March 2020 arXiv papers — page 130

Paul Mücksch, Gerhard Roehrle

Let $\mathscr A$ be a Coxeter arrangement of rank $\ell$. In 1987 Orlik, Solomon and Terao conjectured that for every $1\leq d \leq \ell$, the first $d$ exponents of $\mathscr A$ -- when listed in increasing order -- are realized as the exponents of a free restriction of $\mathscr A$ to some intersection of reflecting hyperplanes of $\mathscr A$ of dimension

Elvise Berchio, Debdip Ganguly, Prasun Roychowdhury

We prove second and fourth order improved Poincaré type inequalities on the hyperbolic space involving Hardy-type remainder terms. Since theirs l.h.s. only involve the radial part of the gradient or of the laplacian, they can be seen as stronger versions of the classical Poincaré inequality. We show that such inequalities hold true on model manifolds as well

Dimitri Bouche, Marianne Clausel, François Roueff, Florence d'Alché-Buc

To address functional-output regression, we introduce projection learning (PL), a novel dictionary-based approach that learns to predict a function that is expanded on a dictionary while minimizing an empirical risk based on a functional loss. PL makes it possible to use non orthogonal dictionaries and can then be combined with dictionary learning; it is thu

Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin

The most widely used internal measure for clustering evaluation is the silhouette coefficient, whose naive computation requires a quadratic number of distance calculations, which is clearly unfeasible for massive datasets. Surprisingly, there are no known general methods to efficiently approximate the silhouette coefficient of a clustering with rigorously pr

Alexis Bouthier, David Kazhdan, Yakov Varshavsky

The goal of this work is to construct a perverse t-structure on the infinity-category of l-adic LG-equivariant sheaves on the loop Lie algebra Lg and to show that the affine Grothendieck-Springer sheaf S is perverse. Moreover, S is an intermediate extension of its restriction to the locus of ``compact" elements with regular semi-simple reduction. Note th

Shishir Khandelwal, Nicolas Palazzo, Nicolas Brunner, Géraldine Haack

Autonomous entanglement engines have recently been proposed to generate steady-state bipartite and multipartite entanglement exploiting only incoherent interactions with thermal baths at different temperatures. In this work, we investigate the interplay between heat current and entanglement in a two-qubit entanglement engine, deriving a critical heat current

Włodzimierz Drabent

This paper contains examples for a companion paper "The Prolog Debugger and Declarative Programming", which discusses (in)adequacy of the Prolog debugger for declarative programming. Logic programming is a declarative programming paradigm. Programming language Prolog makes logic programming possible, at least to a substantial extent. However the Prol

Krzysztof Jachymski, Florian Meinert

Hybrid ion-atom systems provide an excellent platform for studies of state-resolved quantum chemistry at low temperatures, where quantum effects may be prevalent. Here we study theoretically the process of vibrational relaxation of an initially weakly bound molecular ion due to collisions with the background gas atoms. We show that this inelastic process is

Julie Cornet, Nicolas Destainville, Manoel Manghi

Lipid vesicles composed of a mixture of two types of lipids are studied by intensive Monte-Carlo numerical simulations. The coupling between the local composition and the membrane shape is induced by two different spontaneous curvatures of the components. We explore the various morphologies of these biphasic vesicles coupled to the observed patterns such as

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

Energy-efficient navigation constitutes an important challenge in electric vehicles, due to their limited battery capacity. We employ a Bayesian approach to model the energy consumption at road segments for efficient navigation. In order to learn the model parameters, we develop an online learning framework and investigate several exploration strategies such

Arthur Mensch, Gabriel Peyré

Optimal Transport (OT) distances are now routinely used as loss functions in ML tasks. Yet, computing OT distances between arbitrary (i.e. not necessarily discrete) probability distributions remains an open problem. This paper introduces a new online estimator of entropy-regularized OT distances between two such arbitrary distributions. It uses streams of sa

Ziling Wu, Ping Liu, Zheng Hu, Bocheng Li

Anomaly detection of time series plays an important role in reliability systems engineering. However, in practical application, there is no precisely defined boundary between normal and anomalous behaviors in different application scenarios. Therefore, different anomaly detection algorithms and processes ought to be adopted for time series in different situa

Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Joseph E. Gonzalez

Sample-based learning model predictive control (LMPC) strategies have recently attracted attention due to their desirable theoretical properties and their good empirical performance on robotic tasks. However, prior analysis of LMPC controllers for stochastic systems has mainly focused on linear systems in the iterative learning control setting. We present a

Francisco Naveros, Niceto R. Luque, Eduardo Ros, Angelo Arleo

We embed a spiking cerebellar model within an adaptive real-time (RT) control loop that is able to operate a real robotic body (iCub) when performing different vestibulo-ocular reflex (VOR) tasks. The spiking neural network computation, including event- and time-driven neural dynamics, neural activity, and spike-timing dependent plasticity (STDP) mechanisms,

Anton Arnold, Christian Schmeiser, Beatrice Signorello

We are concerned with the short- and large-time behavior of the $L^2$-propagator norm of Fokker-Planck equations with linear drift, i.e. $\partial_t f=\mathrm{div}_{x}{(D \nabla_x f+Cxf)}$. With a coordinate transformation these equations can be normalized such that the diffusion and drift matrices are linked as $D=C_S$, the symmetric part of $C$. The main r

Siddharth Dwivedi, Andrea Addazi, Yang Zhou, Puneet Sharma

We study the multi-boundary entanglement structure of the states prepared in (1+1) and (2+1) dimensional Chern-Simons theory with finite discrete gauge group $G$. The states in (1+1)-$d$ are associated with Riemann surfaces of genus $g$ with multiple $S^1$ boundaries and we use replica trick to compute the entanglement entropy for such states. In (2+1)-$d$,

Manuel Saorín, Jan Šťovíček

We study when the heart of a t-structure in a triangulated category $\mathcal{D}$ with coproducts is AB5 or a Grothendieck category. If $\mathcal{D}$ satisfies Brown representability, a t-structure has an AB5 heart with an injective cogenerator and coproduct-preserving associated homological functor if, and only if, the coaisle has a pure-injective t-cogener

Athanasios Andrikopoulos

Utility representations of preference relations in symmetric topological spaces have the advantage of fully characterising these relations. But, this is not true in the case of representations of preference relations that are mostly incomplete and use asymmetric topologies. In order to avoid this unfortunate circumstance, due to lack of symmetry, the notion

Victor P. Ruban

Vortex coherent structures on arrays of nonlinear oscillators joined by weak links into topologically nontrivial two-dimensional discrete manifolds have been theoretically studied. A circuit of nonlinear electric oscillators coupled by relatively weak capacitances has been considered as a possible physical implementation of such objects. Numerical experiment

Elene Anton, Urtzi Ayesta, Matthieu Jonckheere, Ina Verloop

We analyze the performance of redundancy in a multi-type job and multi-type server system. We assume the job dispatcher is unaware of the servers' capacities, and we set out to study under which circumstances redundancy improves the performance. With redundancy an arriving job dispatches redundant copies to all its compatible servers, and departs as soon

Sebastian Häfner, Sofia Herbers, Stefan Vogt, Christian Lisdat

We present an interrogation laser system for a transportable strontium lattice clock operating at 698 nm, which is based on an ultra-low-expansion glass reference cavity. Transportability is achieved by implementing a rigid, compact, and vibration insensitive mounting of the 12 cm-long reference cavity, sustaining shocks of up to 50 g. The cavity is mounted

Jurgen Berndt, Carlos Olmos

In 1980, Onishchik introduced the index of a Riemannian symmetric space as the minimal codimension of a (proper) totally geodesic submanifold. He calculated the index for symmetric spaces of rank less than or equal to 2, but for higher rank it was unclear how to tackle the problem. In earlier papers we developed several approaches to this problem, which allo

Sverre A. Gulbrandsen, Camilla Espedal, Arne Brataas

Recent experiments demonstrate that antiferromagnets exhibit the spin Hall effect. We study a tight-binding model of an antiferromagnet on a square lattice with Rashba spin-orbit coupling and disorder. By exact diagonalization of a finite system connected to reservoirs within the Landauer-B$\ddot{\text{u}}$ttiker formalism, we compute the transverse spin Hal

Mikhail Dubashinskiy

What will be if, given a pure stationary state on a compact hyperbolic surface, we start applying raising operator every $\hbar$ "adiabatic" second? It turns that during adiabatic time comparable to 1 wavefunction will change as a wave traveling with a finite speed (with respect to the adiabatic time), whereas the semiclassical measure of the system

Lieven Le Bruyn

Two new arithmetic sites are introduced, based on dynamical Belyi maps and Conway's big picture, respectively. We relate these to arboreal Galois representations, Bost-Connes data, and the original arithmetic site due to Connes and Consani.

Hugh Osborne, Yi Ming Lai, Marc de Kamps

This is a living document that will be updated when appropriate. MIIND [1, 2] is a population-level neural simulator. It is based on population density techniques, just like DIPDE [3]. Contrary to DIPDE, MIIND is agnostic to the underlying neuron model used in its populations so any 1, 2 or 3 dimensional model can be set up with minimal effort. The resulting

William Agnew, Pedro Domingos

Current deep reinforcement learning (RL) approaches incorporate minimal prior knowledge about the environment, limiting computational and sample efficiency. \textit{Objects} provide a succinct and causal description of the world, and many recent works have proposed unsupervised object representation learning using priors and losses over static object propert

Hao Wu, Jan Paul Siebert, Xiangrong Xu

This paper proposes a novel automatically generating image masks method for the state-of-the-art Mask R-CNN deep learning method. The Mask R-CNN method achieves the best results in object detection until now, however, it is very time-consuming and laborious to get the object Masks for training, the proposed method is composed by a two-stage design, to automa

Bernadette Spieler, Naomi Pfaff, Stefania Makrygiannaki, Wolfgang Slany

Educational games are commonly used to motivate students and provide enhanced learning opportunities. Apps and mobile games play an increasingly important role in education and smartphones are part of the daily lives of most female teenagers: Half of mobile gamers are women and 64% of women prefer smartphones to other platforms. However, gender differences i

Haozhe Wang, Jiale Zhou, Xuming He

Despite recent success of deep network-based Reinforcement Learning (RL), it remains elusive to achieve human-level efficiency in learning novel tasks. While previous efforts attempt to address this challenge using meta-learning strategies, they typically suffer from sampling inefficiency with on-policy RL algorithms or meta-overfitting with off-policy learn

Qichen Li, Yuanqing Lin, Luofeng Zhou, Jian Li

Creating meta-embeddings for better performance in language modelling has received attention lately, and methods based on concatenation or merely calculating the arithmetic mean of more than one separately trained embeddings to perform meta-embeddings have shown to be beneficial. In this paper, we devise a new meta-embedding model based on the self-attention

Farnaz A. Davani, Sven Hilke, Harald Rösner, David Geissler

Understanding ductility or brittleness of monolithic bulk metallic glasses (BMGs) requires detailed knowledge of the amorphous structure. The medium range order (MRO) of ductile Pd$_{40}$Ni$_{40}$P$_{20}$ and brittle Zr$_{52.5}$Cu$_{17.9}$Ni$_{14.6}$Al$_{10}$Ti$_5$ (Vit105) was characterized prior to and after notched 3-point bending tests using variable-res

Samarth Sinha, Animesh Garg, Hugo Larochelle

Convolutional Neural Networks (CNNs) have shown impressive performance in computer vision tasks such as image classification, detection, and segmentation. Moreover, recent work in Generative Adversarial Networks (GANs) has highlighted the importance of learning by progressively increasing the difficulty of a learning task [26]. When learning a network from s

Lorenzo Dello Schiavo

We study superpositions and direct integrals of quadratic and Dirichlet forms. We show that each quasi-regular Dirichlet space over a probability space admits a unique representation as a direct integral of irreducible Dirichlet spaces, quasi-regular for the same underlying topology. The same holds for each quasi-regular strongly local Dirichlet space over a

Carlos García-Azpeitia, Jean-Philippe Lessard

We study a nonlinear wave equation appearing as a model for a membrane (without viscous effects) under the presence of an electrostatic potential with strength $λ$. The membrane has a unique stable branch of steady states $u_λ$ for $λ\in\lbrack0,λ_{\ast}]$. We prove that the branch $u_λ$ has an infinite number of branches of periodic solutions (free vibratio

Bin Liu, Rongxuan Zhong, Zhaopin Chen, Xizhou Qin

We consider possibilities to grasp and drag one-dimensional solitons in two-component Bose- Einstein condensates (BECs), under the action of gravity, by tweezers induced by spatially confined spin-orbit (SO) coupling applied to the BEC, with the help of focused laser illumination. Solitons of two types are considered, semi-dipoles and mixed modes. We find cr

Maxim Kirsebom, Philipp Kunde, Tomas Persson

We consider the set $\mathcal{R}_\mathrm{io}$ of points returning infinitely many times to a sequence of shrinking targets around themselves. Under additional assumptions we improve Boshernitzan's pioneering result on the speed of recurrence. In the case of the doubling map as well as some linear maps on the $d$ dimensional torus, we even obtain a dichot

Hualie Jiang, Laiyan Ding, Zhenglong Sun, Rui Huang

Unsupervised learning of depth and ego-motion from unlabelled monocular videos has recently drawn great attention, which avoids the use of expensive ground truth in the supervised one. It achieves this by using the photometric errors between the target view and the synthesized views from its adjacent source views as the loss. Despite significant progress, th

Ege Eren, A. Nihat Berker

Metastable reverse-phase droplets are calculated by renormalization-group theory by evaluating the magnetization of a droplet under magnetic field, matching the boundary condition with the reverse phase and noting whether the reverse-phase magnetization sustains. The maximal metastable droplet size and the discontinuity across the droplet boundary are thus c

Zhaoyou Wang, Emily J. Davis

Entanglement entropy is an essential metric for characterizing quantum many-body systems, but its numerical evaluation for neural network representations of quantum states has so far been inefficient and demonstrated only for the restricted Boltzmann machine architecture. Here, we estimate generalized Renyi entropies of autoregressive neural quantum states w

Liang Xu, Xuanwei Zhang, Qianqian Dong

In this paper, we introduce the Chinese corpus from CLUE organization, CLUECorpus2020, a large-scale corpus that can be used directly for self-supervised learning such as pre-training of a language model, or language generation. It has 100G raw corpus with 35 billion Chinese characters, which is retrieved from Common Crawl. To better understand this corpus,

Giacomo Canevari, Giandomenico Orlandi

We prove a $Γ$-convergence result for a class of Ginzburg-Landau type functionals with $\mathcal{N}$-well potentials, where $\mathcal{N}$ is a closed and $(k-2)$-connected submanifold of $\mathbb{R}^m$, in arbitrary dimension. This class includes, for instance, the Landau-de Gennes free energy for nematic liquid crystals. The energy density of minimisers, su

R. Padmanabhan, Alok Shukla

Consider a set of $ n $ points on a plane. A line containing exactly $ 3 $ out of the $ n $ points is called a $ 3 $-rich line. The classical orchard problem asks for a configuration of the $ n $ points on the plane that maximizes the number of $ 3 $-rich lines. In this note, using the group law in elliptic curves over finite fields, we exhibit several (infi

Can Gokler

It is shown that if the Euclidean path integral measure of a minimally coupled free quantum scalar field on a classical metric background is interpreted as probability of observing the field configuration given the background metric then the maximum likelihood estimate of the metric satisfies Euclidean Einstein field equations with the stress-energy tensor o

Sandeep Chinta, Yaswanth Sai Jetti, C Balaji

Default values for many model parameters in Numerical Weather Prediction models are typically adopted based on theoretical or experimental investigations by scheme designers. Short-range forecasts are substantially affected by the specification of parameters in the Weather Research and Forecasting (WRF) model. The presence of a multitude of parameters and se

Benjamin Avanzi, Guillaume Boglioni Beaulieu, Pierre Lafaye de Micheaux, Frédéric Ouimet

The Central Limit Theorem (CLT) is one of the most fundamental results in statistics. It states that the standardized sample mean of a sequence of $n$ mutually independent and identically distributed random variables with finite first and second moments converges in distribution to a standard Gaussian as $n$ goes to infinity. In particular, pairwise independ

Tianyu Zhu, Garnet Kin-Lic Chan

Quantitative prediction of electronic properties in correlated materials requires simulations without empirical truncations and parameters. We present a method to achieve this goal through a new ab initio formulation of dynamical mean-field theory (DMFT). Instead of using small impurities defined in a low-energy subspace, which require complicated downfolded

John W. Simpson-Porco

Relaxed conditions are given for stability of a feedback system consisting of an exponentially stable multi-input multi-output nonlinear plant and an integral controller. Roughly speaking, it is shown that if the composition of the plant equilibrium input-output map and the integral feedback gain is infinitesimally contracting, then the closed-loop system is

Gennady Kozlov

We find the Standard Model sector (SM) interacts to Dark matter (DM) sector through the scale invariant degrees of freedom - the dilatons and Dark photons (DP). The latter have an interplay with SM via the derivatives of the scalar dilaton fields, while to DM it relates via DM current.

Eugene A. Feinberg, Manasa Mandava, Albert N. Shiryaev

This paper extends to Continuous-Time Jump Markov Decision Processes (CTJMDP) the classic result for Markov Decision Processes stating that, for a given initial state distribution, for every policy there is a (randomized) Markov policy, which can be defined in a natural way, such that at each time instance the marginal distributions of state-action pairs for

Karim Bekka, Satoshi Koike

Sufficiency of jets is a very important notion introduced by Rene Thom in order to establish the structural stability theory. The criteria for some sufficiency of jets are known as the Kuo condition and Thom type inequality, which are defined using the Kuo quantity and Thom quantity. Therefore these quantities are meaningful. In this paper we show the equiva

Ozra Heibati, Azam Mani, Esfandiar Faizi, Vahid Karimipour

The problem of combating de-coherence by weak measurements has already been studied for the amplitude damping channel and for specific input states. We generalize this to a large four-parameter family of qubit channels and for the average fidelity over all pure states. As a by-product we classify all the qubit channels which have one invariant pure state and

Xiaogang Zhu, Yufeng Nie, Jungang Wang, Zhanbin Yuan

In this article, an advanced differential quadrature (DQ) approach is proposed for the high-dimensional multi-term time-space-fractional partial differential equations (TSFPDEs) on convex domains. Firstly, a family of high-order difference schemes is introduced to discretize the time-fractional derivative and a semi-discrete scheme for the considered problem

Víctor Hernández-Santamaría, Liliana Peralta

In this paper, we study some controllability and observability problems for stochastic systems coupling fourth- and second-order parabolic equations. The main goal is to control both equations with only one controller localized on the drift of the fourth-order equation. We analyze two cases: on one hand, we study the controllability of a linear backward syst

Kishan Panaganti, Dileep Kalathil

We consider the problem of finitely parameterized multi-armed bandits where the model of the underlying stochastic environment can be characterized based on a common unknown parameter. The true parameter is unknown to the learning agent. However, the set of possible parameters, which is finite, is known a priori. We propose an algorithm that is simple and ea

Jiayin Pan

A consequence of the Cheeger-Gromoll splitting theorem states that for any open manifold $(M,x)$ of nonnegative Ricci curvature, if all the minimal geodesic loops at $x$ that represent elements of $π_1(M,x)$ are contained in a bounded ball, then $π_1(M,x)$ is virtually abelian. We generalize the above result: if these minimal representing geodesic loops of $

Yang Gao, Tao Li, Liaofu Luo

The phylogenetic tree of SARS-CoV-2 (nCov-19) viruses is reconstructed according to the similarity of genome sequences. The tree topology of Betacoronavirus is remarkably consistent with biologist's systematics. Because the tree construction contains enough information about virus mutants, it is suitable to study the evolutionary relationship between nov

Quoc Tran-Dinh, Deyi Liu

We develop a novel unified randomized block-coordinate primal-dual algorithm to solve a class of nonsmooth constrained convex optimization problems, which covers different existing variants and model settings from the literature. We prove that our algorithm achieves optimal $\mathcal{O}(n/k)$ and $\mathcal{O}(n^2/k^2)$ convergence rates (up to a constant fac

Joe Watson

The preferential sampling of locations chosen to observe a spatio-temporal process has been identified as a major problem across multiple fields. Predictions of the process can be severely biased when standard statistical methodologies are applied to preferentially sampled data without adjustment. Currently, methods that can adjust for preferential sampling

Marie Alaghband, Niloofar Yousefi, Ivan Garibay

Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising

Yipu Zhao, Justin S. Smith, Sambhu H. Karumanchi, Patricio A. Vela

Visual-inertial SLAM is essential for robot navigation in GPS-denied environments, e.g. indoor, underground. Conventionally, the performance of visual-inertial SLAM is evaluated with open-loop analysis, with a focus on the drift level of SLAM systems. In this paper, we raise the question on the importance of visual estimation latency in closed-loop navigatio

Jae-Mo Lihm, Cheol-Hwan Park

The Allen-Heine-Cardona theory allows us to calculate phonon-induced electron self-energies from first principles without resorting to the adiabatic approximation. However, this theory has not been able to account for the change of the electron wave function, which is crucial if interband energy differences are comparable to the phonon-induced electron self-

Jintian Zhu

In this paper, we give an affirmative answer to Gromov's conjecture ([3, Conjecture E]) by establishing an optimal Lipschitz lower bound for a class of smooth functions on orientable open $3$-manifolds with uniformly positive sectional curvatures. For rigidity we show that the universal covering of the given manifold must be $\mathbf R^2\times (-c,c)$ wi

Douglas Morrison, Peter Corke, Jürgen Leitner

We present the Evolved Grasping Analysis Dataset (EGAD), comprising over 2000 generated objects aimed at training and evaluating robotic visual grasp detection algorithms. The objects in EGAD are geometrically diverse, filling a space ranging from simple to complex shapes and from easy to difficult to grasp, compared to other datasets for robotic grasping, w

Peter Landgren, Vaibhav Srivastava, Naomi Ehrich Leonard

We study a distributed decision-making problem in which multiple agents face the same multi-armed bandit (MAB), and each agent makes sequential choices among arms to maximize its own individual reward. The agents cooperate by sharing their estimates over a fixed communication graph. We consider an unconstrained reward model in which two or more agents can ch

Luguis de los Santos Baños, Felipe García-Ramos

We show that a cellular automaton (or shift-endomorphism) on a transitive subshift is either almost equicontinuous or sensitive. On the other hand, we construct a cellular automaton on a full-shift (hence a transitive subshift) that is neither almost mean equicontinuous nor mean sensitive.

Anirban Das, Shigeru Imai, Mike P. Wittie, Stacy Patterson

We present a framework for performance optimization in serverless edge-cloud platforms using dynamic task placement. We focus on applications for smart edge devices, for example, smart cameras or speakers, that need to perform processing tasks on input data in real to near-real time. Our framework allows the user to specify cost and latency requirements for

Changhao Sun, Chen Li, Jinghua Zhang, Muhammad Rahaman

For the Convolutional Neural Networks (CNNs) applied in the intelligent diagnosis of gastric cancer, existing methods mostly focus on individual characteristics or network frameworks without a policy to depict the integral information. Mainly, Conditional Random Field (CRF), an efficient and stable algorithm for analyzing images containing complicated conten

Sion An, Soopil Kim, Philip Chikontwe, Sang Hyun Park

Brain-Computer Interfaces (BCI) based on Electroencephalography (EEG) signals, in particular motor imagery (MI) data have received a lot of attention and show the potential towards the design of key technologies both in healthcare and other industries. MI data is generated when a subject imagines movement of limbs and can be used to aid rehabilitation as wel

Yong Zhao, Jian Du, Yishan Wu

John Desmond Bernal (1901-1970) was one of the most eminent scientists in molecular biology, and also regarded as the founding father of the Science of Science. His book The Social Function of Science laid the theoretical foundations for the discipline. In this article, we summarize four chief characteristics of his ideas in the Science of Science: the socio

Harbir Antil, Shodai Kubota, Ken Shirakawa, Noriaki Yamazaki

This paper is devoted to the study of a class of optimal control problems governed by 1-D Kobayashi-Warren-Carter type systems, which are based on a phase-field model of grain boundary motion, proposed by [Kobayashi et al, Physica D, 140, 141-150, 2000]. The class consists of an optimal control problem for a physically realistic state-system of Kobayashi-War

Mengyuan Lee, Ning Ma, Guanding Yu, Huaiyu Dai

Generalized Benders decomposition (GBD) is a globally optimal algorithm for mixed integer nonlinear programming (MINLP) problems, which are NP-hard and can be widely found in the area of wireless resource allocation. The main idea of GBD is decomposing an MINLP problem into a primal problem and a master problem, which are iteratively solved until their solut

J. M. Pino, J. M. Dreiling, C. Figgatt, J. P. Gaebler

The trapped-ion QCCD (quantum charge-coupled device) architecture proposal lays out a blueprint for a universal quantum computer. The design begins with electrodes patterned on a two-dimensional surface configured to trap multiple arrays of ions (or ion crystals). Communication within the ion crystal network allows for the machine to be scaled while keeping

Jun Guo

Let $h=\prod_{i=1}^{t}p_i^{s_i}$ be its decomposition into a product of powers of distinct primes, and $\mathbb{Z}_{h}$ be the residue class ring modulo $h$. Let $\mathbb{Z}_{h}^{n}$ be the $n$-dimensional row vector space over $\mathbb{Z}_{h}$. A generalized Grassmann graph for $\mathbb{Z}_{h}^n$, denoted by $G_r(m,n,\mathbb{Z}_{h})$ ($G_r$ for short), has

Anna Fariha, Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani

The reliability and proper function of data-driven applications hinge on the data's continued conformance to the applications' initial design. When data deviates from this initial profile, system behavior becomes unpredictable. Data profiling techniques such as functional dependencies and denial constraints encode patterns in the data that can be use

Boris Galkin, Ramy Amer, Erika Fonseca, Luiz A. DaSilva

Fifth Generation (5G) cellular networks are expected to provide cellular connectivity for vehicular users, including Unmanned Aerial Vehicles (UAVs). When flying in the air, these users experience strong, unobstructed channel conditions to a large number of Base Stations (BSs) on the ground. This creates very strong interference conditions for the UAV users,

Mai T. P. Le, Luca Sanguinetti, Emil Björnson, Maria-Gabriella Di Benedetto

In overloaded Massive MIMO (mMIMO) systems, wherein the number $K$ of user equipments (UEs) exceeds the number of base station antennas $M$, it has recently been shown that non-orthogonal multiple access (NOMA) can increase the sum spectral efficiency. This paper aims at identifying cases where code-domain NOMA can improve the spectral efficiency of mMIMO in

Nataniel Ruiz, Sarah Adel Bargal, Stan Sclaroff

Face modification systems using deep learning have become increasingly powerful and accessible. Given images of a person's face, such systems can generate new images of that same person under different expressions and poses. Some systems can also modify targeted attributes such as hair color or age. This type of manipulated images and video have been coi

Bagus Tris Atmaja, Masato Akagi

Silence is a part of human-to-human communication, which can be a clue for human emotion perception. For automatic emotion recognition by a computer, it is not clear whether silence is useful to determine human emotion within a speech. This paper presents an investigation of the effect of using silence feature in dimensional emotion recognition. Since the si

Jiabin Yu, Zhi-Da Song, Chao-Xing Liu

Gapless criteria that can efficiently determine whether a crystal is gapless or not are particularly useful for identifying topological semimetals. In this work, we propose a sufficient gapless criterion for three-dimensional non-interacting crystals, based on the simplified expressions for the bulk average value of the static axion field. The brief logic is

V. S. Shchesnovich, M. E. O. Bezerra

We study distinguishability of photons in multiphoton interference on a multiport when fast detectors, capable of precise time resolution, are employed. Such a setup was previously suggested for experimental realization of boson sampling with single photons. We investigate if fast photodetection allows to circumvent distinguishability of realistic single pho

Márk Poór, Saharon Shelah

We give a complete characterization of the sets of cardinals that in a suitable forcing extension can be the Kurepa spectrum, that is, the set of cardinalities of branches of Kurepa trees. This answers a question of the first named author.

Andrey Kormilitzin, Nemanja Vaci, Qiang Liu, Alejo Nevado-Holgado

The field of clinical natural language processing has been advanced significantly since the introduction of deep learning models. The self-supervised representation learning and the transfer learning paradigm became the methods of choice in many natural language processing application, in particular in the settings with the dearth of high quality manually an

Antoine Kornprobst, Matt Davison

Our study aims at quantifying the impact of climate change on corn farming in Ontario under several warming scenarios at the 2068 horizon. It is articulated around a discrete-time dynamic model of corn farm income with an annual time-step, corresponding to one agricultural cycle from planting to harvest. At each period, we compute the income given the corn y

Nataliya Goncharuk, Yury Kudryashov

We study bifurcations in finite-parameter families of vector fields on $S^2$. Recent papers by Yu. Ilyashenko, N. Goncharuk, Yu. Kudryashov, I. Schurov, and N. Solodovnikov provide examples of (locally generic) structurally unstable families of 3-parameter vector fields: generic close 3-parameter families experience different bifurcations. In this paper, we

Ilki Kim

In this work, we study the fluctuation relation and the second law of thermodynamics within a quantum linear oscillator externally driven over the period of time t = tau. To go beyond the standard approach (the two-point projective measurement one) to this subject and also render it discussed in both quantum and classical domains on the single footing, we re

Matthew L. Leavitt, Ari Morcos

The properties of individual neurons are often analyzed in order to understand the biological and artificial neural networks in which they're embedded. Class selectivity-typically defined as how different a neuron's responses are across different classes of stimuli or data samples-is commonly used for this purpose. However, it remains an open questio

Amir Mahdi Sadeghzadeh, Saeed Shiravi, Rasool Jalili

Network traffic classification is used in various applications such as network traffic management, policy enforcement, and intrusion detection systems. Although most applications encrypt their network traffic and some of them dynamically change their port numbers, Machine Learning (ML) and especially Deep Learning (DL)-based classifiers have shown impressive

Patrick L. Combettes, Zev. C. Woodstock

We consider the problem of recovering a signal from nonlinear transformations, under convex constraints modeling a priori information. Standard feasibility and optimization methods are ill-suited to tackle this problem due to the nonlinearities. We show that, in many common applications, the transformation model can be associated with fixed point equations i

L. Tonetto, G. Lugones

Discontinuity gravity modes may arise in perturbed quark-hadron hybrid stars when a sharp density jump exists in the stellar interior and are a potential fingerprint to infer the existence of quark matter cores in compact objects. When a hybrid star is perturbed, conversion reactions may occur at the quark-hadron interface and may have a key role in global s

Shukun Wu

There are two parts for this paper. In the first part, we extend some results in a recent paper by Du, Guth, Li and Zhang to a more general class of phase functions. The main methods are Bourgain-Demeter's $l^2$ decoupling theorem and induction on scales. In the second part, we prove some positive results for the maximal extension operator for hypersurfa

Javier Correa, Enrique R. Pujals

We construct the complete set of orders of growth and we define on it the generalized entropy of a dynamical systems. With this object we provide a framework where we can study the separation of orbits of a map beyond the scope of exponential growth. We are going to show that this construction is particularly useful to study families of dynamical systems wit

Zhen Ma, He Xu, Yonghui Zhang, Junlong Chen

In this paper, a mobile camera positioning method based on forward and inverse kinematics of robot is proposed, which can realize far point positioning of imaging position and attitude tracking in large scene enhancement. Orbit precision motion through the framework overhead cameras and combining with the ground system of sensor array object such as mobile r

Yang Wang, Mohammad Mehrali, Yi-Zhou Zhang, Melvin A. Timmerman

Heterostructures constructed from two-dimensional building blocks have shown promise for field-effect transistors, memory devices, photosensors and other electronic applications1,2. 2D nanosheet crystals can be constructed into multilayer heterostructures using layer-by-layer methods3, but that method cannot be used to fabricate large-scale and thick heteros

Erwen Li, Bokun Zhou, Yunfei Bo, Alan X. Wang

By combining the large Purcell effect of photonic crystal nanocavity and the strong plasma dispersion effect of the transparent conductive oxides, ultra-compact silicon modulators with heterogeneously integrated indium-tin-oxide (ITO) can potentially achieve unprecedented energy efficiency to atto-joule per bit. In this article, we report the first high-spee

Sultan Noman Qasem, Amir Mosavi

In recent decades, attention has been directed at anemia classification for various medical purposes, such as thalassemia screening and predicting iron deficiency anemia (IDA). In this study, a new method has been successfully tested for discrimination between IDA and \b{eta}-thalassemia trait (\b{eta}-TT). The method is based on a Dynamic Harmony Search (DH

Gernot Beer, Eugenio Ruocco, Christian Duenser, Vincenzo Mallardo

The paper is concerned with the development of efficient and accurate solution procedures for the isogeometric boundary element method (BEM) when applied to problems that contain inclusions that have elastic properties different to the computed domain. This topic has been addressed in previous papers but the approach presented here is a considerable improvem

Chenhan Jiang, Shaoju Wang, Hang Xu, Xiaodan Liang

Most advances in medical lesion detection network are limited to subtle modification on the conventional detection network designed for natural images. However, there exists a vast domain gap between medical images and natural images where the medical image detection often suffers from several domain-specific challenges, such as high lesion/background simila

Javier Gonzalez-Trejo, Diego Mercado-Ravell

Detecting and Counting people in a human crowd from a moving drone present challenging problems that arisefrom the constant changing in the image perspective andcamera angle. In this paper, we test two different state-of-the-art approaches, density map generation with VGG19 trainedwith the Bayes loss function and detect-then-count with FasterRCNN with ResNet

Michael Filletti

On 23rd June 2016, 51.9% of British voters voted to leave the European Union, triggering a process and events that have led to the United Kingdom leaving the EU, an event that has become known as 'Brexit'. In this piece of research, we investigate the effects of this entire process on the currency markets, specifically the GBP/EUR exchange rate. Fina