May 2020 arXiv papers — page 17

Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim

One of the most crucial challenges in question answering (QA) is the scarcity of labeled data, since it is costly to obtain question-answer (QA) pairs for a target text domain with human annotation. An alternative approach to tackle the problem is to use automatically generated QA pairs from either the problem context or from large amount of unstructured tex

Seung-Ho Baek, Hyeon Woo Yeo, Seung-Hwan Do, Kwang-Yong Choi

We report a $^{35}$Cl nuclear magnetic resonance (NMR) study of the diluted Kitaev material $\alpha$-Ru$_{1-x}$Ir$_x$Cl$_3$ ($x=0.1$ and $0.2$) where non-magnetic Ir$^{3+}$ dopants substitute Ru$^{3+}$ ions. Upon dilution, the $^{35}$Cl spectra exhibit unusual large magnetic inhomogeneity, which sets in at temperatures below the Kitaev exchange energy scale.

Da-Yi Wu, Yi-Hsuan Yang

This paper investigates the use of generative adversarial network (GAN)-based models for converting the spectrogram of a speech signal into that of a singing one, without reference to the phoneme sequence underlying the speech. This is achieved by viewing speech-to-singing conversion as a style transfer problem. Specifically, given a speech input, and option

Félix Parraud

Let $U^N = (U_1^N,\dots, U^N_p)$ be a d-tuple of $N\times N$ independent Haar unitary matrices and $Z^{NM}$ be any family of deterministic matrices in $\mathbb{M}_N(\mathbb{C})\otimes \mathbb{M}_M(\mathbb{C})$. Let $P$ be a self-adjoint non-commutative polynomial. In 1998, Voiculescu showed that the empirical measure of the eigenvalues of this polynomial eva

So Okano, Tomohiro Fujita

We investigate the gravitational wave production induced by the primordial magnetic fields in a parity-violating magnetogenesis model. It is shown that the gravitational waves detectable by LISA, DECIGO or BBO and the magnetic fields strong enough to explain the blazar observation can be simultaneously produced. The magnetic fields and the gravitational wave

Svante Janson

We explore the tree limits recently defined by Elek and Tardos. In particular, we find tree limits for many classes of random trees. We give general theorems for three classes of conditional Galton-Watson trees and simply generated trees, for split trees and generalized split trees (as defined here), and for trees defined by a continuous-time branching proce

Natesh Ganesh

In their paper 'Falsification and Consciousness' [1], Kleiner and Hoel introduced a formal mathematical model of the process of generating observable data from experiments and using that data to generate inferences and predictions onto an experience space. The resulting substitution argument built on this framework was used to show that any theory of conscio

Christian Dehm, Thai Nguyen, Mitja Stadje

We consider an expected utility maximization problem where the utility function is not necessarily concave and the time horizon is uncertain. We establish a necessary and sufficient condition for the optimality for general non-concave utility function in a complete financial market. We show that the general concavification approach of the utility function to

Alistair O. Hodson, Antonaldo Diaferio, Luisa Ostorero

We derive the distribution of the phantom dark matter in the eight classical dwarf galaxies surrounding the Milky Way, under the assumption that modified Newtonian dynamics (MOND) is the correct theory of gravity. According to their observed shape, we model the dwarfs as axisymmetric systems, rather than spherical systems, as usually assumed. In addition, as

Yitong Ji, Aixin Sun, Jie Zhang, Chenliang Li

Popularity is often included in experimental evaluation to provide a reference performance for a recommendation task. To understand how popularity baseline is defined and evaluated, we sample 12 papers from top-tier conferences including KDD, WWW, SIGIR, and RecSys, and 6 open source toolkits. We note that the widely adopted MostPop baseline simply ranks ite

Geng-Li Zhang, Di Liu, Xi-Ming Wang, Man-Hong Yung

Exceptional points (EPs), the degeneracy point of non-Hermitian systems, have recently attracted great attention after its ability to greatly enhance the sensitivity of micro-cavities is demonstrated experimentally. Unlike the usual degeneracies in Hermitian systems, at EPs, both the eigenenergies and eigenvectors coalesce. Although some of the exotic proper

Mittul Singh, Sami Virpioja, Peter Smit, Mikko Kurimo

In spoken Keyword Search, the query may contain out-of-vocabulary (OOV) words not observed when training the speech recognition system. Using subword language models (LMs) in the first-pass recognition makes it possible to recognize the OOV words, but even the subword n-gram LMs suffer from data sparsity. Recurrent Neural Network (RNN) LMs alleviate the spar

Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng

Few-shot learning (FSL) has attracted increasing attention in recent years but remains challenging, due to the intrinsic difficulty in learning to generalize from a few examples. This paper proposes an adaptive margin principle to improve the generalization ability of metric-based meta-learning approaches for few-shot learning problems. Specifically, we firs

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt

Dynamic optimization problems have gained significant attention in evolutionary computation as evolutionary algorithms (EAs) can easily adapt to changing environments. We show that EAs can solve the graph coloring problem for bipartite graphs more efficiently by using dynamic optimization. In our approach the graph instance is given incrementally such that t

Mikołaj Marciniak, Łukasz Maślanka, Piotr Śniady

We consider Robinson-Schensted-Knuth algorithm applied to a random input and study the growth of the bottom rows of the corresponding Young diagrams. We prove multidimensional Poisson limit theorem for the resulting Plancherel growth process. In this way we extend the result of Aldous and Diaconis to more than just one row. This result can be interpreted as

Behnam Pourghassemi, Chenghao Zhang, Joo Hwan Lee, Aparna Chandramowlishwaran

GPUs are currently the platform of choice for training neural networks. However, training a deep neural network (DNN) is a time-consuming process even on GPUs because of the massive number of parameters that have to be learned. As a result, accelerating DNN training has been an area of significant research in the last couple of years. While earlier networks

Takuya Furusawa, Yuya Tanizaki, Etsuko Itou

We study the phase diagram of two-flavor massless two-color QCD (QC$_2$D) under the presence of quark chemical potentials and imaginary isospin chemical potentials. At the special point of the imaginary isospin chemical potential, called the isospin Roberge--Weiss (RW) point, two-flavor QC$_2$D enjoys the $\mathbb{Z}_2$ center symmetry that acts on both quar

Marc Noy, Clément Requilé, Juanjo Rué

A well-known conjecture by Lov\'asz and Plummer from the 1970s asserted that a bridgeless cubic graph has exponentially many perfect matchings. It was solved in the affirmative by Esperet et al. (Adv. Math. 2011). On the other hand, Chudnovsky and Seymour (Combinatorica 2012) proved the conjecture in the special case of cubic planar graphs. In our work we co

Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu

The challenges of high intra-class variance yet low inter-class fluctuations in fine-grained visual categorization are more severe with few labeled samples, \textit{i.e.,} Fine-Grained categorization problems under the Few-Shot setting (FGFS). High-order features are usually developed to uncover subtle differences between sub-categories in FGFS, but they are

Taro Kanao, Hayato Goto

A two-dimensional array of Kerr-nonlinear parametric oscillators (KPOs) with local four-body interactions is a promising candidate for realizing an Ising machine with all-to-all spin couplings, based on adiabatic quantum computation in the Lechner-Hauke-Zoller (LHZ) scheme. However its performance has been evaluated for only a few KPOs. By numerically simula

He Huang, Martin Pouls, Anne Meyer, Markus Pauly

In this paper, we consider the task of predicting travel times between two arbitrary points in an urban scenario. We view this problem from two temporal perspectives: long-term forecasting with a horizon of several days and short-term forecasting with a horizon of one hour. Both of these perspectives are relevant for planning tasks in the context of urban mo

Moustafa Sayem El-Daher

In an attempt to test the possibility of solving the inverse problem for liquid metals i.e. obtaining the effective pair potential from the experimental structure factor, we solve the modified Hypernetted-Chain Integral equation for liquid aluminum at melting temperature to obtain the effective pair potential starting from the experimental structure factor a

Songyuan Li, Jan Troost

We construct a string theory in three-dimensional anti-de Sitter space-time that is independent of the boundary metric. It is a topologically twisted theory of quantum gravity. We study string theories with an asymptotic N=2 superconformal symmetry and demonstrate that, when the world sheet coupling to the space-time boundary metric undergoes a U(1) R-symmet

Michael Baddeley, Carlo Alberto Boano, Antonio Escobar-Molero, Ye Liu

The popularity of concurrent transmissions (CT) has soared after recent studies have shown their feasibility on the four physical layers specified by BLE 5, hence providing an alternative to the use of IEEE 802.15.4 for the design of reliable and efficient low-power wireless protocols. However, to date, the extent to which physical layer properties affect th

Nam Ho-Nguyen, Stephen J. Wright

We study a model for adversarial classification based on distributionally robust chance constraints. We show that under Wasserstein ambiguity, the model aims to minimize the conditional value-at-risk of the distance to misclassification, and we explore links to adversarial classification models proposed earlier and to maximum-margin classifiers. We also prov

D. R. Grigore

The tensor Feynman amplitudes are reduced to scalar integrals by a procedure of Passarino and Veltman. We provide an alternative approach based on the causal formalism.

Georgios Karachalias, Matija Pretnar, Amr Hany Saleh, Stien Vanderhallen

As popularity of algebraic effects and handlers increases, so does a demand for their efficient execution. Eff, an ML-like language with native support for handlers, has a subtyping-based effect system on which an effect-aware optimizing compiler could be built. Unfortunately, in our experience, implementing optimizations for Eff is overly error-prone becaus

Ahmed Shafee, Mostafa M. Fouda, Mohamed Mahmoud, Waleed Alasmary

The simultaneous charging of many electric vehicles (EVs) stresses the distribution system and may cause grid instability in severe cases. The best way to avoid this problem is by charging coordination. The idea is that the EVs should report data (such as state-of-charge (SoC) of the battery) to run a mechanism to prioritize the charging requests and select

Ram Govind Singh, Sushmita Ruj

The Indian Personal Data Protection Bill 2019 provides a legal framework for protecting personal data. It is modeled after the European Union's General Data Protection Regulation(GDPR). We present a detailed description of the Bill, the differences with GDPR, the challenges and limitations in implementing it. We look at the technical aspects of the bill and

Thomas Studer

Controlled query evaluation (CQE) is an approach to guarantee data privacy for database and knowledge base systems. CQE-systems feature a censor function that may distort the answer to a query in order to hide sensitive information. We introduce a high-level formalization of controlled query evaluation and define several desirable properties of CQE-systems.

Ziv Vasilisky, Moshe Tennenholtz, Oren Kurland

The ranking incentives of many authors of Web pages play an important role in the Web dynamics. That is, authors who opt to have their pages highly ranked for queries of interest, often respond to rankings for these queries by manipulating their pages; the goal is to improve the pages' future rankings. Various theoretical aspects of this dynamics have recent

Ryotaro Kase, Shinji Tsujikawa

For a scalar field $\phi$ coupled to cold dark matter (CDM), we provide a general framework for studying the background and perturbation dynamics on the isotropic cosmological background. The dark energy sector is described by a Horndeski Lagrangian with the speed of gravitational waves equivalent to that of light, whereas CDM is dealt as a perfect fluid cha

Ali Ahmadvand

User intent understanding is a crucial step in designing both conversational agents and search engines. Detecting or inferring user intent is challenging, since the user utterances or queries can be short, ambiguous, and contextually dependent. To address these research challenges, my thesis work focuses on: 1) Utterance topic and intent classification for c

Carmen Amo Alonso, Nikolai Matni, James Anderson

An explicit Model Predictive Control algorithm for large-scale structured linear systems is presented. We base our results on Distributed and Localized Model Predictive Control (DLMPC), a closed-loop model predictive control scheme based on the System Level Synthesis (SLS) framework wherein only local state and model information needs to be exchanged between

Wenyang Qian, Shaoyang Jia, Yang Li, James P. Vary

We study the light-unflavored mesons as relativistic bound states in the nonperturbative Hamiltonian formalism of the basis light-front quantization (BLFQ) approach. The dynamics for the valence quarks of these mesons is specified by an effective Hamiltonian containing the one-gluon exchange interaction and the confining potentials both introduced in our pre

Alessandro Palmieri

In this note, we study the semilinear wave equation with power nonlinearity $|u|^p$ on compact Lie groups. First, we prove a local in time existence result in the energy space via Fourier analysis on compact Lie groups. Then, we prove a blow-up result for the semilinear Cauchy problem for any $p>1$, under suitable sign assumptions for the initial data. Furth

Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw

Averting the effects of anthropogenic climate change requires a transition from fossil fuels to low-carbon technology. A way to achieve this is to decarbonize the electricity grid. However, further efforts must be made in other fields such as transport and heating for full decarbonization. This would reduce carbon emissions due to electricity generation, and

Rizky Reza Fauzi, Yoshihiko Maesono

We propose two new kernel-type estimators of the mean residual life function $m_X(t)$ of bounded or half-bounded interval supported distributions. Though not as severe as the boundary problems in the kernel density estimation, eliminating the boundary bias problems that occur in the naive kernel estimator of the mean residual life function is needed. In this

Ali Ahmadvand, Jason Ingyu Choi, Eugene Agichtein

Classifying the general intent of the user utterance in a conversation, also known as Dialogue Act (DA), e.g., open-ended question, statement of opinion, or request for an opinion, is a key step in Natural Language Understanding (NLU) for conversational agents. While DA classification has been extensively studied in human-human conversations, it has not been

A. Wang, A. Ludu, Z. Zong, L. Zou

Experimental results describing random, uni-directional, long crested, water waves over non-uniform bathymetry confirm the formation of stable coherent wave packages traveling with almost uniform group velocity. The waves are generated with JONSWAP spectrum for various steepness, height and constant period. A set of statistical procedures were applied to the

Ali Ahmadvand, Harshita Sahijwani, Eugene Agichtein

To hold a true conversation, an intelligent agent should be able to occasionally take initiative and recommend the next natural conversation topic. This is a challenging task. A topic suggested by the agent should be relevant to the person, appropriate for the conversation context, and the agent should have something interesting to say about it. Thus, a scri

Chun-Kit Lai, Bochen Liu, Hal Prince

We consider \textit{additive spaces}, consisting of two intervals of unit length or two general probability measures on ${\mathbb R}^1$, positioned on the axes in ${\mathbb R}^2$, with a natural additive measure $\rho$. We study the relationship between the exponential frames, Riesz bases, and orthonormal bases of $L^2(\rho)$ and those of its component space

Yoshifumi Nakata, Tadashi Takayanagi, Yusuke Taki, Kotaro Tamaoka

We introduce a quantity, called pseudo entropy, as a generalization of entanglement entropy via post-selection. In the AdS/CFT correspondence, this quantity is dual to areas of minimal area surfaces in time-dependent Euclidean spaces which are asymptotically AdS. We study its basic properties and classifications in qubit systems. In specific examples, we pro

Vesa Julin, Joonas Niinikoski

We prove a new quantitative version of the Alexandrov theorem which states that if the mean curvature of a regular set in R^{n+1} is close to a constant in L^{n}-sense, then the set is close to a union of disjoint balls with respect to the Hausdorff distance. This result is more general than the previous quantifications of the Alexandrov theorem and using it

Amitojdeep Singh, Sourya Sengupta, Vasudevan Lakshminarayanan

Deep learning methods have been very effective for a variety of medical diagnostic tasks and has even beaten human experts on some of those. However, the black-box nature of the algorithms has restricted clinical use. Recent explainability studies aim to show the features that influence the decision of a model the most. The majority of literature reviews of

Ali Ahmadvand, Harshita Sahijwani, Jason Ingyu Choi, Eugene Agichtein

Identifying the topic (domain) of each user's utterance in open-domain conversational systems is a crucial step for all subsequent language understanding and response tasks. In particular, for complex domains, an utterance is often routed to a single component responsible for that domain. Thus, correctly mapping a user utterance to the right domain is critic

Michael Shin, Eduardo Castillo, Irene Font Peradejordi, Shobhna Jayaraman

In this work, we demonstrate that receptive fields in 3D pose estimation can be effectively specified using optical flow. We introduce adaptive receptive fields, a simple and effective method to aid receptive field selection in pose estimation models based on optical flow inference. We contrast the performance of a benchmark state-of-the-art model running on

Zejiang Hou, Sun-Yuan Kung

Network pruning has become the de facto tool to accelerate deep neural networks for mobile and edge applications. Recently, feature-map discriminant based channel pruning has shown promising results, as it aligns well with the CNN objective of differentiating multiple classes and offers better interpretability of the pruning decision. However, existing discr

Akihiro Higashitani, Kazuki Kurimoto, Mikiya Masuda

The cohomological rigidity problem for toric manifolds asks whether toric manifolds are diffeomorphic (or homeomorphic) if their integral cohomology rings are isomorphic. Many affirmative partial solutions to the problem have been obtained and no counterexample is known. In this paper, we study the diffeomorphism classification of toric Fano $d$-folds with $

Rizky Reza Fauzi, Yoshihiko Maesono

We propose kernel-type smoothed Kolmogorov-Smirnov and Cram\'{e}r-von Mises tests for data on general interval, using bijective transformations. Though not as severe as in the kernel density estimation, utilizing naive kernel method directly to those particular tests will result in boundary problem as well. This happens mostly because the value of the naive

Mohamed I. Ibrahem, Mahmoud Nabil, Mostafa M. Fouda, Mohamed Mahmoud

In advanced metering infrastructure (AMI), smart meters (SMs) are installed at the consumer side to send fine-grained power consumption readings periodically to the system operator (SO) for load monitoring, energy management, billing, etc. However, fraudulent consumers launch electricity theft cyber-attacks by reporting false readings to reduce their bills i

Yan-Wei Li, Massimo Pica Ciamarra

Two-dimensional systems may admit a hexatic phase and hexatic-liquid transitions of different natures. The determination of their phase diagrams proved challenging, and indeed those of hard-disks, hard regular polygons, and inverse power-law potentials, have been only recently clarified. In this context, the role of attractive forces is currently speculative

Ilya Gorshkov, Alexey Staroletov

Axial algebras of Jordan type $\eta$ are commutative algebras generated by idempotents whose adjoint operators have the minimal polynomial dividing $(x-1)x(x-\eta)$, where $\eta\not\in\{0,1\}$ is fixed, with restrictive multiplication rules. These properties generalize the Pierce decompositions for idempotents in Jordan algebras, where $\frac{1}{2}$ is repla

I. Satokangas, S. H. Martin, H. Helanterä, J. Saramäki

All genes interact with other genes, and their additive effects and epistatic interactions affect an organism's phenotype and fitness. Recent theoretical and empirical work has advanced our understanding of the role of multi-locus interactions in speciation. However, relating different models to one another and to empirical observations is challenging. This

Wanjing Wei, Yangzihao Wang, Pin Gao, Shijie Sun

Real-world node embedding applications often contain hundreds of billions of edges with high-dimension node features. Scaling node embedding systems to efficiently support these applications remains a challenging problem. In this paper we present a high-performance multi-GPU node embedding system. It uses model parallelism to split node embeddings onto each

Ioannis Koukoutsidis

We show how to calculate the Age of Information in an overtake-free network of quasi-reversible queues, with exponential exogenous interarrivals of multiple classes of update packets and exponential service times at all nodes. Results are provided for any number of M/M/1 First-Come-First-Served (FCFS) queues in tandem, and for a network with two classes of u

Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague

We consider the privacy-preserving computation of node influence in distributed social networks, as measured by egocentric betweenness centrality (EBC). Motivated by modern communication networks spanning multiple providers, we show for the first time how multiple mutually-distrusting parties can successfully compute node EBC while revealing only differentia

Adam L. Gross, Yasen Hou, Antonio Rossi, Dong Yu

$\text{Bi}_2\text{Se}_3$ is an ideal three-dimensional topological insulator in which the chemical potential can be brought into the bulk band gap with antimony doping. Here, we utilize ultrafast time-resolved transient reflectivity to characterize the photoexcited carrier decay in $\text{Bi}_{2-x}\text{Sb}_x\text{Se}_3$ nanoplatelets. We report a substantia

Stanislav Stoupin

X-ray scattering power of a plane parallel homogeneous slab of material is derived using radiation intensity transfer equations.The scattering power scales with the ratio of the scattering coefficient of interest to the total attenuation coefficient. The results can be used to guide the choice of slab thickness, scattering geometry and photon energy to maxim

G. Adhikari, E. Barbosa de Souza, N. Carlin, J. J. Choi

COSINE-100 is a dark matter detection experiment that uses NaI(Tl) crystal detectors operating at the Yangyang underground laboratory in Korea since September 2016. Its main goal is to test the annual modulation observed by the DAMA/LIBRA experiment with the same target medium. Recently DAMA/LIBRA has released data with an energy threshold lowered to 1 keV,

Ali Ahmadvand, Surya Kallumadi, Faizan Javed, Eugene Agichtein

An accurate understanding of a user's query intent can help improve the performance of downstream tasks such as query scoping and ranking. In the e-commerce domain, recent work in query understanding focuses on the query to product-category mapping. But, a small yet significant percentage of queries (in our website 1.5% or 33M queries in 2019) have non-comme

Jajati Keshari Sahoo, Ratikanta Behera, Sourav Das, R. N. Mohapatra

In this paper, we introduce the notion of weak core and central weak core inverse in a {\it proper $*$-ring}. We further elaborate on these two classes by producing a few representations and characterizations of the weak core and central weak core invertible elements. We investigated additive properties and a few explicit expressions for these two classes of

Behrad Toghi, Divas Grover, Mahdi Razzaghpour, Rajat Jain

Short-term future of automated driving can be imagined as a hybrid scenario in which both automated and human-driven vehicles co-exist in the same environment. In order to address the needs of such road configuration, many technology solutions such as vehicular communication and predictive control for automated vehicles have been introduced in the literature

Dharani Punithan, Byoung-Tak Zhang

We propose an in silico molecular associative memory model for pattern learning, storage and denoising using Pairwise Markov Random Field (PMRF) model. Our PMRF-based molecular associative memory model extracts locally distributed features from the exposed examples, learns and stores the patterns in the molecular associative memory and denoises the given noi

Santanu Mondal, Rajan Gupta, Sungwoo Park, Boram Yoon

We present results on the isovector momentum fraction, $\langle x \rangle_{u-d}$, helicity moment, $\langle x \rangle_{\Delta u-\Delta d}$, and the transversity moment, $\langle x \rangle_{\delta u-\delta d}$, of the nucleon obtained using nine ensembles of gauge configurations generated by the MILC collaboration using $2+1+1$-flavors of dynamical highly imp

Parth Chadha

Model-free deep reinforcement learning (RL) agents can learn an effective policy directly from repeated interactions with a black-box environment. However in practice, the algorithms often require large amounts of training experience to learn and generalize well. In addition, classic model-free learning ignores the domain information contained in the state t

John D. Clemens, Samuel Coskey, Gianni Krakoff

We introduce the computable FS-jump, an analog of the classical Friedman--Stanley jump in the context of equivalence relations on the natural numbers. We prove that the computable FS-jump is proper with respect to computable reducibility. We then study the effect of the computable FS-jump on computably enumerable equivalence relations (ceers).

Yosep Kim, Yong Siah Teo, Daekun Ahn, Dong-Gil Im

Recent quantum technologies utilize complex multidimensional processes that govern the dynamics of quantum systems. We develop an adaptive diagonal-element-probing compression technique that feasibly characterizes any unknown quantum processes using much fewer measurements compared to conventional methods. This technique utilizes compressive projective measu

Anirvan Guha, Trevor J. Kalkus, Thomas B. H. Schroeder, Oliver G. Willis

Strongly electric fish use gradients of ions within their bodies to generate stunning external electrical discharges; the most powerful of these organisms, the Atlantic torpedo ray, can produce pulses of over 1 kW from its electric organs. Despite extensive study of this phenomenon in nature, the development of artificial power generation schemes based on io

Varghese Mathai, Detlef Lohse, Chao Sun

Fluid turbulence is commonly associated with stronger drag, greater heat transfer, and more efficient mixing than in laminar flows. In many natural and industrial settings, turbulent liquid flows contain suspensions of dispersed bubbles and light particles. Recently, much attention has been devoted to understanding the behavior and underlying physics of such

Joachim Gudmundsson, Michael Horton, John Pfeifer, Martin P. Seybold

We present a scalable approach for range and $k$ nearest neighbor queries under computationally expensive metrics, like the continuous Fr\'echet distance on trajectory data. Based on clustering for metric indexes, we obtain a dynamic tree structure whose size is linear in the number of trajectories, regardless of the trajectory's individual sizes or the spat

Zhao Zhang, Kirill Amelin, Xiao Wang, Haiyuan Zou

Near the transverse-field induced quantum critical point of the Ising chain, an exotic dynamic spectrum consisting of exactly eight particles was predicted, which is uniquely described by an emergent quantum integrable field theory with the symmetry of the $E_8$ Lie algebra, but rarely explored experimentally. Here we use high-resolution terahertz spectrosco

Shenglong Zhou

Kernel-based methods for support vector machines (SVM) have shown highly advantageous performance in various applications. However, they may incur prohibitive computational costs for large-scale sample datasets. Therefore, data reduction (reducing the number of support vectors) appears to be necessary, which gives rise to the topic of the sparse SVM. Motivat

Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo

With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhibiting real threats to our society. However, effective and robust detectors for synthesized fake voices are still in their infancy and are not ready to fully tackle this emerging th

Vivek Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias

State-of-the-art under-determined audio source separation systems rely on supervised end-end training of carefully tailored neural network architectures operating either in the time or the spectral domain. However, these methods are severely challenged in terms of requiring access to expensive source level labeled data and being specific to a given set of so

Michail Savvas

Let $\sigma$ be a stability condition on the bounded derived category $D^b({\mathop{\rm Coh}\nolimits} W)$ of a Calabi-Yau threefold $W$ and $\mathcal{M}$ a moduli stack parametrizing $\sigma$-semistable objects of fixed topological type. We define generalized Donaldson-Thomas invariants which act as virtual counts of objects in $\mathcal{M}$, fully generali

Fucai Lin, Tingting Shi, Meng Bao

A discrete subset $S$ of a topological gyrogroup $G$ with the identity $0$ is said to be a {\it suitable set} for $G$ if it generates a dense subgyrogroup of $G$ and $S\cup \{0\}$ is closed in $G$. In this paper, it was proved that each countable Hausdorff topological gyrogroup has a suitable set; moreover, it is shown that each separable metrizable strongly

Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu

Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with non-pharmaceutical interventions (NPIs) such as social distancing restrictions and school and business closures. This paper demonstrates how evolutionary AI could be used to facilitate the next step, i.e. determining most effective intervention

Aidan Backus

We propose a conjecture stating that for resonances, $\lambda_j$, of a noncompactly supported potential, the series $\sum_j \operatorname{Im} \lambda_j/|\lambda_j|^2$ diverges. This series appears in the Breit-Wigner approximation for a compactly supported potential, in which case it converges. We provide heuristic motivation for this conjecture and prove it

Lee Fisher, Wei Li, Stephen P. Shipman

We construct two types of multi-layer quantum graphs (Schr\"odinger operators on metric graphs) for which the dispersion function of wave vector and energy is proved to be a polynomial in the dispersion function of the single layer. This leads to the reducibility of the algebraic Fermi surface, at any energy, into several components. Each component contribut

Emanuele Contini, Qiu Sheng Gu

We take advantage of a semi-analytic model with a state-of-art implementation of the formation of the intra-cluster light (ICL) to study the mass distribution of the ICL in galaxy groups and clusters, at different redshifts. We assume the ICL to follow a NFW profile with a different concentration, linked to that of the dark matter by the relation $c_{ICL}=\g

Maofan Yin, Hongbo Zhang, Robbert van Renesse, Emin Gün Sirer

As a result of RAM becoming cheaper, there has been a trend in key-value store design towards maintaining a fast in-memory index (such as a hash table) while logging user operations to disk, allowing high performance under failure-free conditions while still being able to recover from failures. This design, however, comes at the cost of long recovery times o

Fanjun Meng

Let $f$ be a morphism from a klt pair $(X, \Delta)$ to an abelian variety $A$, $m\geq1$ a rational number and $D$ a Cartier divisor on $X$ such that $D\sim_{\mathbb Q}m(K_X+\Delta)$. We prove that the sheaf $f_*\mathcal{O}_X(D)$ becomes globally generated after pullback by an isogeny and has the Chen-Jiang decomposition, along with some related results. Thes

Zachary Sunberg, Mykel Kochenderfer

This work examines the hypothesis that partially observable Markov decision process (POMDP) planning with human driver internal states can significantly improve both safety and efficiency in autonomous freeway driving. We evaluate this hypothesis in a simulated scenario where an autonomous car must safely perform three lane changes in rapid succession. Appro

Andrew Schopieray

We prove several results in the theory of fusion categories using the product (norm) and sum (trace) of Galois conjugates of formal codegrees. First, we prove that finitely-many fusion categories exist up to equivalence whose global dimension has a fixed norm. Furthermore, with two exceptions, all formal codegrees of spherical fusion categories with square-f

Yoshihiro Nakano

We propose a fast and accurate method of 6D object pose estimation for bin-picking of mechanical parts by a robot manipulator. We extend the single-shot approach to stereo vision by application of attention architecture. Our convolutional neural network model regresses to object locations and rotations from either a left image or a right image without depth

Takahiro Mori

In this paper, we discuss relationships between the continuous embeddings of Dirichlet spaces $(\mathcal{F}, \mathcal{E}_1)$ into Lebesgue spaces and the integrability of the associated resolvent kernel $r_\alpha(x, y)$. For a positive measure $\mu$, we consider the following two properties; the first one is that the Dirichlet space $(\mathcal{F}, \mathcal{E

Long-Bin Chen, Wei Wang, Ruilin Zhu

We present a next-to-next-to-leading order (NNLO) calculation of the quasi parton distribution functions (Quasi-PDFs) in the large momentum effective theory (LaMET). We focus on the flavor non-diagonal quark-quark channel and demonstrate the LaMET factorization at the NNLO accuracy in the modified minimal subtraction scheme. The matching coefficient between

Katharina Kann, Arya McCarthy, Garrett Nicolai, Mans Hulden

In this paper, we describe the findings of the SIGMORPHON 2020 shared task on unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel task in the field of inflectional morphology. Participants were asked to submit systems which take raw text and a list of lemmas as input, and output all inflected forms, i.e., the entire morphological

Pai Chet Ng, Petros Spachos, Konstantinos Plataniotis

Contact tracing is of paramount importance when it comes to preventing the spreading of infectious diseases. Contact tracing is usually performed manually by authorized personnel. Manual contact tracing is an inefficient, error-prone, time-consuming process of limited utility to the population at large as those in close contact with infected individuals are

Ke Yan, Jinzheng Cai, Adam P. Harrison, Dakai Jin

Lesion detection is an important problem within medical imaging analysis. Most previous work focuses on detecting and segmenting a specialized category of lesions (e.g., lung nodules). However, in clinical practice, radiologists are responsible for finding all possible types of anomalies. The task of universal lesion detection (ULD) was proposed to address t

Theo Bühler, Vadim A. Kaimanovich

The original definition of amenability given by von Neumann in the highly non-constructive terms of means was later recast by Day using approximately invariant probability measures. Moreover, as it was conjectured by Furstenberg and proved by Kaimanovich-Vershik and Rosenblatt, the amenability of a locally compact group is actually equivalent to the existenc

Iraklis Moutidis, Hywel T. P. Williams

Detecting important events in high volume news streams is an important task for a variety of purposes.The volume and rate of online news increases the need for automated event detection methods thatcan operate in real time. In this paper we develop a network-based approach that makes the workingassumption that important news events always involve named entit

Y. Fukui, T. Ohno, K. Tsuge, H. Sano

NGC 602 is an outstanding young open cluster in the Small Magellanic Cloud. We have analyzed the new HI data taken with the Galactic Australian Square Kilometre Array Pathfinder survey project at an angular resolution of 30". The results show that there are three velocity components in the NGC 602 region. We found that two of them having ~20 km s$^{-1}$ velo

Shuangyi Wang, Xilong Hou, Richard Housden, Zengguang Hou

A robotic trans-esophageal echocardiography (TEE) probe has been recently developed to address the problems with manual control in the X-ray envi-ronment when a conventional probe is used for interventional procedure guidance. However, the robot was exclusively to be used in local areas and the effectiveness of remote control has not been scientifically test

Han Bao, Clayton Scott, Masashi Sugiyama

Adversarially robust classification seeks a classifier that is insensitive to adversarial perturbations of test patterns. This problem is often formulated via a minimax objective, where the target loss is the worst-case value of the 0-1 loss subject to a bound on the size of perturbation. Recent work has proposed convex surrogates for the adversarial 0-1 los

T. T. Huynh, L. L. C. Lem, A. Kuramata, M. R. Phillips

Cathodoluminescence spectra were measured to determine the characteristics of luminescence bands and carrier dynamics in beta-Ga2O3 bulk single crystals. The CL emission was found to be dominated by a broad UV emission peaked at 3.40 eV, which exhibits strong quenching with increasing temperature; however, its spectral shape and energy position remain virtua

Yinan Wang, Weihong "Grace" Guo, Xiaowei Yue

Feature extraction for tensor data serves as an important step in many tasks such as anomaly detection, process monitoring, image classification, and quality control. Although many methods have been proposed for tensor feature extraction, there are still two challenges that need to be addressed: 1) how to reduce the computation cost for high dimensional and

Ke Hu, Ashfaqur Rahman, Hassan Habibi Gharakheili, Vijay Sivaraman

Nowadays air pollution becomes one of the biggest world issues in both developing and developed countries. Helping individuals understand their air pollution exposure and health risks, the traditional way is to utilize data from static monitoring stations and estimate air pollution qualities in a large area by government agencies. Data from such sensing syst

Konstantinos Psychas, Javad Ghaderi

We consider a distributed server system consisting of a large number of servers, each with limited capacity on multiple resources (CPU, memory, disk, etc.). Jobs with different rewards arrive over time and require certain amounts of resources for the duration of their service. When a job arrives, the system must decide whether to admit it or reject it, and i