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
Fermi bubbles: high latitude X-ray supersonic shell
The nature of the bipolar, $\gamma$-ray Fermi bubbles (FB) is still unclear, in part because their faint, high-latitude X-ray counterpart has until now eluded a clear detection. We stack ROSAT data at varying distances from the FB edges, thus boosting the signal and identifying an expanding shell behind the southwest...
0
1
0
0
0
0
Passivity-Based Generalization of Primal-Dual Dynamics for Non-Strictly Convex Cost Functions
In this paper, we revisit primal-dual dynamics for convex optimization and present a generalization of the dynamics based on the concept of passivity. It is then proved that supplying a stable zero to one of the integrators in the dynamics allows one to eliminate the assumption of strict convexity on the cost functio...
1
0
0
0
0
0
An integral formula for the powered sum of the independent, identically and normally distributed random variables
The distribution of the sum of r-th power of standard normal random variables is a generalization of the chi-squared distribution. In this paper, we represent the probability density function of the random variable by an one-dimensional absolutely convergent integral with the characteristic function. Our integral for...
0
0
1
0
0
0
A Dynamic Boosted Ensemble Learning Method Based on Random Forest
We propose a dynamic boosted ensemble learning method based on random forest (DBRF), a novel ensemble algorithm that incorporates the notion of hard example mining into Random Forest (RF) and thus combines the high accuracy of Boosting algorithm with the strong generalization of Bagging algorithm. Specifically, we pr...
0
0
0
1
0
0
Inter-Operator Resource Management for Millimeter Wave, Multi-Hop Backhaul Networks
In this paper, a novel framework is proposed for optimizing the operation and performance of a large-scale, multi-hop millimeter wave (mmW) backhaul within a wireless small cell network (SCN) that encompasses multiple mobile network operators (MNOs). The proposed framework enables the small base stations (SBSs) to jo...
1
0
0
0
0
0
An Online Learning Approach to Generative Adversarial Networks
We consider the problem of training generative models with a Generative Adversarial Network (GAN). Although GANs can accurately model complex distributions, they are known to be difficult to train due to instabilities caused by a difficult minimax optimization problem. In this paper, we view the problem of training G...
1
0
0
1
0
0
Weakly supervised CRNN system for sound event detection with large-scale unlabeled in-domain data
Sound event detection (SED) is typically posed as a supervised learning problem requiring training data with strong temporal labels of sound events. However, the production of datasets with strong labels normally requires unaffordable labor cost. It limits the practical application of supervised SED methods. The rece...
1
0
0
0
0
0
Revealing the Coulomb interaction strength in a cuprate superconductor
We study optimally doped Bi$_{2}$Sr$_{2}$Ca$_{0.92}$Y$_{0.08}$Cu$_{2}$O$_{8+\delta}$ (Bi2212) using angle-resolved two-photon photoemission spectroscopy. Three spectral features are resolved near 1.5, 2.7, and 3.6 eV above the Fermi level. By tuning the photon energy, we determine that the 2.7-eV feature arises predo...
0
1
0
0
0
0
Ordering dynamics of self-propelled particles in an inhomogeneous medium
Ordering dynamics of self-propelled particles in an inhomogeneous medium in two-dimensions is studied. We write coarse-grained hydrodynamic equations of motion for coarse-grained density and velocity fields in the presence of an external random disorder field, which is quenched in time. The strength of inhomogeneity ...
0
1
0
0
0
0
Inflationary preheating dynamics with ultracold atoms
We discuss the amplification of loop corrections in quantum many-body systems through dynamical instabilities. As an example, we investigate both analytically and numerically a two-component ultracold atom system in one spatial dimension. The model features a tachyonic instability, which incorporates characteristic a...
0
1
0
0
0
0
Autonomous Extracting a Hierarchical Structure of Tasks in Reinforcement Learning and Multi-task Reinforcement Learning
Reinforcement learning (RL), while often powerful, can suffer from slow learning speeds, particularly in high dimensional spaces. The autonomous decomposition of tasks and use of hierarchical methods hold the potential to significantly speed up learning in such domains. This paper proposes a novel practical method th...
1
0
0
0
0
0
Quantification of tumour evolution and heterogeneity via Bayesian epiallele detection
Motivation: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome -- so-called `epialleles' -- offers greater insight into epigenetic dynamic...
0
0
1
1
0
0
A bootstrap test to detect prominent Granger-causalities across frequencies
Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship between two time series. We propose a bootstrap test on unconditional and conditional Granger-causality spectra, as well as on their difference, to catch particularly prominent causality cycles in relative terms. In parti...
0
0
0
1
0
1
Optimal segregation of proteins: phase transitions and symmetry breaking
Asymmetric segregation of key proteins at cell division -- be it a beneficial or deleterious protein -- is ubiquitous in unicellular organisms and often considered as an evolved trait to increase fitness in a stressed environment. Here, we provide a general framework to describe the evolutionary origin of this asymme...
0
0
0
0
1
0
Optimal make-take fees for market making regulation
We consider an exchange who wishes to set suitable make-take fees to attract liquidity on its platform. Using a principal-agent approach, we are able to describe in quasi-explicit form the optimal contract to propose to a market maker. This contract depends essentially on the market maker inventory trajectory and on ...
0
0
0
0
0
1
Spontaneous symmetry breaking due to the trade-off between attractive and repulsive couplings
Spontaneous symmetry breaking (SSB) is an important phenomenon observed in various fields including physics and biology. In this connection, we here show that the trade-off between attractive and repulsive couplings can induce spontaneous symmetry breaking in a homogeneous system of coupled oscillators. With a simple...
0
1
0
0
0
0
Evolutionary Image Composition Using Feature Covariance Matrices
Evolutionary algorithms have recently been used to create a wide range of artistic work. In this paper, we propose a new approach for the composition of new images from existing ones, that retain some salient features of the original images. We introduce evolutionary algorithms that create new images based on a fitne...
1
0
0
0
0
0
Community Detection with Colored Edges
In this paper, we prove a sharp limit on the community detection problem with colored edges. We assume two equal-sized communities and there are $m$ different types of edges. If two vertices are in the same community, the distribution of edges follows $p_i=\alpha_i\log{n}/n$ for $1\leq i \leq m$, otherwise the distri...
1
1
0
0
0
0
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
Nonlocal neural networks have been proposed and shown to be effective in several computer vision tasks, where the nonlocal operations can directly capture long-range dependencies in the feature space. In this paper, we study the nature of diffusion and damping effect of nonlocal networks by doing spectrum analysis on...
0
0
0
1
0
0
Proof of FLT by Algebra Identities and Linear Algebra
The main aim of the present paper is to represent an exact and simple proof for FLT by using properties of the algebra identities and linear algebra.
0
0
1
0
0
0
An Observational Diagnostic for Distinguishing Between Clouds and Haze in Hot Exoplanet Atmospheres
The nature of aerosols in hot exoplanet atmospheres is one of the primary vexing questions facing the exoplanet field. The complex chemistry, multiple formation pathways, and lack of easily identifiable spectral features associated with aerosols make it especially challenging to constrain their key properties. We pro...
0
1
0
0
0
0
$\mathcal{P}$-schemes and Deterministic Polynomial Factoring over Finite Fields
We introduce a family of mathematical objects called $\mathcal{P}$-schemes, where $\mathcal{P}$ is a poset of subgroups of a finite group $G$. A $\mathcal{P}$-scheme is a collection of partitions of the right coset spaces $H\backslash G$, indexed by $H\in\mathcal{P}$, that satisfies a list of axioms. These objects ge...
1
0
1
0
0
0
Similarity Preserving Representation Learning for Time Series Analysis
A considerable amount of machine learning algorithms take instance-feature matrices as their inputs. As such, they cannot directly analyze time series data due to its temporal nature, usually unequal lengths, and complex properties. This is a great pity since many of these algorithms are effective, robust, efficient,...
1
0
0
0
0
0
Modeling Social Organizations as Communication Networks
We identify the "organization" of a human social group as the communication network(s) within that group. We then introduce three theoretical approaches to analyzing what determines the structures of human organizations. All three approaches adopt a group-selection perspective, so that the group's network structure i...
1
1
0
0
0
0
The Ricci flow on solvmanifolds of real type
We show that for any solvable Lie group of real type, any homogeneous Ricci flow solution converges in Cheeger-Gromov topology to a unique non-flat solvsoliton, which is independent of the initial left-invariant metric. As an application, we obtain results on the isometry groups of non-flat solvsoliton metrics and Ei...
0
0
1
0
0
0
Model-based clustering of multi-tissue gene expression data
Recently, it has become feasible to generate large-scale, multi-tissue gene expression data, where expression profiles are obtained from multiple tissues or organs sampled from dozens to hundreds of individuals. When traditional clustering methods are applied to this type of data, important information is lost, becau...
0
0
0
0
1
0
Fastest Convergence for Q-learning
The Zap Q-learning algorithm introduced in this paper is an improvement of Watkins' original algorithm and recent competitors in several respects. It is a matrix-gain algorithm designed so that its asymptotic variance is optimal. Moreover, an ODE analysis suggests that the transient behavior is a close match to a det...
1
0
1
0
0
0
New Bounds on the Field Size for Maximally Recoverable Codes Instantiating Grid-like Topologies
In recent years, the rapidly increasing amounts of data created and processed through the internet resulted in distributed storage systems employing erasure coding based schemes. Aiming to balance the tradeoff between data recovery for correlated failures and efficient encoding and decoding, distributed storage syste...
1
0
0
0
0
0
Two-Step Disentanglement for Financial Data
In this work, we address the problem of disentanglement of factors that generate a given data into those that are correlated with the labeling and those that are not. Our solution is simpler than previous solutions and employs adversarial training in a straightforward manner. We demonstrate the new method on visual d...
1
0
0
1
0
0
Optimal control of a Vlasov-Poisson plasma by an external magnetic field - Analysis of a tracking type optimal control problem
In the paper "Optimal control of a Vlasov-Poisson plasma by an external magnetic field - The basics for variational calculus" [arXiv:1708.02464] we have already introduced a set of admissible magnetic fields and we have proved that each of those fields induces a unique strong solution of the Vlasov-Poisson system. We...
0
0
1
0
0
0
Towards an algebraic natural proofs barrier via polynomial identity testing
We observe that a certain kind of algebraic proof - which covers essentially all known algebraic circuit lower bounds to date - cannot be used to prove lower bounds against VP if and only if what we call succinct hitting sets exist for VP. This is analogous to the Razborov-Rudich natural proofs barrier in Boolean cir...
1
0
1
0
0
0
In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference
In recent years, a great deal of interest has focused on conducting inference on the parameters in a linear model in the high-dimensional setting. In this paper, we consider a simple and very naïve two-step procedure for this task, in which we (i) fit a lasso model in order to obtain a subset of the variables; and (i...
0
0
1
1
0
0
Asymptotic Analysis of Plausible Tree Hash Modes for SHA-3
Discussions about the choice of a tree hash mode of operation for a standardization have recently been undertaken. It appears that a single tree mode cannot address adequately all possible uses and specifications of a system. In this paper, we review the tree modes which have been proposed, we discuss their problems ...
1
0
0
0
0
0
Neurally Plausible Model of Robot Reaching Inspired by Infant Motor Babbling
In this paper we present a neurally plausible model of robot reaching inspired by human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensory-motor interaction of an agent and the world. This model encompasses both learning sensory-motor correlations through...
1
0
0
0
0
0
When Will AI Exceed Human Performance? Evidence from AI Experts
Advances in artificial intelligence (AI) will transform modern life by reshaping transportation, health, science, finance, and the military. To adapt public policy, we need to better anticipate these advances. Here we report the results from a large survey of machine learning researchers on their beliefs about progre...
1
0
0
0
0
0
E-PUR: An Energy-Efficient Processing Unit for Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are a key technology for emerging applications such as automatic speech recognition, machine translation or image description. Long Short Term Memory (LSTM) networks are the most successful RNN implementation, as they can learn long term dependencies to achieve high accuracy. Unfortun...
1
0
0
0
0
0
Increasing Geminid meteor shower activity
Mathematical modelling has shown that activity of the Geminid meteor shower should rise with time, and that was confirmed by analysis of visual observations 1985--2016. We do not expect any outburst activity of the Geminid shower in 2017, even though the asteroid (3200) Phaethon has close approach to Earth in Decembe...
0
1
0
0
0
0
The Bennett-Orlicz norm
Lederer and van de Geer (2013) introduced a new Orlicz norm, the Bernstein-Orlicz norm, which is connected to Bernstein type inequalities. Here we introduce another Orlicz norm, the Bennett-Orlicz norm, which is connected to Bennett type inequalities. The new Bennett-Orlicz norm yields inequalities for expectations o...
0
0
1
1
0
0
Temporal Justification Logic
Justification logics are modal-like logics with the additional capability of recording the reason, or justification, for modalities in syntactic structures, called justification terms. Justification logics can be seen as explicit counterparts to modal logics. The behavior and interaction of agents in distributed syst...
1
0
0
0
0
0
Simultaneous Multiparty Communication Complexity of Composed Functions
In the Number On the Forehead (NOF) multiparty communication model, $k$ players want to evaluate a function $F : X_1 \times\cdots\times X_k\rightarrow Y$ on some input $(x_1,\dots,x_k)$ by broadcasting bits according to a predetermined protocol. The input is distributed in such a way that each player $i$ sees all of ...
1
0
0
0
0
0
Online Learning for Changing Environments using Coin Betting
A key challenge in online learning is that classical algorithms can be slow to adapt to changing environments. Recent studies have proposed "meta" algorithms that convert any online learning algorithm to one that is adaptive to changing environments, where the adaptivity is analyzed in a quantity called the strongly-...
1
0
0
1
0
0
On the global sup-norm of GL(3) cusp forms
Let $\phi$ be a spherical Hecke-Maass cusp form on the non-compact space $\mathrm{PGL}_3(\mathbb{Z})\backslash\mathrm{PGL}_3(\mathbb{R})$. We establish various pointwise upper bounds for $\phi$ in terms of its Laplace eigenvalue $\lambda_\phi$. These imply, for $\phi$ arithmetically normalized and tempered at the arc...
0
0
1
0
0
0
Four revolutions in physics and the second quantum revolution -- a unification of force and matter by quantum information
Newton's mechanical revolution unifies the motion of planets in the sky and falling of apple on earth. Maxwell's electromagnetic revolution unifies electricity, magnetism, and light. Einstein's relativity revolution unifies space with time, and gravity with space-time distortion. The quantum revolution unifies partic...
0
1
0
0
0
0
Concept Drift Learning with Alternating Learners
Data-driven predictive analytics are in use today across a number of industrial applications, but further integration is hindered by the requirement of similarity among model training and test data distributions. This paper addresses the need of learning from possibly nonstationary data streams, or under concept drif...
1
0
0
1
0
0
A new proof of the competitive exclusion principle in the chemostat
We give an new proof of the well-known competitive exclusion principle in the chemostat model with $n$ species competing for a single resource, for any set of increasing growth functions. The proof is constructed by induction on the number of the species, after being ordered. It uses elementary analysis and compariso...
0
0
1
0
0
0
From Random Differential Equations to Structural Causal Models: the stochastic case
Random Differential Equations provide a natural extension of Ordinary Differential Equations to the stochastic setting. We show how, and under which conditions, every equilibrium state of a Random Differential Equation (RDE) can be described by a Structural Causal Model (SCM), while pertaining the causal semantics. T...
0
0
0
1
0
0
Ties That Bind - Characterizing Classes by Attributes and Social Ties
Given a set of attributed subgraphs known to be from different classes, how can we discover their differences? There are many cases where collections of subgraphs may be contrasted against each other. For example, they may be assigned ground truth labels (spam/not-spam), or it may be desired to directly compare the b...
1
1
0
0
0
0
Probing dark matter with star clusters: a dark matter core in the ultra-faint dwarf Eridanus II
We present a new technique to probe the central dark matter (DM) density profile of galaxies that harnesses both the survival and observed properties of star clusters. As a first application, we apply our method to the `ultra-faint' dwarf Eridanus II (Eri II) that has a lone star cluster ~45 pc from its centre. Using...
0
1
0
0
0
0
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)
We propose the ambiguity problem for the foreground object segmentation task and motivate the importance of estimating and accounting for this ambiguity when designing vision systems. Specifically, we distinguish between images which lead multiple annotators to segment different foreground objects (ambiguous) versus ...
1
0
0
0
0
0
On Some Generalized Polyhedral Convex Constructions
Generalized polyhedral convex sets, generalized polyhedral convex functions on locally convex Hausdorff topological vector spaces, and the related constructions such as sum of sets, sum of functions, directional derivative, infimal convolution, normal cone, conjugate function, subdifferential, are studied thoroughly ...
0
0
1
0
0
0
mGPfusion: Predicting protein stability changes with Gaussian process kernel learning and data fusion
Proteins are commonly used by biochemical industry for numerous processes. Refining these proteins' properties via mutations causes stability effects as well. Accurate computational method to predict how mutations affect protein stability are necessary to facilitate efficient protein design. However, accuracy of pred...
0
0
0
1
1
0
How Do Software Startups Pivot? Empirical Results from a Multiple Case Study
In order to handle intense time pressure and survive in dynamic market, software startups have to make crucial decisions constantly on whether to change directions or stay on chosen courses, or in the terms of Lean Startup, to pivot or to persevere. The existing research and knowledge on software startup pivots are v...
1
0
0
0
0
0
Some criteria for Wind Riemannian completeness and existence of Cauchy hypersurfaces
Recently, a link between Lorentzian and Finslerian Geometries has been carried out, leading to the notion of wind Riemannian structure (WRS), a generalization of Finslerian Randers metrics. Here, we further develop this notion and its applications to spacetimes, by introducing some characterizations and criteria for ...
0
0
1
0
0
0
A generalization of Schönemann's theorem via a graph theoretic method
Recently, Grynkiewicz et al. [{\it Israel J. Math.} {\bf 193} (2013), 359--398], using tools from additive combinatorics and group theory, proved necessary and sufficient conditions under which the linear congruence $a_1x_1+\cdots +a_kx_k\equiv b \pmod{n}$, where $a_1,\ldots,a_k,b,n$ ($n\geq 1$) are arbitrary integer...
1
0
0
0
0
0
Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning
In order for robots to perform mission-critical tasks, it is essential that they are able to quickly adapt to changes in their environment as well as to injuries and or other bodily changes. Deep reinforcement learning has been shown to be successful in training robot control policies for operation in complex environ...
1
0
0
0
0
0
Testing convexity of a discrete distribution
Based on the convex least-squares estimator, we propose two different procedures for testing convexity of a probability mass function supported on N with an unknown finite support. The procedures are shown to be asymptotically calibrated.
0
0
1
1
0
0
Small and Strong Formulations for Unions of Convex Sets from the Cayley Embedding
There is often a significant trade-off between formulation strength and size in mixed integer programming (MIP). When modeling convex disjunctive constraints (e.g. unions of convex sets), adding auxiliary continuous variables can sometimes help resolve this trade-off. However, standard formulations that use such auxi...
0
0
1
0
0
0
Safe Robotic Grasping: Minimum Impact-Force Grasp Selection
This paper addresses the problem of selecting from a choice of possible grasps, so that impact forces will be minimised if a collision occurs while the robot is moving the grasped object along a post-grasp trajectory. Such considerations are important for safety in human-robot interaction, where even a certified "hum...
1
0
0
0
0
0
Nonparametric Kernel Density Estimation for Univariate Curent Status Data
We derive estimators of the density of the event times of current status data. The estimators are derived for the situations where the distribution of the observation times is known and where this distribution is unknown. The density estimators are constructed from kernel estimators of the density of transformed curr...
0
0
1
1
0
0
Non-Kähler Mirror Symmetry of the Iwasawa Manifold
We propose a new approach to the Mirror Symmetry Conjecture in a form suitable to possibly non-Kähler compact complex manifolds whose canonical bundle is trivial. We apply our methods by proving that the Iwasawa manifold $X$, a well-known non-Kähler compact complex manifold of dimension $3$, is its own mirror dual to...
0
0
1
0
0
0
Estimation and Inference for Moments of Ratios with Robustness against Large Trimming Bias
Empirical researchers often trim observations with small denominator A when they estimate moments of the form E[B/A]. Large trimming is a common practice to mitigate variance, but it incurs large trimming bias. This paper provides a novel method of correcting large trimming bias. If a researcher is willing to assume ...
0
0
0
1
0
0
FPGA-based real-time 105-channel data acquisition platform for imaging system
In this paper, a real-time 105-channel data acquisition platform based on FPGA for imaging will be implemented for mm-wave imaging systems. PC platform is also realized for imaging results monitoring purpose. Mm-wave imaging expands our vision by letting us see things under poor visibility conditions. With this exten...
1
0
0
0
0
0
Zn-induced in-gap electronic states in La214 probed by uniform magnetic susceptibility: relevance to the suppression of superconducting Tc
Substitution of isovalent non-magnetic defects, such as Zn, in CuO2 plane strongly modifies the magnetic properties of strongly electron correlated hole doped cuprate superconductors. The reason for enhanced uniform magnetic susceptibility, \c{hi}, in Zn substituted cuprates is debatable. So far, the observed magneti...
0
1
0
0
0
0
Predicate Specialization for Definitional Higher-order Logic Programs
Higher-order logic programming is an interesting extension of traditional logic programming that allows predicates to appear as arguments and variables to be used where predicates typically occur. Higher-order characteristics are indeed desirable but on the other hand they are also usually more expensive to support. ...
1
0
0
0
0
0
Metastability and bifurcation in superconducting nanorings
We describe an approach, based on direct numerical solution of the Usadel equation, to finding stationary points of the free energy of superconducting nanorings. We consider both uniform (equilibrium) solutions and the critical droplets that mediate activated transitions between them. For the uniform solutions, we co...
0
1
0
0
0
0
Origin of life in a digital microcosm
While all organisms on Earth descend from a common ancestor, there is no consensus on whether the origin of this ancestral self-replicator was a one-off event or whether it was only the final survivor of multiple origins. Here we use the digital evolution system Avida to study the origin of self-replicating computer ...
1
1
0
0
0
0
The equivalence of two tax processes
We introduce two models of taxation, the latent and natural tax processes, which have both been used to represent loss-carry-forward taxation on the capital of an insurance company. In the natural tax process, the tax rate is a function of the current level of capital, whereas in the latent tax process, the tax rate ...
0
0
0
0
0
1
Space-Time Geostatistical Models with both Linear and Seasonal Structures in the Temporal Components
We provide a novel approach to model space-time random fields where the temporal argument is decomposed into two parts. The former captures the linear argument, which is related, for instance, to the annual evolution of the field. The latter is instead a circular variable describing, for instance, monthly observation...
0
0
1
1
0
0
Stability and Robust Regulation of Passive Linear Systems
We study the stability of coupled impedance passive regular linear systems under power-preserving interconnections. We present new conditions for strong, exponential, and non-uniform stability of the closed-loop system. We apply the stability results to the construction of passive error feedback controllers for robus...
0
0
1
0
0
0
Bayes Minimax Competitors of Preliminary Test Estimators in k Sample Problems
In this paper, we consider the estimation of a mean vector of a multivariate normal population where the mean vector is suspected to be nearly equal to mean vectors of $k-1$ other populations. As an alternative to the preliminary test estimator based on the test statistic for testing hypothesis of equal means, we der...
0
0
1
1
0
0
Non-orthogonal Multiple Access for High-reliable and Low-latency V2X Communications
In this paper, we consider a dense vehicular communication network where each vehicle broadcasts its safety information to its neighborhood in each transmission period. Such applications require low latency and high reliability, and thus, we propose a non-orthogonal multiple access scheme to reduce the latency and to...
1
0
0
0
0
0
Cohomology monoids of monoids with coefficients in semimodules II
We relate the old and new cohomology monoids of an arbitrary monoid $M$ with coefficients in semimodules over $M$, introduced in the author's previous papers, to monoid and group extensions. More precisely, the old and new second cohomology monoids describe Schreier extensions of semimodules by monoids, and the new t...
0
0
1
0
0
0
Lower Bounds for Higher-Order Convex Optimization
State-of-the-art methods in convex and non-convex optimization employ higher-order derivative information, either implicitly or explicitly. We explore the limitations of higher-order optimization and prove that even for convex optimization, a polynomial dependence on the approximation guarantee and higher-order smoot...
1
0
0
1
0
0
Superconductivity in La1-xCexOBiSSe: carrier doping by mixed valence of Ce ions
We report the effects of Ce substitution on structural, electronic, and magnetic properties of layered bismuth-chalcogenide La1-xCexOBiSSe (x = 0-0.9), which are newly obtained in this study. Metallic conductivity was observed for x > 0.1 because of electron carriers induced by mixed valence of Ce ions, as revealed b...
0
1
0
0
0
0
Gaussian Processes Over Graphs
We propose Gaussian processes for signals over graphs (GPG) using the apriori knowledge that the target vectors lie over a graph. We incorporate this information using a graph- Laplacian based regularization which enforces the target vectors to have a specific profile in terms of graph Fourier transform coeffcients, ...
0
0
0
1
0
0
Differences of Type I error rates for ANOVA and Multilevel-Linear-Models using SAS and SPSS for repeated measures designs
To derive recommendations on how to analyze longitudinal data, we examined Type I error rates of Multilevel Linear Models (MLM) and repeated measures Analysis of Variance (rANOVA) using SAS and SPSS.We performed a simulation with the following specifications: To explore the effects of high numbers of measurement occa...
0
0
0
1
0
0
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
We consider alternate formulations of recently proposed hierarchical Nearest Neighbor Gaussian Process (NNGP) models (Datta et al., 2016a) for improved convergence, faster computing time, and more robust and reproducible Bayesian inference. Algorithms are defined that improve CPU memory management and exploit existin...
0
0
0
1
0
0
Variegation and space weathering on asteroid 21 Lutetia
During the flyby in 2010, the OSIRIS camera on-board Rosetta acquired hundreds of high-resolution images of asteroid Lutetia's surface through a range of narrow-band filters. While Lutetia appears very bland in the visible wavelength range, Magrin et al. (2012) tentatively identified UV color variations in the Baetic...
0
1
0
0
0
0
Rokhlin dimension for compact quantum group actions
We show that, for a given compact or discrete quantum group $G$, the class of actions of $G$ on C*-algebras is first-order axiomatizable in the logic for metric structures. As an application, we extend the notion of Rokhlin property for $G$-C*-algebra, introduced by Barlak, Szabó, and Voigt in the case when $G$ is se...
0
0
1
0
0
0
Parametric Identification Using Weighted Null-Space Fitting
In identification of dynamical systems, the prediction error method using a quadratic cost function provides asymptotically efficient estimates under Gaussian noise and additional mild assumptions, but in general it requires solving a non-convex optimization problem. An alternative class of methods uses a non-paramet...
1
0
0
0
0
0
Learning Large-Scale Bayesian Networks with the sparsebn Package
Learning graphical models from data is an important problem with wide applications, ranging from genomics to the social sciences. Nowadays datasets often have upwards of thousands---sometimes tens or hundreds of thousands---of variables and far fewer samples. To meet this challenge, we have developed a new R package ...
1
0
0
1
0
0
An Asymptotically Optimal Index Policy for Finite-Horizon Restless Bandits
We consider restless multi-armed bandit (RMAB) with a finite horizon and multiple pulls per period. Leveraging the Lagrangian relaxation, we approximate the problem with a collection of single arm problems. We then propose an index-based policy that uses optimal solutions of the single arm problems to index individua...
0
0
1
0
0
0
Effective holographic theory of charge density waves
We use Gauge/Gravity duality to write down an effective low energy holographic theory of charge density waves. We consider a simple gravity model which breaks translations spontaneously in the dual field theory in a homogeneous manner, capturing the low energy dynamics of phonons coupled to conserved currents. We fir...
0
1
0
0
0
0
Interactive Certificates for Polynomial Matrices with Sub-Linear Communication
We develop and analyze new protocols to verify the correctness of various computations on matrices over F[x], where F is a field. The properties we verify concern an F[x]-module and therefore cannot simply rely on previously-developed linear algebra certificates which work only for vector spaces. Our protocols are in...
1
0
0
0
0
0
Cost Functions for Robot Motion Style
We focus on autonomously generating robot motion for day to day physical tasks that is expressive of a certain style or emotion. Because we seek generalization across task instances and task types, we propose to capture style via cost functions that the robot can use to augment its nominal task cost and task constrai...
1
0
0
0
0
0
Revealing the basins of convergence in the planar equilateral restricted four-body problem
The planar equilateral restricted four-body problem where two of the primaries have equal masses is used in order to determine the Newton-Raphson basins of convergence associated with the equilibrium points. The parametric variation of the position of the libration points is monitored when the value of the mass param...
0
1
0
0
0
0
The Eccentric Kozai-Lidov mechanism for Outer Test Particle
The secular approximation of the hierarchical three body systems has been proven to be very useful in addressing many astrophysical systems, from planets, stars to black holes. In such a system two objects are on a tight orbit, and the tertiary is on a much wider orbit. Here we study the dynamics of a system by takin...
0
1
0
0
0
0
A more symmetric picture for Kasparov's KK-bifunctor
For C*-algebras $A$ and $B$, we generalize the notion of a quasihomomorphism from $A$ to $B$, due to Cuntz, by considering quasihomomorphisms from some C*-algebra $C$ to $B$ such that $C$ surjects onto $A$, and the two maps forming a quasihomomorphism agree on the kernel of this surjection. Under an additional assump...
0
0
1
0
0
0
Spot dynamics in a reaction-diffusion model of plant root hair initiation
We study pattern formation in a 2-D reaction-diffusion (RD) sub-cellular model characterizing the effect of a spatial gradient of a plant hormone distribution on a family of G-proteins associated with root-hair (RH) initiation in the plant cell Arabidopsis thaliana. The activation of these G-proteins, known as the Rh...
0
1
0
0
0
0
Incorporating Covariates into Integrated Factor Analysis of Multi-View Data
In modern biomedical research, it is ubiquitous to have multiple data sets measured on the same set of samples from different views (i.e., multi-view data). For example, in genetic studies, multiple genomic data sets at different molecular levels or from different cell types are measured for a common set of individua...
0
0
0
1
0
0
Batch-normalized joint training for DNN-based distant speech recognition
Improving distant speech recognition is a crucial step towards flexible human-machine interfaces. Current technology, however, still exhibits a lack of robustness, especially when adverse acoustic conditions are met. Despite the significant progress made in the last years on both speech enhancement and speech recogni...
1
0
0
0
0
0
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects
This paper describes a preliminary study for producing and distributing a large-scale database of embeddings from the Portuguese Twitter stream. We start by experimenting with a relatively small sample and focusing on three challenges: volume of training data, vocabulary size and intrinsic evaluation metrics. Using a...
1
0
0
0
0
0
A temperate exo-Earth around a quiet M dwarf at 3.4 parsecs
The combination of high-contrast imaging and high-dispersion spectroscopy, which has successfully been used to detect the atmosphere of a giant planet, is one of the most promising potential probes of the atmosphere of Earth-size worlds. The forthcoming generation of extremely large telescopes (ELTs) may obtain suffi...
0
1
0
0
0
0
Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning
Low-rank structures play important role in recent advances of many problems in image science and data science. As a natural extension of low-rank structures for data with nonlinear structures, the concept of the low-dimensional manifold structure has been considered in many data processing problems. Inspired by this ...
1
0
1
0
0
0
History-aware Autonomous Exploration in Confined Environments using MAVs
Many scenarios require a robot to be able to explore its 3D environment online without human supervision. This is especially relevant for inspection tasks and search and rescue missions. To solve this high-dimensional path planning problem, sampling-based exploration algorithms have proven successful. However, these ...
1
0
0
0
0
0
A factor-model approach for correlation scenarios and correlation stress-testing
In 2012, JPMorgan accumulated a USD~6.2 billion loss on a credit derivatives portfolio, the so-called `London Whale', partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows f...
0
0
0
0
0
1
Topology data analysis of critical transitions in financial networks
We develop a topology data analysis-based method to detect early signs for critical transitions in financial data. From the time-series of multiple stock prices, we build time-dependent correlation networks, which exhibit topological structures. We compute the persistent homology associated to these structures in ord...
0
1
1
0
0
0
Construction of exact constants of motion and effective models for many-body localized systems
One of the defining features of many-body localization is the presence of extensively many quasi-local conserved quantities. These constants of motion constitute a corner-stone to an intuitive understanding of much of the phenomenology of many-body localized systems arising from effective Hamiltonians. They may be se...
0
1
0
0
0
0
Toric manifolds over cyclohedra
We study the action of the dihedral group on the (equivariant) cohomology of the toric manifolds associated with cycle graphs.
0
0
1
0
0
0
Use of Genome Information-Based Potentials to Characterize Human Adaptation
As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaption that optimizes population survival in differing environments. This paper mathematically models environmentally induced adaptive forces that quantify changes in the distrib...
0
0
0
0
1
0