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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Symmetric Variational Autoencoder and Connections to Adversarial Learning | A new form of the variational autoencoder (VAE) is proposed, based on the
symmetric Kullback-Leibler divergence. It is demonstrated that learning of the
resulting symmetric VAE (sVAE) has close connections to previously developed
adversarial-learning methods. This relationship helps unify the previously
distinct tech... | 0 | 0 | 0 | 1 | 0 | 0 |
Matrix Product Unitaries: Structure, Symmetries, and Topological Invariants | Matrix Product Vectors form the appropriate framework to study and classify
one-dimensional quantum systems. In this work, we develop the structure theory
of Matrix Product Unitary operators (MPUs) which appear e.g. in the description
of time evolutions of one-dimensional systems. We prove that all MPUs have a
strict... | 0 | 1 | 0 | 0 | 0 | 0 |
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning | Deep Learning has recently become hugely popular in machine learning,
providing significant improvements in classification accuracy in the presence
of highly-structured and large databases.
Researchers have also considered privacy implications of deep learning.
Models are typically trained in a centralized manner wit... | 1 | 0 | 0 | 1 | 0 | 0 |
A. G. W. Cameron 1925-2005, Biographical Memoir, National Academy of Sciences | Alastair Graham Walker Cameron was an astrophysicist and planetary scientist
of broad interests and exceptional originality. A founder of the field of
nuclear astrophysics, he developed the theoretical understanding of the
chemical elementsâ origins and made pioneering connections between the
abundances of elements... | 0 | 1 | 0 | 0 | 0 | 0 |
Realization of "Time Crystal" Lagrangians and Emergent Sisyphus Dynamics | We demonstrate how non-convex "time crystal" Lagrangians arise in the
effective description of conventional, realizable physical systems. Such
embeddings allow for the resolution of dynamical singularities that arise in
the reduced description. Sisyphus dynamics, featuring intervals of forward
motion interrupted by q... | 0 | 1 | 0 | 0 | 0 | 0 |
Gradient Normalization & Depth Based Decay For Deep Learning | In this paper we introduce a novel method of gradient normalization and decay
with respect to depth. Our method leverages the simple concept of normalizing
all gradients in a deep neural network, and then decaying said gradients with
respect to their depth in the network. Our proposed normalization and decay
techniqu... | 1 | 0 | 0 | 1 | 0 | 0 |
CARET analysis of multithreaded programs | Dynamic Pushdown Networks (DPNs) are a natural model for multithreaded
programs with (recursive) procedure calls and thread creation. On the other
hand, CARET is a temporal logic that allows to write linear temporal formulas
while taking into account the matching between calls and returns. We consider
in this paper t... | 1 | 0 | 0 | 0 | 0 | 0 |
Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo data | A new approach of solving the ill-conditioned inverse problem for analytical
continuation is proposed. The root of the problem lies in the fact that even
tiny noise of imaginary-time input data has a serious impact on the inferred
real-frequency spectra. By means of a modern regularization technique, we
eliminate red... | 0 | 1 | 0 | 1 | 0 | 0 |
Distral: Robust Multitask Reinforcement Learning | Most deep reinforcement learning algorithms are data inefficient in complex
and rich environments, limiting their applicability to many scenarios. One
direction for improving data efficiency is multitask learning with shared
neural network parameters, where efficiency may be improved through transfer
across related t... | 1 | 0 | 0 | 1 | 0 | 0 |
Finding the number density of atomic vapor by studying its absorption profile | We demonstrate a technique for obtaining the density of atomic vapor, by
doing a fit of the resonant absorption spectrum to a density-matrix model. In
order to demonstrate the usefulness of the technique, we apply it to absorption
in the ${\rm D_2}$ line of a Cs vapor cell at room temperature. The lineshape
of the sp... | 0 | 1 | 0 | 0 | 0 | 0 |
Rigidity for von Neumann algebras given by locally compact groups and their crossed products | We prove the first rigidity and classification theorems for crossed product
von Neumann algebras given by actions of non-discrete, locally compact groups.
We prove that for arbitrary free probability measure preserving actions of
connected simple Lie groups of real rank one, the crossed product has a unique
Cartan su... | 0 | 0 | 1 | 0 | 0 | 0 |
Quantum Singwi-Tosi-Land-Sjoelander approach for interacting inhomogeneous systems under electromagnetic fields: Comparison with exact results | For inhomogeneous interacting electronic systems under a time-dependent
electromagnetic perturbation, we derive the linear equation for response
functions in a quantum mechanical manner. It is a natural extension of the
original semi-classical Singwi-Tosi-Land-Sjoelander (STLS) approach for an
electron gas. The facto... | 0 | 1 | 0 | 0 | 0 | 0 |
3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures | This paper analyzes the use of 3D Convolutional Neural Networks for brain
tumor segmentation in MR images. We address the problem using three different
architectures that combine fine and coarse features to obtain the final
segmentation. We compare three different networks that use multi-resolution
features in terms ... | 0 | 0 | 0 | 1 | 0 | 0 |
Learning Random Fourier Features by Hybrid Constrained Optimization | The kernel embedding algorithm is an important component for adapting kernel
methods to large datasets. Since the algorithm consumes a major computation
cost in the testing phase, we propose a novel teacher-learner framework of
learning computation-efficient kernel embeddings from specific data. In the
framework, the... | 1 | 0 | 0 | 1 | 0 | 0 |
Min-max formulas and other properties of certain classes of nonconvex effective Hamiltonians | This paper is the first attempt to systematically study properties of the
effective Hamiltonian $\overline{H}$ arising in the periodic homogenization of
some coercive but nonconvex Hamilton-Jacobi equations. Firstly, we introduce a
new and robust decomposition method to obtain min-max formulas for a class of
nonconve... | 0 | 0 | 1 | 0 | 0 | 0 |
The Prescribed Ricci Curvature Problem on Homogeneous Spaces with Intermediate Subgroups | Consider a compact Lie group $G$ and a closed subgroup $H<G$. Suppose
$\mathcal M$ is the set of $G$-invariant Riemannian metrics on the homogeneous
space $M=G/H$. We obtain a sufficient condition for the existence of
$g\in\mathcal M$ and $c>0$ such that the Ricci curvature of $g$ equals $cT$ for
a given $T\in\mathca... | 0 | 0 | 1 | 0 | 0 | 0 |
Solving Boundary Value Problem for a Nonlinear Stationary Controllable System with Synthesizing Control | An algorithm for constructing a control function that transfers a wide class
of stationary nonlinear systems of ordinary differential equations from an
initial state to a final state under certain control restrictions is proposed.
The algorithm is designed to be convenient for numerical implementation. A
constructive... | 0 | 0 | 1 | 0 | 0 | 0 |
Modelling and prediction of financial trading networks: An application to the NYMEX natural gas futures market | Over the last few years there has been a growing interest in using financial
trading networks to understand the microstructure of financial markets. Most of
the methodologies developed so far for this purpose have been based on the
study of descriptive summaries of the networks such as the average node degree
and the... | 0 | 0 | 0 | 1 | 0 | 0 |
A comparative study of fairness-enhancing interventions in machine learning | Computers are increasingly used to make decisions that have significant
impact in people's lives. Often, these predictions can affect different
population subgroups disproportionately. As a result, the issue of fairness has
received much recent interest, and a number of fairness-enhanced classifiers
and predictors ha... | 0 | 0 | 0 | 1 | 0 | 0 |
Predicting Opioid Relapse Using Social Media Data | Opioid addiction is a severe public health threat in the U.S, causing massive
deaths and many social problems. Accurate relapse prediction is of practical
importance for recovering patients since relapse prediction promotes timely
relapse preventions that help patients stay clean. In this paper, we introduce
a Genera... | 1 | 0 | 0 | 0 | 0 | 0 |
Self-Trapping of G-Mode Oscillations in Relativistic Thin Disks, Revisited | We examine by a perturbation method how the self-trapping of g-mode
oscillations in geometrically thin relativistic disks is affected by uniform
vertical magnetic fields. Disks which we consider are isothermal in the
vertical direction, but are truncated at a certain height by presence of hot
coronae. We find that th... | 0 | 1 | 0 | 0 | 0 | 0 |
Computable geometric complex analysis and complex dynamics | We discuss computability and computational complexity of conformal mappings
and their boundary extensions. As applications, we review the state of the art
regarding computability and complexity of Julia sets, their invariant measures
and external rays impressions.
| 0 | 0 | 1 | 0 | 0 | 0 |
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes | Estimating the 6D pose of known objects is important for robots to interact
with the real world. The problem is challenging due to the variety of objects
as well as the complexity of a scene caused by clutter and occlusions between
objects. In this work, we introduce PoseCNN, a new Convolutional Neural Network
for 6D... | 1 | 0 | 0 | 0 | 0 | 0 |
MIP Formulations for the Steiner Forest Problem | The Steiner Forest problem is among the fundamental network design problems.
Finding tight linear programming bounds for the problem is the key for both
fast Branch-and-Bound algorithms and good primal-dual approximations. On the
theoretical side, the best known bound can be obtained from an integer program
[KLSv08].... | 1 | 0 | 0 | 0 | 0 | 0 |
Luminescence in germania-silica fibers in 1-2 μm region | We analyze the origins of the luminescence in germania-silica fibers with
high germanium concentration (about 30 mol. % GeO2) in the region 1-2 {\mu}m
with a laser pump at the wavelength 532 nm. We show that such fibers
demonstrate the high level of luminescence which unlikely allows the
observation of photon triplet... | 0 | 1 | 0 | 0 | 0 | 0 |
Boundedness in languages of infinite words | We define a new class of languages of $\omega$-words, strictly extending
$\omega$-regular languages.
One way to present this new class is by a type of regular expressions. The
new expressions are an extension of $\omega$-regular expressions where two new
variants of the Kleene star $L^*$ are added: $L^B$ and $L^S$. T... | 1 | 0 | 0 | 0 | 0 | 0 |
Maximum Regularized Likelihood Estimators: A General Prediction Theory and Applications | Maximum regularized likelihood estimators (MRLEs) are arguably the most
established class of estimators in high-dimensional statistics. In this paper,
we derive guarantees for MRLEs in Kullback-Leibler divergence, a general
measure of prediction accuracy. We assume only that the densities have a convex
parametrizatio... | 0 | 0 | 1 | 1 | 0 | 0 |
Emergent $\mathrm{SU}(4)$ Symmetry in $α$-ZrCl$_3$ and Crystalline Spin-Orbital Liquids | While the enhancement of the spin-space symmetry from the usual
$\mathrm{SU}(2)$ to $\mathrm{SU}(N)$ is promising for finding nontrivial
quantum spin liquids, its realization in magnetic materials remains
challenging. Here we propose a new mechanism by which the $\mathrm{SU}(4)$
symmetry emerges in the strong spin-or... | 0 | 1 | 0 | 0 | 0 | 0 |
Central elements of the Jennings basis and certain Morita invariants | From Morita theoretic viewpoint, computing Morita invariants is important. We
prove that the intersection of the center and the $n$th (right) socle $ZS^n(A)
:= Z(A) \cap \operatorname{Soc}^n(A)$ of a finite-dimensional algebra $A$ is a
Morita invariant; This is a generalization of important Morita invariants ---
the ... | 0 | 0 | 1 | 0 | 0 | 0 |
Linear Disentangled Representation Learning for Facial Actions | Limited annotated data available for the recognition of facial expression and
action units embarrasses the training of deep networks, which can learn
disentangled invariant features. However, a linear model with just several
parameters normally is not demanding in terms of training data. In this paper,
we propose an ... | 1 | 0 | 0 | 1 | 0 | 0 |
ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? | Generating molecules with desired chemical properties is important for drug
discovery. The use of generative neural networks is promising for this task.
However, from visual inspection, it often appears that generated samples lack
diversity. In this paper, we quantify this internal chemical diversity, and we
raise th... | 1 | 0 | 0 | 1 | 0 | 0 |
Nodal domains, spectral minimal partitions, and their relation to Aharonov-Bohm operators | This survey is a short version of a chapter written by the first two authors
in the book [A. Henrot, editor. Shape optimization and spectral theory. Berlin:
De Gruyter, 2017] (where more details and references are given) but we have
decided here to put more emphasis on the role of the Aharonov-Bohm operators
which ap... | 0 | 0 | 1 | 0 | 0 | 0 |
Optimal control of two qubits via a single cavity drive in circuit quantum electrodynamics | Optimization of the fidelity of control operations is of critical importance
in the pursuit of fault-tolerant quantum computation. We apply optimal control
techniques to demonstrate that a single drive via the cavity in circuit quantum
electrodynamics can implement a high-fidelity two-qubit all-microwave gate that
di... | 0 | 1 | 0 | 0 | 0 | 0 |
Modular Representation of Layered Neural Networks | Layered neural networks have greatly improved the performance of various
applications including image processing, speech recognition, natural language
processing, and bioinformatics. However, it is still difficult to discover or
interpret knowledge from the inference provided by a layered neural network,
since its in... | 1 | 0 | 0 | 1 | 0 | 0 |
A Guide to General-Purpose Approximate Bayesian Computation Software | This Chapter, "A Guide to General-Purpose ABC Software", is to appear in the
forthcoming Handbook of Approximate Bayesian Computation (2018). We present
general-purpose software to perform Approximate Bayesian Computation (ABC) as
implemented in the R-packages abc and EasyABC and the c++ program ABCtoolbox.
With simp... | 0 | 0 | 0 | 1 | 0 | 0 |
Feature Selection Facilitates Learning Mixtures of Discrete Product Distributions | Feature selection can facilitate the learning of mixtures of discrete random
variables as they arise, e.g. in crowdsourcing tasks. Intuitively, not all
workers are equally reliable but, if the less reliable ones could be
eliminated, then learning should be more robust. By analogy with Gaussian
mixture models, we seek... | 1 | 0 | 0 | 1 | 0 | 0 |
3D Human Pose Estimation on a Configurable Bed from a Pressure Image | Robots have the potential to assist people in bed, such as in healthcare
settings, yet bedding materials like sheets and blankets can make observation
of the human body difficult for robots. A pressure-sensing mat on a bed can
provide pressure images that are relatively insensitive to bedding materials.
However, prio... | 1 | 0 | 0 | 0 | 0 | 0 |
Multilingual Hierarchical Attention Networks for Document Classification | Hierarchical attention networks have recently achieved remarkable performance
for document classification in a given language. However, when multilingual
document collections are considered, training such models separately for each
language entails linear parameter growth and lack of cross-language transfer.
Learning... | 1 | 0 | 0 | 0 | 0 | 0 |
The complexity of recognizing minimally tough graphs | Let $t$ be a positive real number. A graph is called $t$-tough, if the
removal of any cutset $S$ leaves at most $|S|/t$ components. The toughness of a
graph is the largest $t$ for which the graph is $t$-tough. A graph is minimally
$t$-tough, if the toughness of the graph is $t$ and the deletion of any edge
from the g... | 1 | 0 | 0 | 0 | 0 | 0 |
Homeostatic plasticity and external input shape neural network dynamics | In vitro and in vivo spiking activity clearly differ. Whereas networks in
vitro develop strong bursts separated by periods of very little spiking
activity, in vivo cortical networks show continuous activity. This is puzzling
considering that both networks presumably share similar single-neuron dynamics
and plasticity... | 0 | 0 | 0 | 0 | 1 | 0 |
How Sensitive are Sensitivity-Based Explanations? | We propose a simple objective evaluation measure for explanations of a
complex black-box machine learning model. While most such model explanations
have largely been evaluated via qualitative measures, such as how humans might
qualitatively perceive the explanations, it is vital to also consider objective
measures su... | 1 | 0 | 0 | 1 | 0 | 0 |
Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions | We present many new results related to reliable (interactive) communication
over insertion-deletion channels. Synchronization errors, such as insertions
and deletions, strictly generalize the usual symbol corruption errors and are
much harder to protect against.
We show how to hide the complications of synchronizatio... | 1 | 0 | 0 | 0 | 0 | 0 |
Learning to Generate Samples from Noise through Infusion Training | In this work, we investigate a novel training procedure to learn a generative
model as the transition operator of a Markov chain, such that, when applied
repeatedly on an unstructured random noise sample, it will denoise it into a
sample that matches the target distribution from the training set. The novel
training p... | 1 | 0 | 0 | 1 | 0 | 0 |
Worst-case vs Average-case Design for Estimation from Fixed Pairwise Comparisons | Pairwise comparison data arises in many domains, including tournament
rankings, web search, and preference elicitation. Given noisy comparisons of a
fixed subset of pairs of items, we study the problem of estimating the
underlying comparison probabilities under the assumption of strong stochastic
transitivity (SST). ... | 1 | 0 | 0 | 1 | 0 | 0 |
Decoupling multivariate polynomials: interconnections between tensorizations | Decoupling multivariate polynomials is useful for obtaining an insight into
the workings of a nonlinear mapping, performing parameter reduction, or
approximating nonlinear functions. Several different tensor-based approaches
have been proposed independently for this task, involving different tensor
representations of... | 0 | 0 | 1 | 0 | 0 | 0 |
Arcades: A deep model for adaptive decision making in voice controlled smart-home | In a voice-controlled smart-home, a controller must respond not only to
user's requests but also according to the interaction context. This paper
describes Arcades, a system which uses deep reinforcement learning to extract
context from a graphical representation of home automation system and to update
continuously i... | 1 | 0 | 0 | 1 | 0 | 0 |
Evolutionary Centrality and Maximal Cliques in Mobile Social Networks | This paper introduces an evolutionary approach to enhance the process of
finding central nodes in mobile networks. This can provide essential
information and important applications in mobile and social networks. This
evolutionary approach considers the dynamics of the network and takes into
consideration the central ... | 1 | 0 | 0 | 0 | 0 | 0 |
Band structure engineered layered metals for low-loss plasmonics | Plasmonics currently faces the problem of seemingly inevitable optical losses
occurring in the metallic components that challenges the implementation of
essentially any application. In this work we show that Ohmic losses are reduced
in certain layered metals, such as the transition metal dichalcogenide TaS$_2$,
due t... | 0 | 1 | 0 | 0 | 0 | 0 |
Acceleration through Optimistic No-Regret Dynamics | We consider the problem of minimizing a smooth convex function by reducing
the optimization to computing the Nash equilibrium of a particular zero-sum
convex-concave game. Zero-sum games can be solved using online learning
dynamics, where a classical technique involves simulating two no-regret
algorithms that play ag... | 0 | 0 | 0 | 1 | 0 | 0 |
A Full Bayesian Model to Handle Structural Ones and Missingness in Economic Evaluations from Individual-Level Data | Economic evaluations from individual-level data are an important component of
the process of technology appraisal, with a view to informing resource
allocation decisions. A critical problem in these analyses is that both
effectiveness and cost data typically present some complexity (e.g. non
normality, spikes and mis... | 0 | 0 | 0 | 1 | 0 | 0 |
Misconceptions about Calorimetry | In the past 50 years, calorimeters have become the most important detectors
in many particle physics experiments, especially experiments in colliding-beam
accelerators at the energy frontier. In this paper, we describe and discuss a
number of common misconceptions about these detectors, as well as the
consequences of... | 0 | 1 | 0 | 0 | 0 | 0 |
Exothermicity is not a necessary condition for enhanced diffusion of enzymes | Recent experiments have revealed that the diffusivity of exothermic and fast
enzymes is enhanced when they are catalytically active, and different physical
mechanisms have been explored and quantified to account for this observation.
We perform measurements on the endothermic and relatively slow enzyme aldolase,
whic... | 0 | 1 | 0 | 0 | 0 | 0 |
Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks | This paper introduces a new approach to automatically quantify the severity
of knee OA using X-ray images. Automatically quantifying knee OA severity
involves two steps: first, automatically localizing the knee joints; next,
classifying the localized knee joint images. We introduce a new approach to
automatically det... | 1 | 0 | 0 | 0 | 0 | 0 |
Data-Driven Filtered Reduced Order Modeling Of Fluid Flows | We propose a data-driven filtered reduced order model (DDF-ROM) framework for
the numerical simulation of fluid flows. The novel DDF-ROM framework consists
of two steps: (i) In the first step, we use explicit ROM spatial filtering of
the nonlinear PDE to construct a filtered ROM. This filtered ROM is
low-dimensional,... | 0 | 1 | 0 | 0 | 0 | 0 |
FEAST Eigensolver for Nonlinear Eigenvalue Problems | The linear FEAST algorithm is a method for solving linear eigenvalue
problems. It uses complex contour integration to calculate the eigenvectors
whose eigenvalues that are located inside some user-defined region in the
complex plane. This makes it possible to parallelize the process of solving
eigenvalue problems by ... | 1 | 0 | 0 | 0 | 0 | 0 |
Twin Primes In Quadratic Arithmetic Progressions | A recent heuristic argument based on basic concepts in spectral analysis
showed that the twin prime conjecture and a few other related primes counting
problems are valid. A rigorous version of the spectral method, and a proof for
the existence of infinitely many quadratic twin primes $n^{2}+1$ and $n^{2}+3$,
$n \geq ... | 0 | 0 | 1 | 0 | 0 | 0 |
Bit Complexity of Computing Solutions for Symmetric Hyperbolic Systems of PDEs with Guaranteed Precision | We establish upper bounds of bit complexity of computing solution operators
for symmetric hyperbolic systems of PDEs. Here we continue the research started
in in our revious publications where computability, in the rigorous sense of
computable analysis, has been established for solution operators of Cauchy and
dissip... | 1 | 0 | 0 | 0 | 0 | 0 |
Relativistic corrections for the ground electronic state of molecular hydrogen | We recalculate the leading relativistic corrections for the ground electronic
state of the hydrogen molecule using variational method with explicitly
correlated functions which satisfy the interelectronic cusp condition. The new
computational approach allowed for the control of the numerical precision which
reached a... | 0 | 1 | 0 | 0 | 0 | 0 |
Homogenization in Perforated Domains and Interior Lipschitz Estimates | We establish interior Lipschitz estimates at the macroscopic scale for
solutions to systems of linear elasticity with rapidly oscillating periodic
coefficients and mixed boundary conditions in domains periodically perforated
at a microscopic scale $\varepsilon$ by establishing $H^1$-convergence rates
for such solutio... | 0 | 0 | 1 | 0 | 0 | 0 |
Opinion-Based Centrality in Multiplex Networks: A Convex Optimization Approach | Most people simultaneously belong to several distinct social networks, in
which their relations can be different. They have opinions about certain
topics, which they share and spread on these networks, and are influenced by
the opinions of other persons. In this paper, we build upon this observation to
propose a new ... | 1 | 1 | 0 | 0 | 0 | 0 |
FDTD: solving 1+1D delay PDE in parallel | We present a proof of concept for solving a 1+1D complex-valued, delay
partial differential equation (PDE) that emerges in the study of waveguide
quantum electrodynamics (QED) by adapting the finite-difference time-domain
(FDTD) method. The delay term is spatially non-local, rendering conventional
approaches such as ... | 1 | 1 | 0 | 0 | 0 | 0 |
Optimal Installation for Electric Vehicle Wireless Charging Lanes | Range anxiety, the persistent worry about not having enough battery power to
complete a trip, remains one of the major obstacles to widespread
electric-vehicle adoption. As cities look to attract more users to adopt
electric vehicles, the emergence of wireless in-motion car charging technology
presents itself as a so... | 0 | 0 | 1 | 0 | 0 | 0 |
Improved Fixed-Rank Nyström Approximation via QR Decomposition: Practical and Theoretical Aspects | The Nyström method is a popular technique for computing fixed-rank
approximations of large kernel matrices using a small number of landmark
points. In practice, to ensure high quality approximations, the number of
landmark points is chosen to be greater than the target rank. However, the
standard Nyström method uses ... | 1 | 0 | 0 | 1 | 0 | 0 |
Population splitting of rodlike swimmers in Couette flow | We present a quantitative analysis on the response of a dilute active
suspension of self-propelled rods (swimmers) in a planar channel subjected to
an imposed shear flow. To best capture the salient features of shear-induced
effects, we consider the case of an imposed Couette flow, providing a constant
shear rate acr... | 0 | 1 | 0 | 0 | 0 | 0 |
MultiAmdahl: Optimal Resource Allocation in Heterogeneous Architectures | Future multiprocessor chips will integrate many different units, each
tailored to a specific computation. When designing such a system, the chip
architect must decide how to distribute limited system resources such as area,
power, and energy among the computational units. We extend MultiAmdahl, an
analytical optimiza... | 1 | 0 | 0 | 0 | 0 | 0 |
Coset Vertex Operator Algebras and $\W$-Algebras | We give an explicit description for the weight three generator of the coset
vertex operator algebra $C_{L_{\widehat{\sl_{n}}}(l,0)\otimes
L_{\widehat{\sl_{n}}}(1,0)}(L_{\widehat{\sl_{n}}}(l+1,0))$, for $n\geq 2, l\geq
1$. Furthermore, we prove that the commutant
$C_{L_{\widehat{\sl_{3}}}(l,0)\otimes
L_{\widehat{\sl_{... | 0 | 0 | 1 | 0 | 0 | 0 |
The Moore and the Myhill Property For Strongly Irreducible Subshifts Of Finite Type Over Group Sets | We prove the Moore and the Myhill property for strongly irreducible subshifts
over right amenable and finitely right generated left homogeneous spaces with
finite stabilisers. Both properties together mean that the global transition
function of each big-cellular automaton with finite set of states and finite
neighbou... | 1 | 0 | 1 | 0 | 0 | 0 |
eSource for clinical trials: Implementation and evaluation of a standards-based approach in a real world trial | Objective: The Learning Health System (LHS) requires integration of research
into routine practice. eSource or embedding clinical trial functionalities into
routine electronic health record (EHR) systems has long been put forward as a
solution to the rising costs of research. We aimed to create and validate an
eSourc... | 1 | 0 | 0 | 0 | 0 | 0 |
SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules | Simplified Molecular Input Line Entry System (SMILES) is a single line text
representation of a unique molecule. One molecule can however have multiple
SMILES strings, which is a reason that canonical SMILES have been defined,
which ensures a one to one correspondence between SMILES string and molecule.
Here the fact... | 1 | 0 | 0 | 0 | 0 | 0 |
Binary Tomography Reconstructions With Few Projections | We approach the tomographic problem in terms of linear system of equations
$A\mathbf{x}=\mathbf{p}$ in an $(M\times N)$-sized lattice grid $\mathcal{A}$.
Using a finite number of directions always yields the presence of ghosts, so
preventing uniqueness. Ghosts can be managed by increasing the number of
directions, wh... | 1 | 0 | 0 | 0 | 0 | 0 |
On finite determinacy of complete intersection singularities | We give an elementary combinatorial proof of the following fact: Every real
or complex analytic complete intersection germ X is equisingular -- in the
sense of the Hilbert-Samuel function -- with a germ of an algebraic set defined
by sufficiently long truncations of the defining equations of X.
| 0 | 0 | 1 | 0 | 0 | 0 |
Topological phase transformations and intrinsic size effects in ferroelectric nanoparticles | Composite materials comprised of ferroelectric nanoparticles in a dielectric
matrix are being actively investigated for a variety of functional properties
attractive for a wide range of novel electronic and energy harvesting devices.
However, the dependence of these functionalities on shapes, sizes, orientation
and m... | 0 | 1 | 0 | 0 | 0 | 0 |
Honors Thesis: On the faithfulness of the Burau representation at roots of unity | We study the kernel of the evaluated Burau representation through the braid
element $\sigma_i \sigma_{i+1} \sigma_i$. The element is significant as a part
of the standard braid relation. We establish the form of this element's image
raised to the $n^{th}$ power. Interestingly, the cyclotomic polynomials arise
and can... | 0 | 0 | 1 | 0 | 0 | 0 |
On Interpolation and Symbol Elimination in Theory Extensions | In this paper we study possibilities of interpolation and symbol elimination
in extensions of a theory $\mathcal{T}_0$ with additional function symbols
whose properties are axiomatised using a set of clauses. We analyze situations
in which we can perform such tasks in a hierarchical way, relying on existing
mechanism... | 1 | 0 | 0 | 0 | 0 | 0 |
Stellar Abundances for Galactic Archaeology Database IV - Compilation of Stars in Dwarf Galaxies | We have constructed the database of stars in the local group using the
extended version of the SAGA (Stellar Abundances for Galactic Archaeology)
database that contains stars in 24 dwarf spheroidal galaxies and ultra faint
dwarfs. The new version of the database includes more than 4500 stars in the
Milky Way, by remo... | 0 | 1 | 0 | 0 | 0 | 0 |
Relativistic distortions in the large-scale clustering of SDSS-III BOSS CMASS galaxies | General relativistic effects have long been predicted to subtly influence the
observed large-scale structure of the universe. The current generation of
galaxy redshift surveys have reached a size where detection of such effects is
becoming feasible. In this paper, we report the first detection of the redshift
asymmet... | 0 | 1 | 0 | 0 | 0 | 0 |
Superconductivity at the vacancy disorder boundary in K$_x$Fe$_{2-y}$Se$_2$ | The role of phase separation in the emergence of superconductivity in alkali
metal doped iron selenides A$_{x}$Fe$_{2-y}$Se$_{2}$ (A = K, Rb, Cs) is
revisited. High energy X-ray diffraction and Monte Carlo simulation were used
to investigate the crystal structure of quenched superconducting (SC) and
as-grown non-supe... | 0 | 1 | 0 | 0 | 0 | 0 |
Probing Primordial-Black-Hole Dark Matter with Gravitational Waves | Primordial black holes (PBHs) have long been suggested as a candidate for
making up some or all of the dark matter in the Universe. Most of the
theoretically possible mass range for PBH dark matter has been ruled out with
various null observations of expected signatures of their interaction with
standard astrophysica... | 0 | 1 | 0 | 0 | 0 | 0 |
Fundamental limits of low-rank matrix estimation: the non-symmetric case | We consider the high-dimensional inference problem where the signal is a
low-rank matrix which is corrupted by an additive Gaussian noise. Given a
probabilistic model for the low-rank matrix, we compute the limit in the large
dimension setting for the mutual information between the signal and the
observations, as wel... | 0 | 0 | 1 | 0 | 0 | 0 |
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees | Gaussian processes (GPs) offer a flexible class of priors for nonparametric
Bayesian regression, but popular GP posterior inference methods are typically
prohibitively slow or lack desirable finite-data guarantees on quality. We
develop an approach to scalable approximate GP regression with finite-data
guarantees on ... | 0 | 0 | 0 | 1 | 0 | 0 |
Integral representations and asymptotic behaviours of Mittag-Leffler type functions of two variables | The paper explores various special functions which generalize the
two-parametric Mittag-Leffler type function of two variables. Integral
representations for these functions in different domains of variation of
arguments for certain values of the parameters are obtained. The asymptotic
expansions formulas and asymptot... | 0 | 0 | 1 | 0 | 0 | 0 |
Efficient Mendler-Style Lambda-Encodings in Cedille | It is common to model inductive datatypes as least fixed points of functors.
We show that within the Cedille type theory we can relax functoriality
constraints and generically derive an induction principle for Mendler-style
lambda-encoded inductive datatypes, which arise as least fixed points of
covariant schemes whe... | 1 | 0 | 0 | 0 | 0 | 0 |
Super Jack-Laurent Polynomials | Let $\mathcal{D}_{n,m}$ be the algebra of the quantum integrals of the
deformed Calogero-Moser-Sutherland problem corresponding to the root system of
the Lie superalgebra $\frak{gl}(n,m)$. The algebra $\mathcal{D}_{n,m}$ acts
naturally on the quasi-invariant Laurent polynomials and we investigate the
corresponding sp... | 0 | 0 | 1 | 0 | 0 | 0 |
A New Classification of Technologies | This study here suggests a classification of technologies based on taxonomic
characteristics of interaction between technologies in complex systems that is
not a studied research field in economics of technical change. The proposed
taxonomy here categorizes technologies in four typologies, in a broad analogy
with the... | 1 | 0 | 0 | 0 | 0 | 0 |
Potential functions on Grassmannians of planes and cluster transformations | With a triangulation of a planar polygon with $n$ sides, one can associate an
integrable system on the Grassmannian of 2-planes in an $n$-space. In this
paper, we show that the potential functions of Lagrangian torus fibers of the
integrable systems associated with different triangulations glue together by
cluster tr... | 0 | 0 | 1 | 0 | 0 | 0 |
Physical properties of the first spectroscopically confirmed red supergiant stars in the Sculptor Group galaxy NGC 55 | We present K-band Multi-Object Spectrograph (KMOS) observations of 18 Red
Supergiant (RSG) stars in the Sculptor Group galaxy NGC 55. Radial velocities
are calculated and are shown to be in good agreement with previous estimates,
confirming the supergiant nature of the targets and providing the first
spectroscopicall... | 0 | 1 | 0 | 0 | 0 | 0 |
Gas near a wall: a shortened mean free path, reduced viscosity, and the manifestation of a turbulent Knudsen layer in the Navier-Stokes solution of a shear flow | For the gas near a solid planar wall, we propose a scaling formula for the
mean free path of a molecule as a function of the distance from the wall, under
the assumption of a uniform distribution of the incident directions of the
molecular free flight. We subsequently impose the same scaling onto the
viscosity of the... | 0 | 1 | 0 | 0 | 0 | 0 |
Greater data science at baccalaureate institutions | Donoho's JCGS (in press) paper is a spirited call to action for
statisticians, who he points out are losing ground in the field of data science
by refusing to accept that data science is its own domain. (Or, at least, a
domain that is becoming distinctly defined.) He calls on writings by John
Tukey, Bill Cleveland, a... | 0 | 0 | 0 | 1 | 0 | 0 |
Direct evidence of hierarchical assembly at low masses from isolated dwarf galaxy groups | The demographics of dwarf galaxy populations have long been in tension with
predictions from the Cold Dark Matter (CDM) paradigm. If primordial density
fluctuations were scale-free as predicted, dwarf galaxies should themselves
host dark matter subhaloes, the most massive of which may have undergone star
formation re... | 0 | 1 | 0 | 0 | 0 | 0 |
Short-term Mortality Prediction for Elderly Patients Using Medicare Claims Data | Risk prediction is central to both clinical medicine and public health. While
many machine learning models have been developed to predict mortality, they are
rarely applied in the clinical literature, where classification tasks typically
rely on logistic regression. One reason for this is that existing machine
learni... | 1 | 0 | 0 | 1 | 0 | 0 |
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection | We address the problem of activity detection in continuous, untrimmed video
streams. This is a difficult task that requires extracting meaningful
spatio-temporal features to capture activities, accurately localizing the start
and end times of each activity. We introduce a new model, Region Convolutional
3D Network (R... | 1 | 0 | 0 | 0 | 0 | 0 |
Regularization for Deep Learning: A Taxonomy | Regularization is one of the crucial ingredients of deep learning, yet the
term regularization has various definitions, and regularization methods are
often studied separately from each other. In our work we present a systematic,
unifying taxonomy to categorize existing methods. We distinguish methods that
affect dat... | 1 | 0 | 0 | 1 | 0 | 0 |
Re-Evaluating the Netflix Prize - Human Uncertainty and its Impact on Reliability | In this paper, we examine the statistical soundness of comparative
assessments within the field of recommender systems in terms of reliability and
human uncertainty. From a controlled experiment, we get the insight that users
provide different ratings on same items when repeatedly asked. This volatility
of user ratin... | 1 | 0 | 0 | 0 | 0 | 0 |
Infinite monochromatic sumsets for colourings of the reals | N. Hindman, I. Leader and D. Strauss proved that it is consistent that there
is a finite colouring of $\mathbb R$ so that no infinite sumset
$X+X=\{x+y:x,y\in X\}$ is monochromatic. Our aim in this paper is to prove a
consistency result in the opposite direction: we show that, under certain
set-theoretic assumptions,... | 0 | 0 | 1 | 0 | 0 | 0 |
Mean-Field Games with Differing Beliefs for Algorithmic Trading | Even when confronted with the same data, agents often disagree on a model of
the real-world. Here, we address the question of how interacting heterogenous
agents, who disagree on what model the real-world follows, optimize their
trading actions. The market has latent factors that drive prices, and agents
account for ... | 0 | 0 | 0 | 0 | 0 | 1 |
Energy efficiency of finite difference algorithms on multicore CPUs, GPUs, and Intel Xeon Phi processors | In addition to hardware wall-time restrictions commonly seen in
high-performance computing systems, it is likely that future systems will also
be constrained by energy budgets. In the present work, finite difference
algorithms of varying computational and memory intensity are evaluated with
respect to both energy eff... | 1 | 1 | 0 | 0 | 0 | 0 |
A Plane of High Velocity Galaxies Across the Local Group | We recently showed that several Local Group (LG) galaxies have much higher
radial velocities (RVs) than predicted by a 3D dynamical model of the standard
cosmological paradigm. Here, we show that 6 of these 7 galaxies define a thin
plane with root mean square thickness of only 101 kpc despite a widest extent
of nearl... | 0 | 1 | 0 | 0 | 0 | 0 |
Scalable Magnetic Field SLAM in 3D Using Gaussian Process Maps | We present a method for scalable and fully 3D magnetic field simultaneous
localisation and mapping (SLAM) using local anomalies in the magnetic field as
a source of position information. These anomalies are due to the presence of
ferromagnetic material in the structure of buildings and in objects such as
furniture. W... | 1 | 0 | 0 | 1 | 0 | 0 |
K-means Algorithm over Compressed Binary Data | We consider a network of binary-valued sensors with a fusion center. The
fusion center has to perform K-means clustering on the binary data transmitted
by the sensors. In order to reduce the amount of data transmitted within the
network, the sensors compress their data with a source coding scheme based on
binary spar... | 1 | 0 | 1 | 0 | 0 | 0 |
Variational Inference for Gaussian Process Models with Linear Complexity | Large-scale Gaussian process inference has long faced practical challenges
due to time and space complexity that is superlinear in dataset size. While
sparse variational Gaussian process models are capable of learning from
large-scale data, standard strategies for sparsifying the model can prevent the
approximation o... | 1 | 0 | 0 | 1 | 0 | 0 |
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