October 2020 arXiv papers — page 77

Hiranya Kishore Dey, Sivaramakrishnan Sivasubramanian

The alternating-runs polynomial enumerates alternating runs in the symmetric group. There are three formulae for the number of permutations, $R_{n,k}$ in $\mathfrak{S}_n$ with $k$ alternating runs, but all of them are complicated. We show that when enumerated with sign taken into account, one gets a {\it neat formula}. As a consequence, we get a near refinem

Sangwon Hwang, Hanjin Kim, Hoon Lee, Inkyu Lee

This paper studies multi-agent deep reinforcement learning (MADRL) based resource allocation methods for multi-cell wireless powered communication networks (WPCNs) where multiple hybrid access points (H-APs) wirelessly charge energy-limited users to collect data from them. We design a distributed reinforcement learning strategy where H-APs individually deter

Zhi Qiao, Xugong Qin, Yu Zhou, Fei Yang

Scene text recognition has been a hot topic in computer vision. Recent methods adopt the attention mechanism for sequence prediction which achieve convincing results. However, we argue that the existing attention mechanism faces the problem of attention diffusion, in which the model may not focus on a certain character area. In this paper, we propose Gaussia

George Digkas, Alexander Chatzigeorgiou, Apostolos Ampatzoglou, Paris Avgeriou

While technical debt grows in absolute numbers as software systems evolve over time, the density of technical debt (technical debt divided by lines of code) is reduced in some cases. This can be explained by either the application of refactorings or the development of new artifacts with limited Technical Debt. In this paper we explore the second explanation,

Ryotaro Kobara, Shin Igarashi, Yoshitaka Kawasugi, Ryusei Doi

In-plane magnetoresistance for organic massless Dirac electron system (OMDES) $α$-(BEDT-TTF)$_2$I$_3$ and $θ$-(BEDT-TTF)$_2$I$_3$ in addition to possible candidates of the OMDES $α$-(BETS)$_2$I$_3$ and $α$-(BEDT-STF)$_2$I$_3$, was investigated under hydrostatic pressure. We have found the universal behavior of the in-plane magnetoresistance under a low magne

Xuesu Xiao, Bo Liu, Peter Stone

Learning motion planners to move robot from one point to another within an obstacle-occupied space in a collision-free manner requires either an extensive amount of data or high-quality demonstrations. This requirement is caused by the fact that among the variety of maneuvers the robot can perform, it is difficult to find the single optimal plan without many

Sean Gomes, Steve Zelditch

A self-focal point of a Riemannian manifold $(M,g)$ is a point $p$ so that every geodesic starting from $p$ returns to $p$ at some positive time. It is called a pole if all geodesics through $p$ are closed, and a non-polar self-focal point if all geodesics loop back but not all are smoothly closed. Umbilic points of two dimensional tri-axial ellipsoids are n

Oliver Knill

If h is a ring-valued function on a simplicial complex G we can define two matrices L and g, where the matrix entries are the h energy of homoclinic intersections. We know that the sum over all h values on G is equal to the sum of the Green matrix entries g(x,y). We also have already seen that that the determinants of L or g are both the product of the h(x).

Tyler Vuong, Yangyang Xia, Richard Stern

Voice Type Discrimination (VTD) refers to discrimination between regions in a recording where speech was produced by speakers that are physically within proximity of the recording device ("Live Speech") from speech and other types of audio that were played back such as traffic noise and television broadcasts ("Distractor Audio"). In this work

Peter Kovacs, Xiaosi Zhu, Jesus Carrete, Georg K. H. Madsen

We design and train a neural network (NN) model to efficiently predict the infrared spectra of interstellar polycyclic aromatic hydrocarbons (PAHs) with a computational cost many orders of magnitude lower than what a first-principles calculation would demand. The input to the NN is based on the Morgan fingerprints extracted from the skeletal formulas of the

Chang-Yu Guo, Chang-Lin Xiang

In this paper, we develop an elementary and unified treatment, in the spirit of Rivière and Struwe (Comm. Pure. Appl. Math. 2008), to explore regularity of weak solutions of higher order geometric elliptic systems in critical dimensions without using conservation law. As a result, we obtain an interior Hölder continuity for solutions of the higher order elli

Qin Lou, Xuhui Meng, George Em Karniadakis

In this study, we employ physics-informed neural networks (PINNs) to solve forward and inverse problems via the Boltzmann-BGK formulation (PINN-BGK), enabling PINNs to model flows in both the continuum and rarefied regimes. In particular, the PINN-BGK is composed of three sub-networks, i.e., the first for approximating the equilibrium distribution function,

Francisco Gomes de Oliveira Neto, Felix Dobslaw, Robert Feldt

Diversity has been proposed as a key criterion to improve testing effectiveness and efficiency.It can be used to optimise large test repositories but also to visualise test maintenance issues and raise practitioners' awareness about waste in test artefacts and processes. Even though these diversity-based testing techniques aim to exercise diverse behavio

Jingwei Ma, Jiahui Wen, Panpan Zhang, Guangda Zhang

Neighborhood-based recommenders are a major class of Collaborative Filtering (CF) models. The intuition is to exploit neighbors with similar preferences for bridging unseen user-item pairs and alleviating data sparseness. Many existing works propose neural attention networks to aggregate neighbors and place higher weights on specific subsets of users for rec

Haowei Xu, Jian Zhou, Hua Wang, Ju Li

We theoretically and computationally demonstrate that static magnetization can be generated under light illumination via nonlinear Edelstein effect (NLEE). NLEE is applicable to semiconductors under both linearly and circularly polarized light, and there are no constraints from either spatial inversion or time-reversal symmetry. Remarkably, magnetization can

Jason Obeid, Enamul Hoque

Information visualizations such as bar charts and line charts are very popular for exploring data and communicating insights. Interpreting and making sense of such visualizations can be challenging for some people, such as those who are visually impaired or have low visualization literacy. In this work, we introduce a new dataset and present a neural model f

Soumajit Majumder, Angela Yao

In current interactive instance segmentation works, the user is granted a free hand when providing clicks to segment an object; clicks are allowed on background pixels and other object instances far from the target object. This form of interaction is highly inconsistent with the end goal of efficiently isolating objects of interest. In our work, we propose a

N. L. Diaz, J. M. Matera, R. Rossignoli

We propose a formulation of quantum mechanics in an extended Fock space in which a tensor product structure is applied to time. Subspaces of histories consistent with the dynamics of a particular theory are defined by a direct quantum generalization of the corresponding classical action. The diagonalization of such quantum actions enables us to recover the p

Maciej Besta, Torsten Hoefler

We propose Atomic Active Messages (AAM), a mechanism that accelerates irregular graph computations on both shared- and distributed-memory machines. The key idea behind AAM is that hardware transactional memory (HTM) can be used for simple and efficient processing of irregular structures in highly parallel environments. We illustrate techniques such as coarse

Huy Phan, Huy Le Nguyen, Oliver Y. Chén, Philipp Koch

Existing generative adversarial networks (GANs) for speech enhancement solely rely on the convolution operation, which may obscure temporal dependencies across the sequence input. To remedy this issue, we propose a self-attention layer adapted from non-local attention, coupled with the convolutional and deconvolutional layers of a speech enhancement GAN (SEG

J. Emenheiser, A. Salova, J. Snyder, J. P. Crutchfield

Oscillator networks display intricate synchronization patterns. Determining their stability typically requires incorporating the symmetries of the network coupling. Going beyond analyses that appeal only to a network's automorphism group, we explore synchronization patterns that emerge from the phase-shift invariance of the dynamical equations and symmet

S. Yu. Orevkov

We prove two inequalities for the complex orientations of a separating (Type I) non-singular real algebraic curve in $RP^2$ of any odd degree. We also construct a separating non-singular pseudoholomorphic curve in $RP^2$ of any degree congruent to 9 mod 12 which does not satisfies one of these inequalities. Therefore the oriented isotopy type of the real loc

Vladimir Müller, Yuri Tomilov

We show that the set of all possible constant diagonals of a bounded Hilbert space operator is always convex. This, in particular, answers an open question of J.-C. Bourin ($2003$). Moreover, we show that the joint numerical range of a commuting operator tuple is in general not convex, which fills a gap in the literature. We also prove that the Asplund-Ptak

Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao

Differentiable rendering has paved the way to training neural networks to perform "inverse graphics" tasks such as predicting 3D geometry from monocular photographs. To train high performing models, most of the current approaches rely on multi-view imagery which are not readily available in practice. Recent Generative Adversarial Networks (GANs) that

Anastasia Chavez, Christopher O'Neill

A mathematics student's first introduction to the fundamental theorem of finite fields (FTFF) often occurs in an advanced abstract algebra course and invokes the power of Galois theory to prove it. Yet the combinatorial and algebraic coding theory applications of finite fields can show up early on for students in STEM. To make the FTFF more accessible to

Kelly Isham

Let $f_n(k)$ be the number of subrings of index $k$ in $\mathbb{Z}^n$. We show that results of Brakenhoff imply a lower bound for the asymptotic growth of subrings in $\mathbb{Z}^n$, improving upon lower bounds given by Kaplan, Marcinek, and Takloo-Bighash. Further, we prove two new lower bounds for $f_n(p^e)$ when $e \ge n-1$. Using these bounds, we study t

Akira Matsui, Daisuke Moriwaki

Online advertisements have become one of today's most widely used tools for enhancing businesses partly because of their compatibility with A/B testing. A/B testing allows sellers to find effective advertisement strategies such as ad creatives or segmentations. Even though several studies propose a technique to maximize the effect of an advertisement, th

Tim Bratten, Mauro Natale

In his article "Unitary Representations and Complex Analysis", David Vogan gives a characterization of the continuous invariant Hermitian forms defined on the compactly supported sheaf cohomology groups of certain homogeneous analytic sheaves defined on open orbits in generalized flag manifolds. In the last section of the manuscript, Vogan raises a question

Sijue Wu

It is known since the work of Dyachenko \& Zakharov \cite{zd} that for the weakly nonlinear 2d infinite depth water waves, there are no 3-wave interactions and all of the 4-wave interaction coefficients vanish on the non-trivial resonant manifold. In this paper we study this partial integrability from a different point of view. We construct, directly in the

Maliheh Izadi, Abbas Heydarnoori, Georgios Gousios

Many platforms exploit collaborative tagging to provide their users with faster and more accurate results while searching or navigating. Tags can communicate different concepts such as the main features, technologies, functionality, and the goal of a software repository. Recently, GitHub has enabled users to annotate repositories with topic tags. It has also

Haitao Wang

Given a set of pairwise disjoint polygonal obstacles in the plane, finding an obstacle-avoiding Euclidean shortest path between two points is a classical problem in computational geometry and has been studied extensively. The previous best algorithm was given by Hershberger and Suri [FOCS 1993, SIAM J. Comput. 1999] and the algorithm runs in $O(n\log n)$ tim

Jean-Christophe Mourrat

We consider vector spin glasses whose energy function is a Gaussian random field with covariance given in terms of the matrix of scalar products. For essentially any model in this class, we give an upper bound for the limit free energy, which is expected to be sharp. The bound is expressed in terms of an infinite-dimensional Hamilton-Jacobi equation.

Sarad Venugopalan, Ivan Homoliak, Zengpeng Li, Pawel Szalachowski

Voting is a means to agree on a collective decision based on available choices (e.g., candidates), where participants agree to abide by their outcome. To improve some features of e-voting, decentralized blockchain-based solutions can be employed, where the blockchain represents a public bulletin board that in contrast to a centralized bulletin board provides

Davide Trotta, Matteo Spadetto

We contribute to the knowledge of the quantifier completions and their applications by using the language of doctrines. This algebraic presentation allows us to properly analyse the behaviour of the existential and universal quantifiers. We wish to convey the following points: the first is that these completions preserve the lattice structure and the distrib

Andrew M. Thomas, Takashi Owada

To recover the topology of a manifold in the presence of heavy tailed or exponentially decaying noise, one must understand the behavior of geometric complexes whose points lie in the tail of these noise distributions. This study advances this line of inquiry, and demonstrates functional strong laws of large numbers for the Euler characteristic process of ran

Danil Akhtiamov, Alon Dogon

A group $\Gamma$ is said to be uniformly HS stable if any map $\varphi : \Gamma \to U(n)$ that is almost a unitary representation (w.r.t. the Hilbert Schmidt norm) is close to a genuine unitary representation of the same dimension. We present a complete classification of uniformly HS stable groups among finitely generated residually finite ones. Necessity of

Chen Xu, Yao Xie

We develop a general framework for constructing distribution-free prediction intervals for time series. Theoretically, we establish explicit bounds on conditional and marginal coverage gaps of estimated prediction intervals, which asymptotically converge to zero under additional assumptions. We obtain similar bounds on the size of set differences between ora

Paul Stankus, Andrei Nomerotski, Anže Slosar, Stephen Vintskevich

Improved quantum sensing of photons from astronomical objects could provide high resolution observations in the optical benefiting numerous fields, including general relativity, dark matter studies, and cosmology. It has been recently proposed that stations in optical interferometers would not require a phase-stable optical link if instead sources of quantum

Nikolai Konovalov

In this note we compare the fracture squares from genuine equivariant stable homotopy theory and the fracture squares which appear in the Goodwillie tower for the norm functor.

Alexandru Ghitza, Takuya Yamauchi

Let $C$ be a genus two hyperelliptic curve over a totally real field $F$. We show that the mod 2 Galois representation $\bar{\rho}_{C,2}\colon\mathrm{Gal}(\bar{F}/F)\to \mathrm{GSp}_4(\mathbb{F}_2)$ attached to $C$ is automorphic when the image of $\bar{\rho}_{C,2}$ is isomorphic to $S_5$ and it is also a transitive subgroup under a fixed isomorphism $\mathr

Mohamad N. Nasser, Mohammad N. Abdulrahim

We study the $n$th degree representations $\hat{ρ_G}$ of $Cb_{n}$ and $\hat{ρ_B}$ of $C_{n}$, defined by Valerij G. Bardakov, where $Cb_{n}$ is the group of basis conjugating automorphisms and $C_n$ is the group of conjugating automorphisms. We prove that $\hat{ρ_G}$ is reducible and its $(n-1)$th degree composition factor $\hat{ϕ_G}$ is irreducible if and o

Gary MacGillivray, Shahla Nasserasr, Feiran Yang

A mixed graph is, informally, an object obtained from a simple undirected graph by choosing an orientation for a subset of its edges. A mixed graph is $(m, n)$-coloured if each edge is assigned one of $m \geq 0$ colours, and each arc is assigned one of $n \geq 0$ colours. Oriented graphs are $(0, 1)$-coloured mixed graphs, and 2-edge-coloured graphs are $(2,

Mengwu Guo, Ehsan Haghighat

An energy-based a posteriori error bound is proposed for the physics-informed neural network solutions of elasticity problems. An admissible displacement-stress solution pair is obtained from a mixed form of physics-informed neural networks, and the proposed error bound is formulated as the constitutive relation error defined by the solution pair. Such an er

Mohammad J. Salariseddigh, Uzi Pereg, Holger Boche, Christian Deppe

Deterministic identification (DI) is addressed for Gaussian channels with fast and slow fading, where channel side information is available at the decoder. In particular, it is established that the number of messages scales as $2^{n\log(n)R}$, where $n$ is the block length and $R$ is the coding rate. Lower and upper bounds on the DI capacity are developed in

Paritosh Ramanan, Dan Li, Nagi Gebraeel

Large scale power systems are comprised of regional utilities with assets that stream sensor readings in real time. In order to detect cyberattacks, the globally acquired, real time sensor data needs to be analyzed in a centralized fashion. However, owing to operational constraints, such a centralized sharing mechanism turns out to be a major obstacle. In th

Grzegorz Rzadkowski

In the present paper, we model the cumulative number of persons reported to be infected by the SARS-CoV-2 virus, in a country or a region, by a sum of logistic functions. For a given logistic function, using Eulerian numbers, we find the zeros of its successive derivatives and their relationship with the saturation level of this function. In a given time ser

Marco Zamparo

The L\'evy-Lorentz gas describes the motion of a particle on the real line in the presence of a random array of scattering points, whose distances between neighboring points are heavy-tailed i.i.d. random variables with finite mean. The motion is a continuous-time, constant-speed interpolation of the simple symmetric random walk on the marked points. In this

Ruilin Zhu

Motivated by the observation of exotic structure around 6900MeV in the $J/ψ$-pair mass spectrum using proton-proton collision data by the LHCb collaboration, we study the spectra of fully-heavy tetraquarks within Bethe-Salpeter equation and Regge trajectory relation. The $X(6900)$ may be explained as a radially excited state with quark content $cc\bar{c}\bar

Maria-Romina Ivan, Imre Leader, Luca Q. Zamboni

A factorisation $x = u_1 u_2 \cdots$ of an infinite word $x$ on alphabet $X$ is called `monochromatic', for a given colouring of the finite words $X^*$ on alphabet $X$, if each $u_i$ is the same colour. Wojcik and Zamboni proved that the word $x$ is periodic if and only if for every finite colouring of $X^*$ there is a monochromatic factorisation of $x$. On

Mingjie Sun, Siddhant Agarwal, J. Zico Kolter

Under a commonly-studied backdoor poisoning attack against classification models, an attacker adds a small trigger to a subset of the training data, such that the presence of this trigger at test time causes the classifier to always predict some target class. It is often implicitly assumed that the poisoned classifier is vulnerable exclusively to the adversa

Marcel Sheeny, Emanuele De Pellegrin, Saptarshi Mukherjee, Alireza Ahrabian

Datasets for autonomous cars are essential for the development and benchmarking of perception systems. However, most existing datasets are captured with camera and LiDAR sensors in good weather conditions. In this paper, we present the RAdar Dataset In Adverse weaThEr (RADIATE), aiming to facilitate research on object detection, tracking and scene understand

Valentin Gebhart, Augusto Smerzi, Luca Pezzè

Quantum phase estimation (QPE) is the key subroutine of several quantum computing algorithms as well as a central ingredient in quantum computational chemistry and quantum simulation. While QPE strategies have focused on the estimation of a single phase, applications to the simultaneous estimation of several phases may bring substantial advantages; for insta

Ivan Henao, Raam Uzdin

The laws of thermodynamics are usually formulated under the assumption of infinitely large environments. While this idealization facilitates theoretical treatments, real physical systems are always finite and their interaction range is limited. These constraints have consequences for important tasks such as cooling, not directly captured by the second law of

Sam Chow, Niclas Technau

Gallagher's theorem describes the multiplicative diophantine approximation rate of a typical vector. We establish a fully-inhomogeneous version of Gallagher's theorem, a diophantine fibre refinement, and a sharp and unexpected threshold for Liouville fibres. Along the way, we prove an inhomogeneous version of the Duffin--Schaeffer conjecture for a class of n

Dallas Albritton, Rajendra Beekie

The critical Burgers equation $\partial_t u + u \partial_x u + Λu = 0$ is a toy model for the competition between transport and diffusion with regard to shock formation in fluids. It is well known that smooth initial data does not generate shocks in finite time. Less is known about the long-time behavior for `shock-like' initial data: $u_0 \to \pm a$ as

R. A. Konoplya, A. Zhidenko

An interpretation to the physics of stable geodesics of massive particles in black hole backgrounds has been recently proposed in the context of the AdS/CFT correspondence. It was argued that the existence of stable orbits indicates that the dual state does not thermalize on a thermal time scale and the bulk excitations can be interpreted as metastable state

Pranav Subramani, Nicholas Vadivelu, Gautam Kamath

A common pain point in differentially private machine learning is the significant runtime overhead incurred when executing Differentially Private Stochastic Gradient Descent (DPSGD), which may be as large as two orders of magnitude. We thoroughly demonstrate that by exploiting powerful language primitives, including vectorization, just-in-time compilation, a

Alessandro Papitto, Domitilla de Martino

Millisecond pulsars in tight binaries have recently opened new challenges in our understanding of physical processes governing the evolution of binaries and the interaction between astrophysical plasma and electromagnetic fields. Transitional systems that showed changes from rotation-powered to accretion powered states and vice versa have bridged the populat

Georgios Katsouleas, Efthymios N. Karatzas, Fotios Travlopanos

In this work, we investigate the performance CutFEM as a high fidelity solver as well as we construct a competent and economical reduced order solver for PDE-constrained optimization problems in parametrized domains that live in a fixed background geometry and mesh. Its effectiveness and reliability will be assessed through its application for the numerical

Lilian C. Brambila, Pedro Frejlich, David Martínez Torres

We analyze \emph{submersions with Poisson fibres}. These are submersions whose total space carries a Poisson structure, on which the ambient Poisson structure pulls back, as a Dirac structure, to Poisson structures on each individual fibre. Our ``Poisson-Dirac viewpoint'' is prompted by natural examples of Poisson submersions with Poisson fibers -- in toric

Bruno Brito, Hai Zhu, Wei Pan, Javier Alonso-Mora

Prediction of human motions is key for safe navigation of autonomous robots among humans. In cluttered environments, several motion hypotheses may exist for a pedestrian, due to its interactions with the environment and other pedestrians. Previous works for estimating multiple motion hypotheses require a large number of samples which limits their applicabili

Paritosh Ramanan, Murat Yildirim, Nagi Gebraeel, Edmond Chow

Unit Commitment (UC) is a fundamental problem in power system operations. When coupled with generation maintenance, the joint optimization problem poses significant computational challenges due to coupling constraints linking maintenance and UC decisions. Obviously, these challenges grow with the size of the network. With the introduction of sensors for moni

Raphael Köster, Kevin R. McKee, Richard Everett, Laura Weidinger

Game theoretic views of convention generally rest on notions of common knowledge and hyper-rational models of individual behavior. However, decades of work in behavioral economics have questioned the validity of both foundations. Meanwhile, computational neuroscience has contributed a modernized 'dual process' account of decision-making where model-f

J. R. M. de Nova, P. F. Palacios, I. Carusotto, F. Sols

For flowing quantum gases, it has been found that at long times an initial black-hole laser (BHL) configuration exhibits only two possible states: the ground state or a periodic self-oscillating state of continuous emission of solitons. So far, all the works on this subject are based on a highly idealized model, quite difficult to implement experimentally. H

Utkarsh Mishra, Abolfazl Bayat

The Ground-state criticality of many-body systems is a resource for quantum-enhanced sensing, namely the Heisenberg precision limit, provided that one has access to the whole system. We show that for partial accessibility, the sensing capabilities of a block of spins in the ground state reduces to the sub-Heisenberg limit. To compensate for this, we drive th

Lorenzo Speri, Nicola Tamanini, Robert R. Caldwell, Jonathan R. Gair

Quasars have recently been used as an absolute distance indicator, extending the Hubble diagram to high redshift to reveal a deviation from the expansion history predicted for the standard, $Λ$CDM cosmology. Here we show that the Laser Interferometer Space Antenna (LISA) will efficiently test this claim with standard sirens at high redshift, defined by the c

Julio Arrechea, Carlos Barceló, Valentin Boyanov, Luis J. Garay

General relativity predicts its own demise at singularities, but also appears to conveniently shield itself from the catastrophic consequences of such singularities, making them safe. For instance, if strong cosmic censorship were ultimately satisfied, spacetime singularities, although present, would not pose any practical problems to predictability. Here we

Cheonbok Park, Yunwon Tae, Taehee Kim, Soyoung Yang

Unsupervised machine translation, which utilizes unpaired monolingual corpora as training data, has achieved comparable performance against supervised machine translation. However, it still suffers from data-scarce domains. To address this issue, this paper presents a novel meta-learning algorithm for unsupervised neural machine translation (UNMT) that train

Zexing Li, Baoping Liu

We consider the self-dual Chern-Simons-Schrödinger model in two spatial dimensions. This problem is $L^2$-critical. Under equivariant setting, global wellposedness and scattering were proved in [Liu-Smith, 2016] for solution with initial charge below certain threshold given by the ground state. In this work, we show that the only non-scattering solutions wit

Alexandra Diehl, Matthias Kraus, Alfie Abdul-Rahman, Mennatallah El-Assady

Visualization guidelines, if defined properly, are invaluable to both practical applications and the theoretical foundation of visualization. In this paper, we present a collection of research activities for studying visualization guidelines according to Grounded Theory (GT). We used the discourses at VisGuides, which is an online discussion forum for visual

Will McCutcheon

Systems of coupled cavity modes have the potential to provide bright quantum optical states of light in a highly versatile manner. Microring resonators for instance are highly scalable candidates for photon sources thanks to CMOS fabrication techniques, their small footprint and the relative ease of coupling many such microrings together, however, surface ro

Samuel A. Stein, Betis Baheri, Daniel Chen, Ying Mao

Tremendous progress has been witnessed in artificial intelligence where neural network backed deep learning systems have been used, with applications in almost every domain. As a representative deep learning framework, Generative Adversarial Network (GAN) has been widely used for generating artificial images, text-to-image or image augmentation across areas

Lisha Chen, Hui Su, Qiang Ji

Existing deep learning based facial landmark detection methods have achieved excellent performance. These methods, however, do not explicitly embed the structural dependencies among landmark points. They hence cannot preserve the geometric relationships between landmark points or generalize well to challenging conditions or unseen data. This paper proposes a

Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman

Scaling model-based inverse reinforcement learning (IRL) to real robotic manipulation tasks with unknown dynamics remains an open problem. The key challenges lie in learning good dynamics models, developing algorithms that scale to high-dimensional state-spaces and being able to learn from both visual and proprioceptive demonstrations. In this work, we prese

Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang, Felix J. Herrmann

Most of the seismic inversion techniques currently proposed focus on robustness with respect to the background model choice or inaccurate physical modeling assumptions, but are not apt to large-scale 3D applications. On the other hand, methods that are computationally feasible for industrial problems, such as full waveform inversion, are notoriously bogged d

Chen Yang, Xinyi Zhou, Reza Zafarani

COVID-19 has impacted all lives. To maintain social distancing and avoiding exposure, works and lives have gradually moved online. Under this trend, social media usage to obtain COVID-19 news has increased. Also, misinformation on COVID-19 is frequently spread on social media. In this work, we develop CHECKED, the first Chinese dataset on COVID-19 misinforma

Simon Hochgerner

It is shown that the helicity of three dimensional viscous incompressible flow can be identified with the overall linking of the fluid's initial vorticity to the expectation of a stochastic mean field limit. The relevant mean field limit is obtained by following the Lagrangian paths in the stochastic Hamiltonian interacting particle system of [S. Hochgerner,

Xingchun Xiang, Qingtao Tang, Huaixuan Zhang, Tao Dai

Regression tree (RT) has been widely used in machine learning and data mining community. Given a target data for prediction, a regression tree is first constructed based on a training dataset before making prediction for each leaf node. In practice, the performance of RT relies heavily on the local mean of samples from an individual node during the tree cons

Chaobing Shan, Chunbo Wei, Bing Deng, Jianqiang Huang

Most of the existing tracking methods link the detected boxes to the tracklets using a linear combination of feature cosine distances and box overlap. But the problem of inconsistent features of an object in two different frames still exists. In addition, when extracting features, only appearance information is utilized, neither the location relationship nor

Will FitzGerald

We consider an interacting particle system on the lattice involving pushing and blocking interactions, called PushASEP, in the presence of a wall at the origin. We show that the invariant measure of this system is equal in distribution to a vector of point-to-line last passage percolation times in a random geometrically distributed environment. The largest c

Scott E. Perkins, Nicolás Yunes, Emanuele Berti

Gravitational wave observations of compact binary mergers are already providing stringent tests of general relativity and constraints on modified gravity. Ground-based interferometric detectors will soon reach design sensitivity and they will be followed by third-generation upgrades, possibly operating in conjunction with space-based detectors. How will thes

Shuai Zhang, Zite Jiang, Xingzhong Hou, Zhen Guan

The subgraph-centric programming model is a promising approach and has been applied in many state-of-the-art distributed graph computing frameworks. However, traditional graph partition algorithms have significant difficulties in processing large-scale power-law graphs. The major problem is the communication bottleneck found in many subgraph-centric framewor

D. I. Florentin, C. Schuett, E. M. Werner, N. Zhang

We study a long standing open problem by Ulam, which is whether the Euclidean ball is the unique body of uniform density which will float in equilibrium in any direction. We answer this problem in the class of origin symmetric n-dimensional convex bodies whose relative density to water is 1/2. For n=3, this result is due to Falconer.

Han Yu

In 1962, Gallagher proved an higher dimensional version of Khintchine's theorem on Diophantine approximation. Gallagher's theorem states that for any non-increasing approximation function $\psi:\mathbb{N}\to (0,1/2)$ with $\sum_{q=1}^{\infty} \psi(q)\log q=\infty$ and $\gamma=\gamma'=0$ the following set \[ \{(x,y)\in [0,1]^2: \|qx-\gamma\|\|qy-\gamma'\|<\ps

Jingyi Zhou, Vladimir Khachatryan, Haiyan Gao, Douglas W. Higinbotham

To extract the charge radius of the proton, $r_{p}$, from the electron scattering data, the PRad collaboration at Jefferson Lab has developed a rigorous framework for finding the best functional forms - the fitters - for a robust extraction of $r_{p}$ from a wide variety of sample functions for the range and uncertainties of the PRad data. In this paper we u

Thomas G. Anderson, Oscar P. Bruno

This article introduces a novel "bootstrap domain-of-dependence" concept, according to which, for all time following a given illumination period of arbitrary duration, the wave field scattered by an obstacle is encoded in the history of boundary scattering events for a time-length equal to the diameter of the obstacle, measured in time units. Resulting solut

Louis Ly, Yen-Hsi Richard Tsai

We consider surveillance-evasion differential games, where a pursuer must try to constantly maintain visibility of a moving evader. The pursuer loses as soon as the evader becomes occluded. Optimal controls for game can be formulated as a Hamilton-Jacobi-Isaac equation. We use an upwind scheme to compute the feedback value function, corresponding to the end-

Renbo Zhao, Robert M. Freund

We present and analyze a new generalized Frank-Wolfe method for the composite optimization problem $(P):{\min}_{x\in\mathbb{R}^n}\; f(\mathsf{A} x) + h(x)$, where $f$ is a $\theta$-logarithmically-homogeneous self-concordant barrier, $\mathsf{A}$ is a linear operator and the function $h$ has bounded domain but is possibly non-smooth. We show that our general

J. -R. Chazottes, M. Shinoda

We construct finite-range interactions on $\mathcal{S}^{\mathbb{Z}^2}$, where $\mathcal{S}$ is a finite set, for which the associated equilibrium states (i.e., the shift-invariant Gibbs states) fail to converge as temperature goes to zero. More precisely, if we pick any one-parameter family $(μ_β)_{β>0}$ in which $μ_β$ is an equilibrium state at inverse temp

Kenta Nakahashi, Kohei Takaishi, Takayuki Suzuki, Katsuichi Kanemoto

The power flow process mediated by spin current in the bilayer device consisting of ferromagnetic metal (FM) and non-magnetic metal (NM) layers is examined by realizing experimental evaluations for each process from the microwave absorption to electromotive force (EMF) output. The absorption power by ferromagnetic resonance (FMR) of the thin FM layer during

Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan

Let $f: \{0,1\}^n \to \{0, 1\}$ be a boolean function, and let $f_\land (x, y) = f(x \land y)$ denote the AND-function of $f$, where $x \land y$ denotes bit-wise AND. We study the deterministic communication complexity of $f_\land$ and show that, up to a $\log n$ factor, it is bounded by a polynomial in the logarithm of the real rank of the communication mat

Craig Knuth, Glen Chou, Necmiye Ozay, Dmitry Berenson

We present a method for feedback motion planning of systems with unknown dynamics which provides probabilistic guarantees on safety, reachability, and goal stability. To find a domain in which a learned control-affine approximation of the true dynamics can be trusted, we estimate the Lipschitz constant of the difference between the true and learned dynamics,

Yi-Chun Chen, Xiangqian Yang

We study the information design problem in a single-unit auction setting. The information designer controls independent private signals according to which the buyers infer their binary private values. Assuming that the seller adopts the optimal auction due to Myerson (1981) in response, we characterize both the buyer-optimal information structure, which maxi

Luis A. Anchordoqui

It has long been known that the sharpened tension between the observed and inferred values of the Hubble constant $H_0$ can be alleviated if a fraction of dark matter particles of type $χ$ were produced non-thermally in association with photons $γ$ through the decays of a heavy and relatively long-lived state, viz. $X \to χ+ γ$. It was recently proposed that

Miriam Enzi, Sophie N. Parragh, Jakob Puchinger

The aim of the bi-objective multimodal car-sharing problem (BiO-MMCP) is to determine the optimal mode of transport assignment for trips and to schedule the routes of available cars and users whilst minimizing cost and maximizing user satisfaction. We investigate the BiO-MMCP from a user-centred point of view. As user satisfaction is a crucial aspect in shar

Suman Deb, Raghunath Sahoo, Dhananjaya Thakur, Sushanta Tripathy

Heavy-flavored hadrons are unique probes to study the properties of hot and dense QCD medium produced in ultra-relativistic heavy-ion collisions at RHIC and the LHC. Transverse spherocity is one of the event-topology variables used to separate jetty and isotropic events from the pool of event samples. This study aims to understand the production dynamics of

Yair Schiff, Vijil Chenthamarakshan, Karthikeyan Natesan Ramamurthy, Payel Das

Deep generative models are increasingly becoming integral parts of the in silico molecule design pipeline and have dual goals of learning the chemical and structural features that render candidate molecules viable while also being flexible enough to generate novel designs. Specifically, Variational Auto Encoders (VAEs) are generative models in which encoder-

B. H. Reddy, Asif Ali, Ravi Shankar Singh

We investigate the electronic structure of ternary palladates $A$Pd$_3$O$_4$ ($A$ = Sr, Ca) using valence band photoemission spectroscopy and band structure calculations. Overall width of the valence band and energy positions of various features in experimental valence band spectra are well captured by band structure calculations using hybrid functional. Ban

Robin Rajamäki, Visa Koivunen

Sparse arrays can resolve significantly more scatterers or sources than sensor by utilizing the co-array - a virtual array structure consisting of pairwise differences or sums of sensor positions. Although several sparse array configurations have been developed for passive sensing applications, far fewer active array designs exist. In active sensing, the sum

Ido Efrat

For $m\geq2$, let $F$ be a field of characteristic prime to $m$ and containing the roots of unity of order $m$, and let $G_F$ be its absolute Galois group. We show that the 3-fold Massey products $\langleχ_1,χ_2,χ_3\rangle$, with $χ_1,χ_2,χ_3\in H^1(G_F,\mathbb{Z}/m)$ and $χ_1,χ_3$ $\mathbb{Z}/m$-linearly independent, are non-essential. This was earlier prov