January 2022 arXiv papers — page 134

Wendong Gan, Bolong Wen, Ying Yan, Haitao Chen

Prosody modeling is important, but still challenging in expressive voice conversion. As prosody is difficult to model, and other factors, e.g., speaker, environment and content, which are entangled with prosody in speech, should be removed in prosody modeling. In this paper, we present IQDubbing to solve this problem for expressive voice conversion. To model

C. A. Konidas

It is well known that the set of universal functions on a tree contains a vector space except zero which is dense in the set of harmonic functions. In this paper we improve this result by proving that the set of universal functions on a tree contains two vector spaces except zero which are dense in the space of harmonic functions and intersect only at zero.

Felipe Bernal Arango, Filippo Alpeggiani, Donato Conteduca, Aron Opheij

Near-field scanning optical microscopy is a powerful technique for imaging below the diffraction limit, which has been extensively used in bio-medical imaging and nanophotonics. However, when the electromagnetic fields under measurement are strongly confined, they can be heavily perturbed by the presence of the near-field probe itself. Here, taking inspirati

Sharp Chim Yui Lo

Verification of solutions is crucial for establishing the reliability of simulations. A central challenge is to find an accurate and reliable estimate of the discretization error. Current approaches to this estimation rely on the observed order of accuracy; however, studies have shown that it may alter irregularly or become undefined. Therefore, we propose a

Giulio Colombo, Luciano Mari, Marco Rigoli

In this paper, we study an extension of the CPE conjecture to manifolds $M$ which support a structure relating curvature to the geometry of a smooth map $\varphi : M \to N$. The resulting system, denoted by $(\varphi-\mathrm{CPE})$, is natural from the variational viewpoint and describes stationary points for the integrated $\varphi$-scalar curvature functio

Yipeng Li, Xiangmin Jiao

Numerical integration on spheres, including the computation of the areas of spherical triangles, is a core computation in geomathematics. The commonly used techniques sometimes suffer from instabilities and significant loss of accuracy. We describe a new algorithm, called ARPIST, for accurate and stable integration of functions on spherical triangles. ARPIST

Fabio Bagagiolo, Luciano Marzufero

Motivated by an optimal visiting problem, we study a switching mean-field game on a network, where both a decisional and a switching time-variable is at disposal of the agents for what concerns, respectively, the instant to decide and the instant to perform the switch. Every switch between the nodes of the network represents a switch from $0$ to $1$ of one c

Artyom M. Grigoryan, Sos S. Agaian

Copying the quantum states is contradictory to classical information processing since the fundamental difference between classical and quantum information is that while classical information can be copied perfectly, quantum information cannot. However, this statement does not rule out the risk of building a device that can reproduce a set of quantum states.

Nicholas LaBerge, K. Hunter Wapman, Allison C. Morgan, Sam Zhang

Women and people of color remain dramatically underrepresented among computing faculty, and improvements in demographic diversity are slow and uneven. Effective diversification strategies depend on quantifying the correlates, causes, and trends of diversity in the field. But field-level demographic changes are driven by subfield hiring dynamics because facul

Vincent Guan, Mathav Murugan, Juncheng Wei

We show that the bounded solutions to the fractional Helmholtz equation, $(-Δ)^s u= u$ for $0<s<1$ in $\mathbb{R}^n$, are given by the bounded solutions to the classical Helmholtz equation $(-Δ)u= u$ in $\mathbb{R}^n$ for $n \ge 2$ when $u$ is additionally assumed to be vanishing at $\infty$. When $n=1$, we show that the bounded fractional Helmholtz solution

Xu Zheng, Baowen Li

We propose a method to control the energy distribution in multimode mechanical systems using a single nonlinear feedback loop. We demonstrate that this feedback mechanism simultaneously amplifies the fundamental vibrational mode while suppressing all higher-order modes, effectively channeling energy into the lowest-frequency mode. This process mimics the ene

Gregor Dumphart, Johannes Sager, Armin Wittneben

This paper studies achievable information rates of backscatter communication systems where the tag performs load modulation with a freely adaptable passive termination. We find that the complex phasor of the tag current is constrained to a disk and that the capacity problem can therefore be described with existing results on peak-power-limited quadrature cha

Yanchao Sun, Ruijie Zheng, Xiyao Wang, Andrew Cohen

In many reinforcement learning (RL) applications, the observation space is specified by human developers and restricted by physical realizations, and may thus be subject to dramatic changes over time (e.g. increased number of observable features). However, when the observation space changes, the previous policy will likely fail due to the mismatch of input f

V. Volokitin, I. Meyerov, S. Denisov

Similar to its classical version, quantum Markovian evolution can be either time-discrete or time-continuous. Discrete quantum Markovian evolution is usually modeled with completely-positive trace-preserving maps while time-continuous evolution is often specified with superoperators referred to as &#34;Lindbladians&#34;. Here we address the following questio

François Pacaud, Michel Schanen, Daniel Adrian Maldonado, Alexis Montoison

This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations on upcoming graphical processing units (GPU) dominated computer systems. We design a custom automatic differentiation (AutoDiff) backend that targets highly parallel architectures by extracting the second-order information in ba

Álvaro Gutiérrez, Mercedes H. Rosas

This work highlights the existence of partial symmetries in large families of iterated plethystic coefficients. The plethystic coefficients involved come from the expansion in the Schur basis of iterated plethysms of Schur functions indexed by one-row partitions. The partial symmetries are described in terms of an involution on partitions, the flip involutio

Ayush Arunachalam, S. Novia Berriel, Parag Banerjee, Kanad Basu

Over the recent years, there has been an extensive adoption of Machine Learning (ML) in a plethora of real-world applications, ranging from computer vision to data mining and drug discovery. In this paper, we utilize ML to facilitate efficient film fabrication, specifically Atomic Layer Deposition (ALD). In order to make advances in ALD process development,

Davide Castelnovo, Fabio Gadducci, Marino Miculan

Adhesive categories provide an abstract framework for the algebraic approach to rewriting theory, where many general results can be recast and uniformly proved. However, checking that a model satisfies the adhesivity properties is sometimes far from immediate. In this paper we present a new criterion giving a sufficient condition for $\mathcal{M}, \mathcal{N

Shunhua Jiang, Binghui Peng, Omri Weinstein

We settle the complexity of dynamic least-squares regression (LSR), where rows and labels $(\mathbf{A}^{(t)}, \mathbf{b}^{(t)})$ can be adaptively inserted and/or deleted, and the goal is to efficiently maintain an $\epsilon$-approximate solution to $\min_{\mathbf{x}^{(t)}} \| \mathbf{A}^{(t)} \mathbf{x}^{(t)} - \mathbf{b}^{(t)} \|_2$ for all $t\in [T]$. We

James B. Hartle

Simplicial approximation and the ideas associated with the Regge calculus.provide a concrete way of implementing a sum over histories formulation ofquantum gravity. A four-dimensional simplicial geometry is made up of flat four-simplices joined together.A sum over simplicial geometries is a sum over thedifferent ways the simplices can be joined together with

Alexei A. Deriglazov

We try to go beyond the geometrical optics approximation, by showing that a massless polarized particle allows a wide class of non minimal interactions with an arbitrary gravitational field. One specific example of a curvature-dependent interaction is presented, that results in a frequency-dependent Faraday effect. Even in a Schwarzschild spacetime, this lea

Ilaria Castellani, Mariangiola Dezani-Ciancaglini, Paola Giannini

We propose an interpretation of multiparty sessions as &#34;flow event structures&#34;, which allows concurrency between communications within a session to be explicitly represented. We show that this interpretation is equivalent, when the multiparty sessions can be described by global types, to an interpretation of global types as &#34;prime event structure

George E. Andrews, James A. Sellers, Fares Soufan

In his 1984 Memoir of the American Mathematical Society, George Andrews defined two families of functions, $\phi_k(n)$ and $c\phi_k(n),$ which enumerate two types of combinatorial objects which Andrews called generalized Frobenius partitions. As part of that Memoir, Andrews proved a number of Ramanujan--like congruences satisfied by specific functions within

Jun-Hui Yuan, Ge-Qi Mao, Kan-Hao Xue, Na Bai

Ferroelectricity observed in thin film $\mathrm{HfO_2}$, either doped with Si, Al, etc. or in the $\mathrm{Hf_{0.5}Zr_{0.5}O_2}$ form, has gained great technical significance. However, the soft mode theory faces a difficulty in explaining the origin of such ferroelectricity. In this work, we propose that the 7 cation coordination number of $\mathrm{HfO_2/ZrO

Byung Hee An, Youngjin Bae, Eunjeong Lee

We prove that there are at least as many exact embedded Lagrangian fillings as seeds for Legendrian links of finite type $\mathsf{ADE}$ or affine type $\tilde{\mathsf{D}} \tilde{\mathsf{E}}$. We also provide as many Lagrangian fillings with rotational symmetry as seeds of type $\mathsf{B}$, $\mathsf{G}_2$, $\tilde{\mathsf{G}}_2$, $\tilde{\mathsf{B}}$, or $\t

Yunpu Zhao, Rui Zhang, Xiaqing Li

Automating machine learning has achieved remarkable technological developments in recent years, and building an automated machine learning pipeline is now an essential task. The model ensemble is the technique of combining multiple models to get a better and more robust model. However, existing automated machine learning tends to be simplistic in handling th

Michele Trabucchi, Nami Mowlavi

Pieces of empirical evidence suggest the existence of a period-age relation for long-period variables (LPVs). Yet, this property has hardly been studied on theoretical grounds thus far. We aim to examine the period-age relation using the results from recent nonlinear pulsation calculations. We combined isochrone models with theoretical periods to simulate th

Chuanyuan Ge, Shiping Liu

In 2001, Davies, Gladwell, Leydold, and Stadler proved discrete nodal domain theorems for eigenfunctions of generalized Laplacians, i.e., symmetric matrices with non-positive off-diagonal entries. In this paper, we establish nodal domain theorems for arbitrary symmetric matrices by exploring the induced signed graph structure. Our concepts of nodal domains f

Bin Yi, Sougato Bose

Liang information flow is a quantity widely used in classical network theory to quantify causation, and has been applied widely, for example, to finance and climate. The most striking aspect here is to freeze/subtract a certain node of the network to ascertain its causal influence to other nodes of the network. Such an approach is yet to be applied to quantu

Yaguang Yang

The Hirsch Conjecture stated that any $d$-dimensional polytope with n facets has a diameter at most equal to $n - d$. This conjecture was disproved by Santos (A counterexample to the Hirsch Conjecture, Annals of Mathematics, 172(1) 383-412, 2012). The implication of Santos' work is that all {\it vertex} pivot algorithms cannot solve the linear programming pr

Long Sun

In this work, inspired by some physical intuitions, we define a series of symmetry enriched categories to describe symmetry enriched topological (SET) orders, and define a new tensor product, called the relative tensor product, which describes the stacking of 2+1D SET orders. Then we choose and modify the domain and codomain categories, and manage to make th

Wenjun Yu, Jinzhao Sun, Zeyao Han, Xiao Yuan

With the fast development of quantum technology, the sizes of both digital and analog quantum systems increase drastically. In order to have better control and understanding of the quantum hardware, an important task is to characterize the interaction, i.e., to learn the Hamiltonian, which determines both static and dynamic properties of the system. Conventi

Bernd Kolar, Johannes Diwold, Conrad Gstöttner, Markus Schöberl

The paper addresses the exact linearization of flat nonlinear discrete-time systems by generalized static or dynamic feedbacks which may also depend on forward-shifts of the new input. We first investigate the question which forward-shifts of a given flat output can be chosen in principle as a new input, and subsequently how to actually introduce the new inp

Mehmet Huseyin Temel, Boris Skoric

Entropically secure encryption is a way to encrypt a large plaintext with a small key and still have information-theoretic security, thus in a certain sense circumventing Shannon's result that perfect encryption requires the key to be at least as long as the entropy of the plaintext. Entropically secure encryption is not perfect, and it works only if a lower

Stijn Cambie

In $1967$, Vizing determined the maximum size of a graph with given order and radius. In $1973$, Fridman answered the same question for digraphs with given order and outradius. We investigate that question when restricting to biconnected digraphs. Biconnected digraphs are the digraphs with a finite total distance and hence the interesting ones, as we want to

Stijn Cambie

In 1984, Plesník determined the minimum total distance for given order and diameter and characterized the extremal graphs and digraphs. We prove the analog for given order and radius, when the order is sufficiently large compared to the radius. This confirms asymptotically a conjecture of Chen et al. We also state an analog of the conjecture of Chen et al fo

Amol Sasane

Let ${\mathbb{D}}=\{z\in \mathbb{C}:|z|<1\}$ and for an integer $d\geq 1$, let $S_d$ denote the symmetric group, consisting of of all permutations of the set $\{1,\cdots, d\}$. A function $f:{\mathbb{D}}^d\rightarrow \mathbb{C}$ is symmetric if $f(z_1,\cdots, z_d)=f(z_{σ(1)},\cdots, z_{σ(d)})$ for all $σ\in S_d$ and all $(z_1,\cdots, z_d)\in {\mathbb{D}}^d$.

Alexander Prolubnikov

We consider discrete optimization problems with interval uncertatinty of objective function coefficients. The interval uncertainty models measurements errors. A pos\-sible optimal solution is a solution that is optimal for some possible values of the coefficients. Pro\-ba\-bi\-li\-ty of a possible solution is the probability to obtain such coefficients that

S. Sinha, K. G. Bakshi

A zero-sum two-person Perfect Information Semi-Markov game (PISMG) under limiting ratio average payoff has a value and both the maximiser and the minimiser have optimal pure semi-stationary strategies. We arrive at the result by first fixing an arbitrary initial state and forming the matrix of undiscounted payoffs corresponding to each pair of pure stationar

Vinayak M Kulkarni, Amit Gupta, N. S. Vidhyadhiraja

The non-interacting and non-Hermitian, parity-time ($\mathcal{PT}$)-symmetric Anderson model exhibits an exceptional point (EP) at a non-Hermitian coupling $g=1$, which remains unrenormalized in the presence of interactions (Lourenco et al, arXiv:1806.03116), where the EP was shown to coincide with the quantum critical point (QCP) for Kondo destruction. In t

Renato Fehlberg Júnior, Ivan Kaygorodov

We describe the Kantor square (and Kantor product) of multiplications, extending the classification proposed in [I. Kaygorodov, On the Kantor product, Journal of Algebra and Its Applications, 16 (2017), 9, 1750167]. Besides, we explicitly describe the Kantor square of some low dimensional algebras and give constructive methods for obtaining new transposed Po

François Rivière, Timothée de Guillebon, Damien Raynal, Martin Schmidt

The Brownian motion of a particle hotter than its environment is an iconic out-of-equilibrium system. Its study provides valuable insights into nanoscale thermal effects. Notably, it supplies an excellent diagnosis of thermal effects in optically levitated particles, a promising platform for force sensing and quantum physics tests. Thus, understanding the re

Behnam Pourhassan, Houcine Aounallah, Mir Faizal, Sudhaker Upadhyay

We will investigate a system of M2-M5 branes as a black M2-M5 bound state. The behavior of this system will be investigated at short distances. At such scales, we will have to incorporate quantum gravitational corrections to the supergravity solutions. We will study the non-equilibrium quantum thermodynamics of this black M2-M5 bound state. The quantum work

John Etnyre, Marc Kegel, Sinem Onaran

It is known that any contact 3-manifold can be obtained by rational contact Dehn surgery along a Legendrian link L in the standard tight contact 3-sphere. We define and study various versions of contact surgery numbers, the minimal number of components of a surgery link L describing a given contact 3-manifold under consideration. In the first part of the pap

Jiming Ma, Fangting Zheng

In this paper, we obtain the complete classification for compact hyperbolic Coxeter four-dimensional polytopes with eight facets.

Yitian Chai, Hongyu Zhang, Beijun Shen, Xiaodong Gu

Recently, pre-trained programming language models such as CodeBERT have demonstrated substantial gains in code search. Despite showing great performance, they rely on the availability of large amounts of parallel data to fine-tune the semantic mappings between queries and code. This restricts their practicality in domain-specific languages with relatively sc

Talia Baravi, Ofer Feinerman, Oren Raz

The echo-chamber effect is a common term in opinion dynamic modeling to describe how a person&#39;s opinion might be artificially enhanced as it is reflected back at her through social interactions. Here, we study the existence of this effect in statistical mechanics models, which are commonly used to study opinion dynamics. We show that the Ising model does

Xingjian Xu, Minghua Chen

Data-driven discovery of partial differential equations (PDEs) from observed data in machine learning has been developed by embedding the discovery problem. Recently, the discovery of traditional ODEs dynamics using linear multistep methods in deep learning have been discussed in [Racheal and Du, SIAM J. Numer. Anal. 59 (2021) 429-455; Du et al. arXiv:2103.1

Jun Lu

In 1954, Alston S. Householder published Principles of Numerical Analysis, one of the first modern treatments on matrix decomposition that favored a (block) LU decomposition-the factorization of a matrix into the product of lower and upper triangular matrices. And now, matrix decomposition has become a core technology in machine learning, largely due to the

Luca Schumann, Trinh Viet Doan, Tanya Shreedhar, Ricky Mok

The rapid deployment of new Internet protocols over the last few years and the COVID-19 pandemic more recently (2020) has resulted in a change in the Internet traffic composition. Consequently, an updated microscopic view of traffic shares is needed to understand how the Internet is evolving to capture both such shorter- and longer-term events. Toward this e

Jiho Song, Seong-Hwan Hyun, Jong-Ho Lee, Jeongsik Choi

We develop joint vehicle tracking and road side unit (RSU) selection algorithms suitable for vehicle-to-infrastructure (V2I) communications. We first design an analytical framework for evaluating vehicle tracking systems based on the extended Kalman filter. A simple, yet effective, metric that quantifies the vehicle tracking performance is derived in terms o

Yuxing Wang, Tiantian Zhang, Yongzhe Chang, Bin Liang

The integration of Reinforcement Learning (RL) and Evolutionary Algorithms (EAs) aims at simultaneously exploiting the sample efficiency as well as the diversity and robustness of the two paradigms. Recently, hybrid learning frameworks based on this principle have achieved great success in various challenging robot control tasks. However, in these methods, p

Kenshiro Tashiro

In this paper, we give a systolic inequality for a quotient space of a Carnot group $Γ\backslash G$ with Popp&#39;s volume. Namely we show the existence of a positive constant $C$ such that the systole of $Γ\backslash G$ is less than ${\rm Cvol}(Γ\backslash G)^{\frac{1}{Q}}$, where $Q$ is the Hausdorff dimension. Moreover, the constant depends only on the di

Santanu Mondal, Krishnendu Paul, Shameek Paul

For a weight-set $A\subseteq \mathbb Z_n$, the $A$-weighted zero-sum constant $C_A(n)$ is defined to be the smallest natural number $k$, such that any sequence of $k$ elements in $\mathbb Z_n$ has an $A$-weighted zero-sum subsequence of consecutive terms. A sequence of length $C_A(n)-1$ in $\mathbb Z_n$ which does not have any $A$-weighted zero-sum subsequen

Xiaoyu Zhao, Jun Li, Qinghua Guo

Analog neural networks are highly effective to solve some optimization problems, and they have been used for target localization in distributed multiple-input multiple-output (MIMO) radar. In this work, we design a new relaxed energy function based neural network (RNFNN) for target localization in distributed MIMO radar. We start with the maximum likelihood

Shenghao Hua, Bingrong Huang

In this paper, we prove the conjectured order lower bound for the $k$-th moment of central values of quadratic twisted self-dual $\textrm{GL}(3)$ $L$-functions for all $k\geq 1$, based on our recent work on the twisted first moment of central values in this family of $L$-functions.

Kunle Adegoke, Robert Frontczak, Taras Goy

We study a certain family of infinite series with reciprocal Catalan numbers. We first evaluate two special candidates of the family in closed form, where we also present some Catalan-Fibonacci relations. Then we focus on the general properties of the family and prove explicit formulas, including two types of integral representations.

Chandan Singh Dalawat

This update to my article on Congruent numbers, elliptic curves, and the passage from the local to the global, which appeared in Resonance, December 2009, pp. 1183--1205 (https://www.ias.ac.in/describe/article/reso/014/12/1183-1205) and was posted here as arXiv:0704.3783, covers a few recent advances in the arithmetic of elliptic curves with special referenc

Casey Cartwright, Benjamin Harms, Matthias Kaminski, Ronny Thomale

We study phase transitions in five-dimensional Einstein Gravity with a negative cosmological constant, coupled to a Skyrme matter field. These transitions are topological generalizations of the Hawking-Page transition between thermal Anti de Sitter (AdS) spacetime and an AdS black hole. Phases are characterized by a topological number associated with the Sky

Max Wenqiang Xu, Yunkun Zhou

We prove that the size of the product set of any finite arithmetic progression $\mathcal{A}\subset \mathbb{Z}$ satisfies \[|\mathcal A \cdot \mathcal A| \ge \frac{|\mathcal A|^2}{(\log |\mathcal A|)^{2\theta +o(1)} } ,\] where $2\theta=1-(1+\log\log 2)/(\log 2)$ is the constant appearing in the celebrated Erd\H{o}s multiplication table problem. This confirms

Muhammad Aitsam

Data privacy is a major issue for many decades, several techniques have been developed to make sure individuals' privacy but still world has seen privacy failures. In 2006, Cynthia Dwork gave the idea of Differential Privacy which gave strong theoretical guarantees for data privacy. Many companies and research institutes developed differential privacy librar

Qiang Heng, Hua Zhou, Eric C. Chi

Proximal Markov Chain Monte Carlo is a novel construct that lies at the intersection of Bayesian computation and convex optimization, which helped popularize the use of nondifferentiable priors in Bayesian statistics. Existing formulations of proximal MCMC, however, require hyperparameters and regularization parameters to be prespecified. In this work, we ex

Tanay Roy, Liang Jiang, David I. Schuster

Grover's quantum search algorithm provides a quadratic quantum advantage over classical algorithms across a broad class of unstructured search problems. The original protocol is probabilistic, returning the desired result with significant probability on each query, but in general, requiring several iterations of the algorithm. We present a modified version t

Christopher J. Geoga, Oana Marin, Michel Schanen, Michael L. Stein

The Matérn covariance function is ubiquitous in the application of Gaussian processes to spatial statistics and beyond. Perhaps the most important reason for this is that the smoothness parameter $ν$ gives complete control over the mean-square differentiability of the process, which has significant implications for the behavior of estimated quantities such a

Moo K. Chung, Shih-Gu Huang, Ian C. Carroll, Vince D. Calhoun

We introduce an innovative, data-driven topological data analysis (TDA) technique for estimating the state spaces of dynamically changing functional human brain networks at rest. Our method utilizes the Wasserstein distance to measure topological differences, enabling the clustering of brain networks into distinct topological states. This technique outperfor

Seonmi Choi, Seongjeong Kim

M. Niebrzydowski and J. H. Przytycki defined a Kauffman bracket magma and constructed the invariant P of framed links in 3-space. The invariant is closely related to the Kauffman bracket polynomial. The normalized bracket polynomial is obtained from the Kauffman bracket polynomial by the multiplication of indeterminate and it is an ambient isotopy invariant

Seong-Yeop Jeong, Daniel Verscharen, Christian Vocks, Joel B. Abraham

We propose a transport theory for the kinetic evolution of solar-wind electrons in the heliosphere. We derive a gyro-averaged kinetic transport equation that accounts for the spherical expansion of the solar wind and the geometry of the Parker-spiral magnetic field. To solve our three-dimensional kinetic equation, we develop a mathematical approach that comb

Daniel Herden, Jonathan Meddaugh, Mark Sepanski, Isaac Echols

The $P_3$-hull number of a graph is the minimum cardinality of an infecting set of vertices that will eventually infect the entire graph under the rule that uninfected nodes become infected if two or more neighbors are infected. In this paper, we study the $P_3$-hull number for generalized Petersen graphs and a number of closely related graphs that arise fro

Asifa Yousaf

Stability and control of a non-linear system represent an important system configuration that frequently arises in practical engineering. Stability covers a vast range of systems that do not obey the superposition principle and applies to more real-world systems because all real control systems are non-linear. For efficient stabilization of these systems, a

Devendra Prasad

Let $P(x) \in \mathbb{Z}[x]$ be a polynomial. We give an easy and new proof of the fact that the set of primes $p$ such that $p \mid P(n)$, for some $n \in \mathbb{Z}$, is infinite. We also get analog of this result for some special domains.

M. R. Setare, M. Koohgard

We extend the reflected entropy to the bipartite state in a two dimensional Galilean conformal field theory ($GCFT_2$) which is dual to the asymptotically flat spacetime described by the generalized minimal massive gravity (GMMG). To this end we consider the Renyi entanglement entropy formula that can be related to the reflected entropy by some manipulations

David Barina

X3 is a lossless optimizing dictionary-based data compressor. The algorithm uses a combination of a dictionary, context modeling, and arithmetic coding. Optimization adds the ability to find the most appropriate parameters for each file. Even without optimization, x3 can compress data with a compression ratio comparable to the best dictionary compression met

Mohamad Kazem Shirani Faradonbeh, Aditya Modi

Learning-based control of linear systems received a lot of attentions recently. In popular settings, the true dynamical models are unknown to the decision-maker and need to be interactively learned by applying control inputs to the systems. Unlike the matured literature of efficient reinforcement learning policies for adaptive control of a single system, res

Kshitija Taywade, Brent Harrison, Adib Bagh

We investigate the use of a multi-agent multi-armed bandit (MA-MAB) setting for modeling repeated Cournot oligopoly games, where the firms acting as agents choose from the set of arms representing production quantity (a discrete value). Agents interact with separate and independent bandit problems. In this formulation, each agent makes sequential choices amo

Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu

Over the past several years, legal applications of deep learning have been on the rise. However, as with other high-stakes decision making areas, the requirement for interpretability is of crucial importance. Current models utilized by legal practitioners are more of the conventional machine learning type, wherein they are inherently interpretable, yet unabl

Jyotshana V. Prajapat, Anoop Varghese

We classify the geodetically convex sets and geodetically convex functions on the Heisenberg group ${\mathbb H}^n$, $n\geq 1$.

Oana Marin, Christopher Geoga, Michel Schanen

To target challenges in differentiable optimization we analyze and propose strategies for derivatives of the Matérn kernel with respect to the smoothness parameter. This problem is of high interest in Gaussian processes modelling due to the lack of robust derivatives of the modified Bessel function of second kind with respect to order. In the current work we

Jizhou Li, Bin Chen, Guibin Zan, Guannan Qian

Resolving morphological chemical phase transformations at the nanoscale is of vital importance to many scientific and industrial applications across various disciplines. The TXM-XANES imaging technique, by combining full field transmission X-ray microscopy (TXM) and X-ray absorption near edge structure (XANES), has been an emerging tool which operates by acq

Warren B Powell, Saeed Ghadimi

The most common approaches for solving multistage stochastic programming problems in the research literature have been to either use value functions (&#34;dynamic programming&#34;) or scenario trees (&#34;stochastic programming&#34;) to approximate the impact of a decision now on the future. By contrast, common industry practice is to use a deterministic app

Tapesh Yadav

For a sufficiently nice 2 dimensional shape, we define its approximating matrix (or patterned matrix) as a random matrix with iid entries arranged according to a given pattern. For large approximating matrices, we observe that the eigenvalues roughly follow an underlying distribution. This phenomenon is similar to the classical observation on Wigner matrices

Nicholas Dyson, Benedikt Ahrens, Jacopo Emmenegger

In this work, we describe our experience in learning the use of a computer proof assistant - specifically, Lean - from scratch, through proving formulae for the solutions of polynomial equations. Specifically, in this work we characterize the solutions of quadratic, cubic, and quartic polynomials over certain fields, specifically, fields with operations retu

Junghyun Bae, Stylianos Chatzidakis

Cosmic ray muons have been considered as a non-conventional radiation probe in various applications. To utilize cosmic ray muons in engineering applications, two important quantities, trajectory and momentum, must be known. The muon trajectories are easily reconstructed using two-fold detector arrays with a high spatial resolution. However, precise measureme

Vitaly V. Chaban

The development of novel task-specific ionic liquids (ILs) represents an essential challenge in modern organic and physical chemistries. Recently we reported surface-active ILs contained the two well-known organic cations (1-butyl-3-methylimidazolium and tetrabutylammonium) and the two surface-active anions (lauryl sulfate, lauryl ether sulfate). In the pres

E. M. Campo, S. Shankar, A. S. Szalay, R. J. Hanisch

A call for coordinated action from government, academia, and industry.

K. N. Telikova, S. A. Balashev, P. Noterdaeme, J. -K. Krogager

We present a spectroscopic investigation with VLT/X-shooter of seven candidate extremely strong damped Lyman-$α$ absorption systems (ESDLAs, $N(\text{HI})\ge 5\times 10^{21}$ cm$^{-2}$) observed along quasar sightlines. We confirm the extremely high column densities, albeit slightly (0.1~dex) lower than the original ESDLA definition for four systems. We meas

Emmanuel Duplay, Zhuo Fan Bao, Sebastian Rodriguez Rosero, Arnab Sinha

The application of directed energy to spacecraft mission design is explored using rapid transit to Mars as the design objective. An Earth-based laser array of unprecedented size (10~m diameter) and power (100~MW) is assumed to be enabled by ongoing developments in photonic laser technology. A phased-array laser of this size and incorporating atmospheric comp

Eva M. Campo

This paper identifies the challenges associated with coordinating the development of new research methodologies and an accelerated pace of new discoveries in materials science with slower-evolving textbooks and curricula. The target audience is the undergraduate to post-graduate educational community, but implications for the K-12 pipeline are also considere

Martin Törngren, Haydn Thompson, Erik Herzog, Rafia Inam

Industry is moving towards advanced Cyber-Physical Systems (CPS), with trends in smartness, automation, connectivity and collaboration. We examine the drivers and requirements for the use of edge computing in critical industrial applications. Our purpose is to provide a better understanding of industrial needs and to initiate a discussion on what role edge c

Dominik Bauer, Timothy Patten, Markus Vincze

Observational noise, inaccurate segmentation and ambiguity due to symmetry and occlusion lead to inaccurate object pose estimates. While depth- and RGB-based pose refinement approaches increase the accuracy of the resulting pose estimates, they are susceptible to ambiguity in the observation as they consider visual alignment. We propose to leverage the fact

Changchuan Yin

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current global COVID-19 pandemic, in which millions of lives have been lost. Understanding the zoonotic evolution of the coronavirus may provide insights for developing effective vaccines, monitoring the transmission trends, and preventing new zoonotic infections. Homo

Thuy T. Do, Du Nguyen, Anh Le, Anh Nguyen

Hydroxychloroquine (HCQ) is used to prevent or treat malaria caused by mosquito bites. Recently, the drug has been suggested to treat COVID-19, but that has not been supported by scientific evidence. The information regarding the drug efficacy has flooded social networks, posting potential threats to the community by perverting their perceptions of the drug

Ziyang Tang, Yihao Feng, Qiang Liu

Reinforcement learning (RL) has drawn increasing interests in recent years due to its tremendous success in various applications. However, standard RL algorithms can only be applied for single reward function, and cannot adapt to an unseen reward function quickly. In this paper, we advocate a general operator view of reinforcement learning, which enables us

Zhenduo Wang, Qingyao Ai

In conversational search, agents can interact with users by asking clarifying questions to increase their chance to find better results. Many recent works and shared tasks in both NLP and IR communities have focused on identifying the need of asking clarifying questions and methodologies of generating them. These works assume asking clarifying questions is a

Eason Li, Franc Brglez

We consider instances of bipartite graphs and a number of asymptotic performance experiments in three projects: (1) top movie lists, given databases of movies and viewers, (2) maximum matchings, and (3) minimum set covers. Experiments are designed to measure the asymptotic runtime performance of abstract data types (ADTs) in three programming languages: Java

Enyan Dai, Wei Jin, Hui Liu, Suhang Wang

Graph Neural Networks (GNNs) have shown their great ability in modeling graph structured data. However, real-world graphs usually contain structure noises and have limited labeled nodes. The performance of GNNs would drop significantly when trained on such graphs, which hinders the adoption of GNNs on many applications. Thus, it is important to develop noise

Montassar Naghmouchi, Hella Kaffel, Maryline Laurent

Nowadays, open standards for self-sovereign identity and access management enable portable solutions that are following the requirements of IoT systems. This paper proposes a blockchain-based identity and access management system for IoT -- specifically smart vehicles -- as an example of use-case, showing two interoperable blockchains, Ethereum and Hyperledg

Juntao Duan, Ionel Popescu, Heinrich Matzinger

It is well known the sample covariance has a consistent bias in the spectrum, for example spectrum of Wishart matrix follows the Marchenko-Pastur law. We in this work introduce an iterative algorithm &#39;Concent&#39; that actively eliminate this bias and recover the true spectrum for small and moderate dimensions.

Panagiotis Skrimponis, Seongjoon Kang, Abbas Khalili, Wonho Lee

Power consumption is a key challenge in millimeter wave (mmWave) receiver front-ends, due to the need to support high dimensional antenna arrays at wide bandwidths. Recently, there has been considerable work in developing low-power front-ends, often based on low-resolution ADCs and low-power mixers. A critical but less studied consequence of such designs is

Hesamoddin Hosseini, Reza Monsefi, Shabnam Shadroo

Lung cancer has been one of the most prevalent disease in recent years. According to the research of this field, more than 200,000 cases are identified each year in the US. Uncontrolled multiplication and growth of the lung cells result in malignant tumour formation. Recently, deep learning algorithms, especially Convolutional Neural Networks (CNN), have bec

Rafał Mirek, Andrzej Opala, Magdalena Furman, Mateusz Król

We demonstrate that time-delayed nonlinear effects in exciton-polaritons can be used to construct neural networks where information is coded in optical pulses arriving consecutively on the sample. The highly nonlinear effects are induced by time-dependent interactions with the excitonic reservoir. These nonlinearities allow to create a nonlinear XOR logic ga