September 2019 arXiv papers — page 32

Ting-Rui Chiang, Hao-Tong Ye, Yun-Nung Chen

With a lot of work about context-free question answering systems, there is an emerging trend of conversational question answering models in the natural language processing field. Thanks to the recently collected datasets, including QuAC and CoQA, there has been more work on conversational question answering, and recent work has achieved competitive performan

Srikanta Sannigrahi, Suman Chakraborti, Pawan Kumar Joshi, Saskia Keesstra

Ecosystem Services are a bundle of natural processes and functions that are essential for human well-being, subsistence, and livelihood. The expansion of cultivation and cropland, which is the backbone of the Indian economy, is one of the main drivers of rapid Land Use Land Cover changes in India. To assess the impact of the Green Revolution led agrarian exp

Sucharita Giri, Alexandra Maxi Dudzinski, Jean Christophe Tremblay, Gopal Dixit

Chirality is ubiquitous in nature and of fundamental importance in science. The present work focuses on understanding the conditions required to modify the chirality during ultrafast electronic motion by bringing enantiomers out-of-equilibrium. Different kinds of ultrashort linearly-polarised laser pulses are used to drive an ultrafast charge migration proce

Subhra Sankar Dhar, Prashant Jha, Aranyak Acharyya

In this article, we study the problem of variable screening in multiple nonparametric regression model. The proposed methodology is based on the fact that the partial derivative of the regression function with respect to the irrelevant variable should be negligible. The Statistical property of the proposed methodology is investigated under both cases : (i) w

Weihao Xuan, Ruijie Ren

In order to drive safely on the road, autonomous vehicle is expected to predict future outcomes of its surrounding environment and react properly. In fact, many researchers have been focused on solving behavioral prediction problems for autonomous vehicles. However, very few of them consider multi-agent prediction under challenging driving scenarios such as

Niushan Gao, Cosimo Munari, Foivos Xanthos

We investigate a variety of stability properties of Haezendonck-Goovaerts premium principles on their natural domain, namely Orlicz spaces. We show that such principles always satisfy the Fatou property. This allows to establish a tractable dual representation without imposing any condition on the reference Orlicz function. In addition, we show that Haezendo

Subhra Sankar Dhar, Prashant Jha, Prabrisha Rakhshit

This article studies a trimmed version of the Nadaraya-Watson estimator to estimate the unknown non-parametric regression function. The characterization of the estimator through minimization problem is established, and its pointwise asymptotic distribution is also derived. The robustness property of the proposed estimator is also studied through breakdown po

Michael Assaf, Shay Be'er, Elijah Roberts

Cells use genetic switches to shift between alternate stable gene expression states, e.g., to adapt to new environments or to follow a developmental pathway. Conceptually, these stable phenotypes can be considered as attractive states on an epigenetic landscape with phenotypic changes being transitions between states. Measuring these transitions is challengi

D. V. Babukhin, A. A. Zhukov, W. V. Pogosov

In recent years, there has been a significant progress in the development of digital quantum processors. The state-of-the-art quantum devices are imperfect, and fully-algorithmic fault-tolerant quantum computing is a matter of future. Until technology develops to the state with practical error correction, computational approaches other than the standard digi

Seyed Yaser Ayazi, Ahmad Mohamadnejad

We study all extensions of the Standard Model (SM) with a vector dark matter (VDM) candidate which can explain the peak structure observed by recent DAMPE experiment in electron-positron cosmic ray spectrum. In this regard, we consider all leptophilic renormalizable VDM-SM interactions through scalar, spinor, and vector mediators. We show that only two out o

Ilan Hirshberg, N. Christopher Phillips

We construct an example of a simple approximately homogeneous C*-algebra such that its Elliott invariant admits an automorphism which is not induced by an automorphism of the algebra.

C. L. Edmunds, C. Hempel, R. J. Harris, V. M. Frey

Quantum error correction provides a path to large-scale quantum computers, but is built on challenging assumptions about the characteristics of the underlying errors. In particular, the mathematical assumption of statistically independent errors in quantum logic operations is at odds with realistic environments where error sources may exhibit strong temporal

Rüdiger Schmitz, Frederic Madesta, Maximilian Nielsen, Jenny Krause

Histopathologic diagnosis relies on simultaneous integration of information from a broad range of scales, ranging from nuclear aberrations ($\approx \mathcal{O}(0.1{\mu m})$) through cellular structures ($\approx \mathcal{O}(10{\mu m})$) to the global tissue architecture ($\gtrapprox \mathcal{O}(1{mm})$). To explicitly mimic how human pathologists combine mu

Andreas Folkers, Matthias Rick, Christof Büskens

We present a control approach for autonomous vehicles based on deep reinforcement learning. A neural network agent is trained to map its estimated state to acceleration and steering commands given the objective of reaching a specific target state while considering detected obstacles. Learning is performed using state-of-the-art proximal policy optimization i

Kotaro Shimizu, Masahito Mochizuki

We develop a theory of designing slit experiments in two-dimensional electron systems with the Rashba spin-orbit interaction. By simulating the spatiotemporal dynamics of electrons passing through a single slit or a double slit, we find that the interference fringes of the electron probability density attain specific spin orientations via the precession of s

Gyungchoon Go, Ik-Sun Hong, Seo-Won Lee, Se Kwon Kim

We theoretically investigate coupled gyration modes of magnetic solitons whose distances to the nearest neighbors are staggered. In a one-dimensional bipartite lattice, analogous to the Su-Schrieffer-Heeger model, there is a mid-gap gyration mode bounded at the domain wall connecting topologically distinct two phases. As a technological application, we show

Masayuki Tanaka, Francesco Valentino, Sune Toft, Masato Onodera

We present the first stellar velocity dispersion measurement of a massive quenching galaxy at z=4.01. The galaxy is first identified as a massive z>~4 galaxy with suppressed star formation from photometric redshifts based on deep multi-band data in the UKIDSS Ultra Deep Survey field. A follow-up spectroscopic observation with MOSFIRE on Keck revealed strong

Paul Zinn-Justin

We propose a new formulation of Hall polynomials in terms of honeycombs, which were previously introduced in the context of the Littlewood--Richardson rule. We prove a Pieri rule and associativity for our honeycomb formula, thus showing equality with Hall polynomials. Our proofs are linear algebraic in nature, extending nontrivially the corresponding bijecti

Raheel Anwar, Muhammad Irfan Yousuf, Muhammad Abid

It is commonly believed that real networks are scale-free and fraction of nodes $P(k)$ with degree $k$ satisfies the power law $P(k) \propto k^{-\gamma} \text{ for } k > k_{min} > 0$. Preferential attachment is the mechanism that has been considered responsible for such organization of these networks. In many real networks, degree distribution before the $k_

Satoshi Iso, Noriaki Kitazawa, Hikaru Ohta, Takao Suyama

We study the behavior of the effective potential between revolving D$p$-branes at all ranges of the distance $r$, interpolating $r \gg l_s$ and $r \ll l_s$ ($l_s$ is the string length). Since the one-loop open string amplitude cannot be calculated exactly, we instead employ an efficient method of $\it{ partial\ modular\ transformation}$. The method is to per

K. Okamoto, Y. Nakano, S. Masuda, Y. Itow

Neutrinos generated during solar flares remain elusive. However, after $50$ years of discussion and search, the potential knowledge unleashed by their discovery keeps the search crucial. Neutrinos associated with solar flares provide information on otherwise poorly known particle acceleration mechanisms during solar flare. For neutrino detectors, the separat

Aidan J. Crilly, Brian D. Appelbe, Owen M. Mannion, Chad J. Forrest

The kinematic lower bound for the single scattering of neutrons produced in DT fusion reactions produces a backscatter edge in the measured neutron spectrum. The energy spectrum of backscattered neutrons is dependent on the scattering ion velocity distribution. As the neutrons preferentially scatter in the densest regions of the capsule, the neutron backscat

A. Bhattacharyya, P. P. Ferreira, F. B. Santos, D. T. Adroja

In this letter, we have examined the superconducting ground state of the HfV$_2$Ga$_4$ compound using resistivity, magnetization, zero-field (ZF) and transverse-field (TF) muon-spin relaxation and rotation ($\mu$SR) measurements. Resistivity and magnetization unveil the onset of bulk superconductivity with $T_{\bf c}\sim$ 3.9~K, while TF-$\mu$SR measurements

Kyoungho Cho, Jeong-Hyuck Park

Taking $\mathbf{O}(D,D)$ covariant field variables as its truly fundamental constituents, Double Field Theory can accommodate not only conventional supergravity but also non-Riemannian gravities that may be classified by two non-negative integers, $(n,\bar{n})$. Such non-Riemannian backgrounds render a propagating string chiral and anti-chiral over $n$ and $

Navid Zobeiry, Keith D. Humfeld

Form a pure mathematical point of view, common functional forms representing different physical phenomena can be defined. For example, rates of chemical reactions, diffusion and heat transfer are all governed by exponential-type expressions. If machine learning is used for physical problems, inferred from domain knowledge, original features can be transforme

Xue Liang, Jing Xia, Xichao Zhang, Motohiko Ezawa

Antiferromagnets are promising materials for future spintronic applications due to their unique properties including zero stray fields, robustness versus external magnetic fields and ultrafast dynamics, which have attracted extensive interest in recent years. In this work, we investigate the dynamics of isolated skyrmions in an antiferromagnetic nanotrack wi

Soumajyoti Sarkar, Mohammad Almukaynizi, Jana Shakarian, Paulo Shakarian

With rise in security breaches over the past few years, there has been an increasing need to mine insights from social media platforms to raise alerts of possible attacks in an attempt to defend conflict during competition. In this study, we attempt to build a framework that utilizes unconventional signals from the darkweb forums by leveraging the reply netw

Chiranjibi Sitaula, Yong Xiang, Sunil Aryal, Xuequan Lu

Sharing images online poses security threats to a wide range of users due to the unawareness of privacy information. Deep features have been demonstrated to be a powerful representation for images. However, deep features usually suffer from the issues of a large size and requiring a huge amount of data for fine-tuning. In contrast to normal images (e.g., sce

Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Yisheng Guan

Deep Reinforcement Learning (RL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements. To alleviate this issue, we propose to exploit the symmetries present in robotic tasks. Intuitively, symmetries from observed trajectories define transformations that leave the space o

Einosuke Iida, Yaguang Yang, Makoto Yamashita

In this paper, we propose an infeasible arc-search interior-point algorithm for solving nonlinear programming problems. Most algorithms based on interior-point methods are categorized as line search, since they compute a next iterate on a straight line determined by a search direction which approximates the central path.The proposed arc-search interior-point

Yi Cheng, Hongyuan Zhu, Ying Sun, Cihan Acar

6D object pose estimation is widely applied in robotic tasks such as grasping and manipulation. Prior methods using RGB-only images are vulnerable to heavy occlusion and poor illumination, so it is important to complement them with depth information. However, existing methods using RGB-D data cannot adequately exploit consistent and complementary information

Wojciech Nadara, Marcin Smulewicz

The maximum average degree $\mathrm{mad}(G)$ of a graph $G$ is the maximum average degree over all subgraphs of $G$. In this paper we prove that for every $G$ and positive integer $k$ such that $\mathrm{mad}(G) \ge k$ there exists $S \subseteq V(G)$ such that $\mathrm{mad}(G - S) \le \mathrm{mad}(G) - k$ and $G[S]$ is $(k-1)$-degenerate. Moreover, such $S$ c

Peng Zheng, Ryan Barber, Reed J. D. Sorensen, Christopher J. L. Murray

Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis. We consider ME models where the random effects component is linear. We then develop an efficient approach for a broad problem class that allows nonlinear measurements, priors, and constraints, and finds robust estimates in all of

Larry Guth, Hong Wang, Ruixiang Zhang

We prove a sharp square function estimate for the cone in $\mathbb{R}^3$ and consequently the local smoothing conjecture for the wave equation in $2+1$ dimensions.

Hua Wang, Dewei Su, Chuangchuang Liu, Longcun Jin

The video super-resolution (VSR) task aims to restore a high-resolution (HR) video frame by using its corresponding low-resolution (LR) frame and multiple neighboring frames. At present, many deep learning-based VSR methods rely on optical flow to perform frame alignment. The final recovery results will be greatly affected by the accuracy of optical flow. Ho

Thomas D. Cohen, Henry Lamm, Richard F. Lebed

We present a model-independent global analysis of hadronic form factors for the semileptonic decays $b\rightarrow c\ell\nu$ that exploits lattice-QCD data, dispersion relations, and heavy-quark symmetries. The analysis yields predictions for the relevant form factors, within quantifiable bounds. These form factors are used to compute the semileptonic ratios

Xiaojing Liu, Toshio Horiuchi, Hiroshi Ando

In the present paper we shall improve one dimensional weighted Hardy inequalities with one-sided boundary condition by adding sharp remainders. As an application, we shall establish n dimensional weighted Hardy inequalities in a bounded smooth domain with weight functions being powers of the distance function d(x) to the boundary. Our results will be applica

Barnaby Norris, Joss Bland-Hawthorn

Astronomers have come to recognize the benefits of photonics, often in combination with optical systems, in solving longstanding experimental problems in Earth-based astronomy. Here, we explore some of the recent advances made possible by integrated photonics. We also look to the future with a view to entirely new kinds of astronomy, particularly in an era o

Q. Luo, H. Wang

Phase retrieval (PR) is an inverse problem about recovering a signal from phaseless linear measurements. This problem can be effectively solved by minimizing a nonconvex amplitude-based loss function. However, this loss function is non-smooth. To address the non-smoothness, a series of methods have been proposed by adding truncating, reweighting and smoothin

Sanjin Benic, Yoshitaka Hatta, Hsiang-nan Li, Dong-Jing Yang

We find a novel mechanism for generating transverse single-spin asymmetry (SSA) in semi-inclusive deep inelastic scattering, distinct from the known ones which involve the Sivers and Collins functions, or their collinear twist-three counterparts. It is demonstrated that a phase needed for SSA can be produced purely within a parton-level cross section startin

Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang, Debanjan Mahata

In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN). In our GAN model, the generator outputs a sequence of keyphrases based on the title and abstract of a scientific article. The discriminator learns to distinguish between machine-generated and human-curated keyphrases. We evaluate this approach o

Venkatesan Guruswami, Bernhard Haeupler, Amirbehshad Shahrasbi

We give a complete answer to the following basic question: "What is the maximal fraction of deletions or insertions tolerable by $q$-ary list-decodable codes with non-vanishing information rate?" This question has been open even for binary codes, including the restriction to the binary insertion-only setting, where the best-known result was that a $\gamma\le

Dhiya Alghalibi, Marco E. Rosti, Luca Brandt

We perform fully Eulerian numerical simulations of an initially spherical hyperelastic particle suspended in a Newtonian pressure-driven flow in a cylindrical straight pipe. We study the full particle migration and deformation for different Reynolds numbers and for various levels of particle elasticity, to disentangle the interplay of inertia and elasticity

Peixiang Zhong, Di Wang, Chunyan Miao

Messages in human conversations inherently convey emotions. The task of detecting emotions in textual conversations leads to a wide range of applications such as opinion mining in social networks. However, enabling machines to analyze emotions in conversations is challenging, partly because humans often rely on the context and commonsense knowledge to expres

Evan A Martin, Audrey Qiuyan Fu

Graphical models or networks describe the statistical dependence among multiple variables and are widely used in biology (e.g., gene regulatory networks). Under appropriate assumptions, directed edges may represent causal relationships. A key feature of a biological network is sparsity, defined by how likely an edge is present, of which we often have some kn

Teruaki Okushima, Tomoaki Niiyama, Kensuke S. Ikeda, Yasushi Shimizu

Relaxation modes are the collective modes in which all probability deviations from equilibrium states decay with the same relaxation rates. In contrast, a first passage time is the required time for arriving for the first time from one state to another. In this paper, we discuss how and why the slowest relaxation rates of relaxation modes are reconstructed f

Tian-You Fan, Wenge Yang, Xiao-Hong Sun

This article provides a detailed review on the generalized dynamics of soft-matter quasicrystals developed recent years. Comparing to solid quasicrystals consisted mainly with metallic alloys, soft-matter quasicrystals have been observed in liquid crystals, polymers, colloids, nanoparticles, and surfactants, which indicate quite different formation mechanism

Kathryn Lindsey, Chenxi Wu

We prove an explicit characterization of the points in Thurston's Master Teapot. This description can be implemented algorithmically to test whether a point in $\mathbb{C} \times \mathbb{R}$ belongs to the complement of the Master Teapot. As an application, we show that the intersection of the Master Teapot with the unit cylinder is not symmetrical under ref

Rajat Talak, Sertac Karaman, Eytan Modiano

We develop a new framework of uncertainty variables to model uncertainty. An uncertainty variable is characterized by an uncertainty set, in which its realization is bound to lie, while the conditional uncertainty is characterized by a set map, from a given realization of a variable to a set of possible realizations of another variable. We prove Bayes' law a

Xiaofa Chen, Xiao-Wu Chen

For a certain full additive subcategory X of an additive category A, one defines the lower extension groups in relative homological algebra. We show that these groups are isomorphic to the suspended Hom groups in the Verdier quotient category of the bounded homotopy category of A by that of X. Alternatively, these groups are isomorphic to the negative cohomo

Xin Ding, Z. Jane Wang, William J. Welch

Filtering out unrealistic images from trained generative adversarial networks (GANs) has attracted considerable attention recently. Two density ratio based subsampling methods---Discriminator Rejection Sampling (DRS) and Metropolis-Hastings GAN (MH-GAN)---were recently proposed, and their effectiveness in improving GANs was demonstrated on multiple datasets.

Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He

System logs record detailed runtime information of software systems and are used as the main data source for many tasks around software engineering. As modern software systems are evolving into large scale and complex structures, logs have become one type of fast-growing big data in industry. In particular, such logs often need to be stored for a long time i

Sheuly Ghosh, Subhradip Ghosh

Ni-Mn based ternary Heusler compounds have drawn attentions lately as significant magneto-caloric effects in some of them have been observed. Substitution of Ni and Mn by other $3d$ transition metals in controlled quantity have turned out to be successful in enhancing the effect and bring the operational temperatures closer to the room temperature. Using den

Wentao Ma, Yiming Cui, Nan Shao, Su He

We consider the importance of different utterances in the context for selecting the response usually depends on the current query. In this paper, we propose the model TripleNet to fully model the task with the triple <context, query, response> instead of <context, response> in previous works. The heart of TripleNet is a novel attention mechanism named triple

A. Hadley, C. Notthoff, P. Mota-Santiago, S. Dutt

Small angle X-ray scattering (SAXS) was used to quantitatively study the morphology of aligned, mono-disperse conical etched ion tracks in thin films of amorphous silicon dioxide with aspect ratios of around 6:1, and in polycarbonate foils with aspect ratios of around 1000:1. This paper presents the measurement procedure and methods developed for the analysi

Reza Abdolmaleki, Jürgen Herzog, Guangjun Zhu

Let $S=K[x_1,\ldots,x_n]$ be the polynomial ring in $n$ variables over a field $K$. In this paper, we compute the socle of $\cb$-bounded strongly stable ideals and determine that the saturation number of strongly stable ideals and of equigenerated $\cb$-bounded strongly stable ideals. We also provide explicit formulas for the saturation number $\sat(I)$ of V

Akhil Gupta, Naman Shukla, Lavanya Marla, Arinbjörn Kolbeinsson

The importance of domain knowledge in enhancing model performance and making reliable predictions in the real-world is critical. This has led to an increased focus on specific model properties for interpretability. We focus on incorporating monotonic trends, and propose a novel gradient-based point-wise loss function for enforcing partial monotonicity with d

Stuart Watt, Mikhail Kostylev

The spintronic properties of a palladium thin film have been investigated in the presence of hydrogen gas in cobalt/palladium bilayers. Measurements of the inverse spin Hall Effect (ISHE) using cavity ferromagnetic resonance allow estimations of the spin Hall conductivity and spin diffusion length in both nitrogen and hydrogen gas atmospheres. Unwanted spin

Daiki Matsunaga, Toyotaro Suzumura, Toshihiro Takahashi

Recently, there has been a surge of interest in the use of machine learning to help aid in the accurate predictions of financial markets. Despite the exciting advances in this cross-section of finance and AI, many of the current approaches are limited to using technical analysis to capture historical trends of each stock price and thus limited to certain exp

Shachar Lovett, Kewen Wu, Jiapeng Zhang

A decision list is an ordered list of rules. Each rule is specified by a term, which is a conjunction of literals, and a value. Given an input, the output of a decision list is the value corresponding to the first rule whose term is satisfied by the input. Decision lists generalize both CNFs and DNFs, and have been studied both in complexity theory and in le

Murilo S. Marques, Thiago P. Nogueira, Marcia C. Barbosa, José Rafael Bordin

In this work, a two dimensional system of polymer grafted nanoparticles is analyzed using large-scale Langevin Dymanics simulations. Effective core-softened potentials were obtained for two cases: one where the polymers are free to rotate around the nanoparticle core and a second where the polymers are fixed, with a $45^\circ$ angle between them. The use of

Yoshiko Kanada-En'yo, Kazuyuki Ogata

Cluster structures of $^{14}$C were investigated with a method of antisymmetrized molecular dynamics (AMD) combined with a $3\alpha+nn$ cluster model while focusing on the monopole excitations and linear-chain $3\alpha$ band. Variation after parity and angular momentum projections was performed in the AMD framework, and the generator coordinate method was ap

Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg, Shalinee Kishore

Uncertainty analysis in the form of probabilistic forecasting can significantly improve decision making processes in the smart power grid when integrating renewable energy sources such as wind. Whereas point forecasting provides a single expected value, probabilistic forecasts provide more information in the form of quantiles, prediction intervals, or full p

Alexander Evgrafov, Alexander Levin

In this paper we present a method of characteristic sets for inversive difference polynomials and apply it to the analysis of systems of quasi-linear algebraic difference equations. We describe characteristic sets and compute difference dimension polynomials associated with some such systems. Then we apply our results to the comparative analysis of differenc

Sandeep Kumar, Jiaxi Ying, Jos&#39;e Vin&#39;icius de M. Cardoso, Daniel P. Palomar

Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. It is well known that structured graph learning from observed samples is an NP-hard combinatorial problem. In this paper, we first show that for a set of important graph families it is possible to convert the structural constraints

David Basin, Felix Klaedtke, Eugen Zalinescu

We present an approach for verifying systems at runtime. Our approach targets distributed systems whose components communicate with monitors over unreliable channels, where messages can be delayed, reordered, or even lost. Furthermore, our approach handles an expressive specification language that extends the real-time logic MTL with freeze quantifiers for r

Ruud van Deursen, Guillaume Godin

Graphs and networks are a key research tool for a variety of science fields, most notably chemistry, biology, engineering and social sciences. Modeling and generation of graphs with efficient sampling is a key challenge for graphs. In particular, the non-uniqueness, high dimensionality of the vertices and local dependencies of the edges may render the task c

Mark Van der Merwe, Vinu Joseph, Ganesh Gopalakrishnan

Belief Propagation (BP) is a message-passing algorithm for approximate inference over Probabilistic Graphical Models (PGMs), finding many applications such as computer vision, error-correcting codes, and protein-folding. While general, the convergence and speed of the algorithm has limited its practical use on difficult inference problems. As an algorithm th

Eugene Levin

These notes are written for the book &#34;From the past to the future: the legacy of Lev Lipatov&#34;, editors: Jochen Bartels et all, which will be published by WS. I tried to share with you the atmosphere and the flavour of everyday life in Gribov&#39;s theory department, where Lev matured as an independent researcher and wrote all his breakthrough papers.

Karel Devriendt, Renaud Lambiotte, Piet Van Mieghem

The symmetric nonnegative inverse eigenvalue problem (SNIEP) asks which sets of numbers (counting multiplicities) can be the eigenvalues of a symmetric matrix with nonnegative entries. While examples of such matrices are abundant in linear algebra and various applications, this question is still open for matrices of dimension $N\geq 5$. One of the approaches

Al Amin Hosain, Panneer Selvam Santhalingam, Parth Pathak, Jana Kosecka

Voice-controlled personal and home assistants (such as the Amazon Echo and Apple Siri) are becoming increasingly popular for a variety of applications. However, the benefits of these technologies are not readily accessible to Deaf or Hard-ofHearing (DHH) users. The objective of this study is to develop and evaluate a sign recognition system using multiple mo

David Venuto, Leonard Boussioux, Junhao Wang, Rola Dali

Imitation learning seeks to learn an expert policy from sampled demonstrations. However, in the real world, it is often difficult to find a perfect expert and avoiding dangerous behaviors becomes relevant for safety reasons. We present the idea of \textit{learning to avoid}, an objective opposite to imitation learning in some sense, where an agent learns to

Jingyi Xu, Michael Danielczuk, Jeff Ichnowski, Jeffrey Mahler

Robot grasping of deformable hollow objects such as plastic bottles and cups is challenging as the grasp should resist disturbances while minimally deforming the object so as not to damage it or dislodge liquids. We propose minimal work as a novel grasp quality metric that combines wrench resistance and the object deformation. We introduce an efficient algor

Borja Balle, James Bell, Adria Gascon, Kobbi Nissim

A protocol by Ishai et al.\ (FOCS 2006) showing how to implement distributed $n$-party summation from secure shuffling has regained relevance in the context of the recently proposed \emph{shuffle model} of differential privacy, as it allows to attain the accuracy levels of the curator model at a moderate communication cost. To achieve statistical security $2

Bruno Scheihing Hitschfeld

In this thesis, we show how the structure of the landscape potential of the primordial Universe may be probed through the primordial density perturbations responsible for the origin of the cosmic microwave background anisotropies and the large-scale structure of our Universe. Isocurvature fields may have fluctuated across the barriers separating local minima

Karl Dilcher, Maciej Ulas

For each integer $n\geq 1$ we consider the unique polynomials $P, Q\in\mathbb{Q}[x]$ of smallest degree $n$ that are solutions of the equation $P(x)x^{n+1}+Q(x)(x+1)^{n+1}=1$. We derive numerous properties of these polynomials and their derivatives, including explicit expansions, differential equations, recurrence relations, generating functions, resultants,

Alp Aydinoglu, Victor M. Preciado, Michael Posa

While many robotic tasks, like manipulation and locomotion, are fundamentally based in making and breaking contact with the environment, state-of-the-art control policies struggle to deal with the hybrid nature of multi-contact motion. Such controllers often rely heavily upon heuristics or, due to the combinatoric structure in the dynamics, are unsuitable fo

René-Jean Essiambre, Roland Ryf, Sjoerd van der Heide, Juan I. Bonetti

We demonstrate the first transmission of a new twelve-dimensional modulation format over a three-core coupled-core multicore fiber. The format occupies a single time slot spread across all three linearly-coupled spatial modes and shows improved MI and GMI after transmission compared to PDM-QPSK.

Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar, Manaal Faruqui

The attention layer in a neural network model provides insights into the model&#39;s reasoning behind its prediction, which are usually criticized for being opaque. Recently, seemingly contradictory viewpoints have emerged about the interpretability of attention weights (Jain & Wallace, 2019; Vig & Belinkov, 2019). Amid such confusion arises the need to unde

Yanying Wu

Gene Ontology (GO) is the most important resource for gene function annotation. It provides a way to unify biological knowledge across different species via a dynamic and controlled vocabulary. GO is now widely represented in the Semantic Web standard Web Ontology Language (OWL). OWL renders a rich logic constructs to GO but also has its limitations. On the

Shusen Wang

Random feature mapping (RFM) is a popular method for speeding up kernel methods at the cost of losing a little accuracy. We study kernel ridge regression with random feature mapping (RFM-KRR) and establish novel out-of-sample error upper and lower bounds. While out-of-sample bounds for RFM-KRR have been established by prior work, this paper&#39;s theories ar

Julie L Newcomb, Rastislav Bodik

Programs that respond to asynchronous events are challenging to write; they are difficult to reason about and tricky to test and debug. Because these programs can have a huge space of possible input timings and interleaving, the programmer may easily miss corner cases. We propose applying synthesis to aid programmers in creating programs more easily and with

Carlo Cenedese, Giuseppe Belgioioso, Yu Kawano, Sergio Grammatico

In this paper, we study proximal type dynamics in the context of noncooperative multi-agent network games. These dynamics arise in different applications, since they describe distributed decision making in multi-agent networks, e.g., in opinion dynamics, distributed model fitting and network information fusion, where the goal of each agent is to seek an equi

Dimitris Boskos, Jorge Cortés, Sonia Martínez

Distributional ambiguity sets provide quantifiable ways to characterize the uncertainty about the true probability distribution of random variables of interest. This makes them a key element in data-driven robust optimization by exploiting high-confidence guarantees to hedge against uncertainty. This paper explores the construction of Wasserstein ambiguity s

William Clark, Anthony Bloch

The evolution of a Lagrangian mechanical system is variational. Likewise, when dealing with a hybrid Lagrangian system (a system with discontinuous impacts), the impacts can also be described by variations. These variational impacts are given by the so-called Weierstrass-Erdmann corner conditions. Therefore, hybrid Lagrangian systems can be completely unders

Rustam Pirmagomedov, Yevgeni Koucheryavy

Internet of Things (IoT) technology has delivered new enablers for improving human abilities. These enablers promise an enhanced quality of life and professional efficiency; however, the synthesis of IoT and human augmentation technologies has also extended IoT-related challenges far beyond the current scope. These potential challenges associated with IoT-em

Vedran Sekara, Elisa Omodei, Laura Healy, Jan Beise

Today, 95% of the global population has 2G mobile phone coverage and the number of individuals who own a mobile phone is at an all time high. Mobile phones generate rich data on billions of people across different societal contexts and have in the last decade helped redefine how we do research and build tools to understand society. As such, mobile phone data

Thomas N. Haider

Statistical topic models are increasingly and popularly used by Digital Humanities scholars to perform distant reading tasks on literary data. It allows us to estimate what people talk about. Especially Latent Dirichlet Allocation (LDA) has shown its usefulness, as it is unsupervised, robust, easy to use, scalable, and it offers interpretable results. In a p

Sheung Chi Chan, James Cheney, Pramod Bhatotia, Thomas Pasquier

System level provenance is of widespread interest for applications such as security enforcement and information protection. However, testing the correctness or completeness of provenance capture tools is challenging and currently done manually. In some cases there is not even a clear consensus about what behavior is correct. We present an automated tool, Pro

Christopher Amato, Andrea Baisero

To coordinate with other systems, agents must be able to determine what the systems are currently doing and predict what they will be doing in the future---plan and goal recognition. There are many methods for plan and goal recognition, but they assume a passive observer that continually monitors the target system. Real-world domains, where information gathe

Edoardo Ballico, Emanuele Ventura

Let $X$ be a complex projective variety defined over $\mathbb R$. Recently, Bernardi and the first author introduced the notion of admissible rank with respect to $X$. This rank takes into account only decompositions that are stable under complex conjugation. Such a decomposition carries a label, i.e., a pair of integers recording the cardinality of its tota

O. de Melo, C. de Melo, G. Santana, J. Santoyo

Porous silicon layers were embedded with ZnTe using the isothermal close space sublimation technique. The presence of ZnTe was demonstrated using cross-sectional energy dispersive spectroscopy maps. ZnTe embedded samples present intense room temperature photoluminescence along the whole visible range. We ascribe this PL to ZnTe nanocrystals of different size

Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa

Deep learning approaches based on convolutional neural networks (CNNs) have been successful in solving a number of problems in medical imaging, including image segmentation. In recent years, it has been shown that CNNs are vulnerable to attacks in which the input image is perturbed by relatively small amounts of noise so that the CNN is no longer able to per

Aaron Yi Ding, Gianluca Limon De Jesus, Marijn Janssen

The security of the Internet of Things (IoT) has attracted much attention due to the growing number of IoT-oriented security incidents. IoT hardware and software security vulnerabilities are exploited affecting many companies and persons. Since the causes of vulnerabilities go beyond pure technical measures, there is a pressing demand nowadays to demystify I

Bernardo Sievers, Mariano Quintero, Joaquín Sacanell

We have studied the irreversibility of the magnetization induced by thermal cycles in La0.5Ca0.5MnO3 manganites, which present a low temperature state characterized by the coexistence of phases. The effect is evidenced by a decrease of the magnetization after cycling the sample between 300 and 50 K. We developed a phenomenological model that allows us to cor

Fan Sang, Daehee Jang, Ming-Wei Shih, Taesoo Kim

Global corporations (e.g., Google and Microsoft) have recently introduced a new model of cloud services, fuzzing-as-a-service (FaaS). Despite effectively alleviating the cost of fuzzing, the model comes with privacy concerns. For example, the end user has to trust both cloud and service providers who have access to the application to be fuzzed. Such concerns

Konstantinos Karvounis

We define a family of the braid group representations via the action of the $R$-matrix (of the quasitriangular extension) of the restricted quantum $\mathfrak{sl}(2)$ on a tensor power of a simple projective module. This family is an extension of the Lawrence representation specialized at roots of unity. Although the center of the braid group has finite orde

Zeyu Zhou, Zuxin Jin, Tian Qiu, Andrew M. Rappe

We investigate a simple and robust scheme for choosing the phases of adiabatic electronic states smoothly (as a function of geometry) so as to maximize the performance of ab initio non-adiabatic dynamics methods. Our approach is based upon consideration of the overlap matrix ($\mathbf{U}$) between basis functions at successive points in time and selecting th

Emilio Almansi, Verónica Becher

We study a construction published by Donald Knuth in 1965 yielding a completely uniformly distributed sequence of real numbers. Knuth&#39;s work is based on de Bruijn sequences of increasing orders and alphabet sizes, which grow exponentially in each of the successive segments composing the generated sequence. In this work we present a similar albeit simpler

Serim Ryou, Seong-Gyun Jeong, Pietro Perona

We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classification tasks struggle to disambiguate visually similar objects. Likewise, in human pose estimation symmetric body parts often confuse the network with assigning indiscriminative sco