo environment | Using a sample of galaxies selected from the Sloan Digital Sky Survey Data
Release 7 (SDSS DR7) and a catalog of bulge-disk decompositions, we study how
the size distribution of galaxies depends on the intrinsic properties of
galaxies, such as concentration, morphology, specific star formation rate
(sSFR), and bulge ... | 0 | 1 | 0 | 0 | 0 | 0 |
Towards thinner convolutional neural networks through Gradually Global Pruning | Deep network pruning is an effective method to reduce the storage and
computation cost of deep neural networks when applying them to resource-limited
devices. Among many pruning granularities, neuron level pruning will remove
redundant neurons and filters in the model and result in thinner networks. In
this paper, we... | 1 | 0 | 0 | 0 | 0 | 0 |
Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars | We propose a systematic learning-based approach to the generation of massive
quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D
images thereof, with associated ground truth information, for the purposes of
training, benchmarking, and diagnosing learning-based computer vision and
robotics alg... | 1 | 0 | 0 | 1 | 0 | 0 |
Multiband NFC for High-Throughput Wireless Computer Vision Sensor Network | Vision sensors lie in the heart of computer vision. In many computer vision
applications, such as AR/VR, non-contacting near-field communication (NFC) with
high throughput is required to transfer information to algorithms. In this
work, we proposed a novel NFC system which utilizes multiple frequency bands to
achieve... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning Rare Word Representations using Semantic Bridging | We propose a methodology that adapts graph embedding techniques (DeepWalk
(Perozzi et al., 2014) and node2vec (Grover and Leskovec, 2016)) as well as
cross-lingual vector space mapping approaches (Least Squares and Canonical
Correlation Analysis) in order to merge the corpus and ontological sources of
lexical knowled... | 1 | 0 | 0 | 0 | 0 | 0 |
Effect of annealing temperatures on the electrical conductivity and dielectric properties of Ni1.5Fe1.5O4 spinel ferrite prepared by chemical reaction at different pH values | The electrical conductivity and dielectric properties of Ni1.5Fe1.5O4 ferrite
has been controlled by varying the annealing temperature of the chemical routed
samples. The frequency activated conductivity obeyed Jonschers power law and
universal scaling suggested semiconductor nature. An unusual metal like state
has b... | 0 | 1 | 0 | 0 | 0 | 0 |
Molecular dynamic simulation of water vapor interaction with blind pore of dead-end and saccate type | One of the varieties of pores, often found in natural or artificial building
materials, are the so-called blind pores of dead-end or saccate type.
Three-dimensional model of such kind of pore has been developed in this work.
This model has been used for simulation of water vapor interaction with
individual pore by mo... | 1 | 1 | 0 | 0 | 0 | 0 |
Learning Program Component Order | Successful programs are written to be maintained. One aspect to this is that
programmers order the components in the code files in a particular way. This is
part of programming style. While the conventions for ordering are sometimes
given as part of a style guideline, such guidelines are often incomplete and
programm... | 1 | 0 | 0 | 0 | 0 | 0 |
Random Euler Complex-Valued Nonlinear Filters | Over the last decade, both the neural network and kernel adaptive filter have
successfully been used for nonlinear signal processing. However, they suffer
from high computational cost caused by their complex/growing network
structures. In this paper, we propose two random Euler filters for
complex-valued nonlinear fi... | 0 | 0 | 0 | 1 | 0 | 0 |
Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model | Memory has a great impact on the evolution of every process related to human
societies. Among them, the evolution of an epidemic is directly related to the
individuals' experiences. Indeed, any real epidemic process is clearly
sustained by a non-Markovian dynamics: memory effects play an essential role in
the spreadi... | 0 | 1 | 0 | 0 | 0 | 0 |
On the equivalence of Eulerian and Lagrangian variables for the two-component Camassa-Holm system | The Camassa-Holm equation and its two-component Camassa-Holm system
generalization both experience wave breaking in finite time. To analyze this,
and to obtain solutions past wave breaking, it is common to reformulate the
original equation given in Eulerian coordinates, into a system of ordinary
differential equation... | 0 | 0 | 1 | 0 | 0 | 0 |
Bulk diffusion in a kinetically constrained lattice gas | In the hydrodynamic regime, the evolution of a stochastic lattice gas with
symmetric hopping rules is described by a diffusion equation with
density-dependent diffusion coefficient encapsulating all microscopic details
of the dynamics. This diffusion coefficient is, in principle, determined by a
Green-Kubo formula. I... | 0 | 1 | 0 | 0 | 0 | 0 |
Censored pairwise likelihood-based tests for mixing coefficient of spatial max-mixture models | Max-mixture processes are defined as Z = max(aX, (1 -- a)Y) with X an
asymptotic dependent (AD) process, Y an asymptotic independent (AI) process and
a $\in$ [0, 1]. So that, the mixing coefficient a may reveal the strength of
the AD part present in the max-mixture process. In this paper we focus on two
tests based o... | 0 | 0 | 1 | 1 | 0 | 0 |
From rate distortion theory to metric mean dimension: variational principle | The purpose of this paper is to point out a new connection between
information theory and dynamical systems. In the information theory side, we
consider rate distortion theory, which studies lossy data compression of
stochastic processes under distortion constraints. In the dynamical systems
side, we consider mean di... | 1 | 0 | 1 | 0 | 0 | 0 |
Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks | Quantized Neural Networks (QNNs), which use low bitwidth numbers for
representing parameters and performing computations, have been proposed to
reduce the computation complexity, storage size and memory usage. In QNNs,
parameters and activations are uniformly quantized, such that the
multiplications and additions can... | 1 | 0 | 0 | 0 | 0 | 0 |
The Causal Frame Problem: An Algorithmic Perspective | The Frame Problem (FP) is a puzzle in philosophy of mind and epistemology,
articulated by the Stanford Encyclopedia of Philosophy as follows: "How do we
account for our apparent ability to make decisions on the basis only of what is
relevant to an ongoing situation without having explicitly to consider all that
is no... | 1 | 0 | 0 | 1 | 0 | 0 |
A Visual Representation of Wittgenstein's Tractatus Logico-Philosophicus | In this paper we present a data visualization method together with its
potential usefulness in digital humanities and philosophy of language. We
compile a multilingual parallel corpus from different versions of
Wittgenstein's Tractatus Logico-Philosophicus, including the original in German
and translations into Engli... | 1 | 0 | 0 | 0 | 0 | 0 |
Primordial perturbations generated by Higgs field and $R^2$ operator | If the very early Universe is dominated by the non-minimally coupled Higgs
field and Starobinsky's curvature-squared term together, the potential diagram
would mimic the landscape of a valley, serving as a cosmological attractor. The
inflationary dynamics along this valley is studied, model parameters are
constrained... | 0 | 1 | 0 | 0 | 0 | 0 |
Schubert polynomials, theta and eta polynomials, and Weyl group invariants | We examine the relationship between the (double) Schubert polynomials of
Billey-Haiman and Ikeda-Mihalcea-Naruse and the (double) theta and eta
polynomials of Buch-Kresch-Tamvakis and Wilson from the perspective of Weyl
group invariants. We obtain generators for the kernel of the natural map from
the corresponding ri... | 0 | 0 | 1 | 0 | 0 | 0 |
Massive Fields as Systematics for Single Field Inflation | During inflation, massive fields can contribute to the power spectrum of
curvature perturbation via a dimension-5 operator. This contribution can be
considered as a bias for the program of using $n_s$ and $r$ to select inflation
models. Even the dimension-5 operator is suppressed by $\Lambda = M_p$, there
is still a ... | 0 | 1 | 0 | 0 | 0 | 0 |
The second boundary value problem of the prescribed affine mean curvature equation and related linearized Monge-Ampère equation | These lecture notes are concerned with the solvability of the second boundary
value problem of the prescribed affine mean curvature equation and related
regularity theory of the Monge-Ampère and linearized Monge-Ampère
equations. The prescribed affine mean curvature equation is a fully nonlinear,
fourth order, geomet... | 0 | 0 | 1 | 0 | 0 | 0 |
Additive Combinatorics: A Menu of Research Problems | This text contains over three hundred specific open questions on various
topics in additive combinatorics, each placed in context by reviewing all
relevant results. While the primary purpose is to provide an ample supply of
problems for student research, it is hopefully also useful for a wider
audience. It is the aut... | 0 | 0 | 1 | 0 | 0 | 0 |
NMR evidence for static local nematicity and its cooperative interplay with low-energy magnetic fluctuations in FeSe under pressure | We present $^{77}$Se-NMR measurements on single-crystalline FeSe under
pressures up to 2 GPa. Based on the observation of the splitting and broadening
of the NMR spectrum due to structural twin domains, we discovered that static,
local nematic ordering exists well above the bulk nematic ordering temperature,
$T_{\rm ... | 0 | 1 | 0 | 0 | 0 | 0 |
LitStoryTeller: An Interactive System for Visual Exploration of Scientific Papers Leveraging Named entities and Comparative Sentences | The present study proposes LitStoryTeller, an interactive system for visually
exploring the semantic structure of a scientific article. We demonstrate how
LitStoryTeller could be used to answer some of the most fundamental research
questions, such as how a new method was built on top of existing methods, based
on wha... | 1 | 0 | 0 | 0 | 0 | 0 |
Acoustic Metacages for Omnidirectional Sound Shielding | Conventional sound shielding structures typically prevent fluid transport
between the exterior and interior. A design of a two-dimensional acoustic
metacage with subwavelength thickness which can shield acoustic waves from all
directions while allowing steady fluid flow is presented in this paper. The
structure is de... | 0 | 1 | 0 | 0 | 0 | 0 |
Concave losses for robust dictionary learning | Traditional dictionary learning methods are based on quadratic convex loss
function and thus are sensitive to outliers. In this paper, we propose a
generic framework for robust dictionary learning based on concave losses. We
provide results on composition of concave functions, notably regarding
super-gradient computa... | 1 | 0 | 0 | 1 | 0 | 0 |
Target-Quality Image Compression with Recurrent, Convolutional Neural Networks | We introduce a stop-code tolerant (SCT) approach to training recurrent
convolutional neural networks for lossy image compression. Our methods
introduce a multi-pass training method to combine the training goals of
high-quality reconstructions in areas around stop-code masking as well as in
highly-detailed areas. Thes... | 1 | 0 | 0 | 0 | 0 | 0 |
Embedding simply connected 2-complexes in 3-space -- IV. Dual matroids | We introduce dual matroids of 2-dimensional simplicial complexes. Under
certain necessary conditions, duals matroids are used to characterise
embeddability in 3-space in a way analogous to Whitney's planarity criterion.
We further use dual matroids to extend a 3-dimensional analogue of
Kuratowski's theorem to the cla... | 0 | 0 | 1 | 0 | 0 | 0 |
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