November 2018 arXiv papers — page 24

Sofie Haesaert, Sadegh Soudjani, Alessandro Abate

The formal verification and controller synthesis for Markov decision processes that evolve over uncountable state spaces are computationally hard and thus generally rely on the use of approximations. In this work, we consider the correct-by-design control of general Markov decision processes (gMDPs) with respect to temporal logic properties by leveraging app

Nir Shlezinger, Koby Todros

The least mean-square (LMS) filter is one of the most common adaptive linear estimation algorithms. In many practical scenarios, and particularly in digital communications systems, the signal of interest (SOI) and the input signal are jointly wide-sense cyclostationary. Previous works analyzing the performance of LMS filters for this important case assume sp

Tommaso Menara, Shi Gu, Danielle S. Bassett, Fabio Pasqualetti

The question of controllability of natural and man-made network systems has recently received considerable attention. In the context of the human brain, the study of controllability may not only shed light into the organization and function of different neural circuits, but also inform the design and implementation of minimally invasive yet effective interve

Corentin Briat, Mustafa Khammash

Ergodicity and output controllability have been shown to be fundamental concepts for the analysis and synthetic design of closed-loop stochastic reaction networks, as exemplified by the use of antithetic integral feedback controllers. In [Gupta, Briat & Khammash, PLoS Comput. Biol., 2014], some ergodicity and output controllability conditions for unimolecula

Henri Nurminen, Tohid Ardeshiri, Robert Piché, Fredrik Gustafsson

Filtering and smoothing algorithms for linear discrete-time state-space models with skew-t-distributed measurement noise are proposed. The algorithms use a variational Bayes based posterior approximation with coupled location and skewness variables to reduce the error caused by the variational approximation. Although the variational update is done suboptimal

Corentin Briat, Mustafa Khammash

Controlling stochastic reactions networks is a challenging problem with important implications in various fields such as systems and synthetic biology. Various regulation motifs have been discovered or posited over the recent years, the most recent one being the so-called Antithetic Integral Control (AIC) motif in Briat et al. (Cell Systems, 2016). Several f

Benjamin Richert

We give an alternate proof for a theorem of Migliore and Nagel. In particular, we show that if $\mathcal H$ is an SI-sequence, then the collection of Betti diagrams for all Artinian Gorenstein $k$-algebras with the weak Lefschetz property and Hilbert function $\mathcal H$ has a unique largest element.

J. W. T. Hessels, L. G. Spitler, A. D. Seymour, J. M. Cordes

FRB 121102 is the only known repeating fast radio burst source. Here we analyze a wide-frequency-range (1-8 GHz) sample of high-signal-to-noise, coherently dedispersed bursts detected using the Arecibo and Green Bank telescopes. These bursts reveal complex time-frequency structures that include sub-bursts with finite bandwidths. The frequency-dependent burst

Daniel Allcock

We give very simple algorithms for best play in the simplest kind of Dots & Boxes endgames: those that consist entirely of loops and long chains. In every such endgame we compute the margin of victory, assuming both players maximize the number of boxes they capture, and specify a move that leads to that result. We improve on results of Buzzard and Ciere on t

Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar

Accurate prediction of disease trajectories is critical for early identification and timely treatment of patients at risk. Conventional methods in survival analysis are often constrained by strong parametric assumptions and limited in their ability to learn from high-dimensional data, while existing neural network models are not readily-adapted to the longit

Vincent Cheung, Ramona Vogt

We calculate the polarization of prompt $\varUpsilon$($n$S) production in the improved color evaporation model at leading order employing the $k_T$-factorization approach. We present the polarization parameter $\lambda_\vartheta$ of prompt $\varUpsilon$($n$S) as a function of transverse momentum in $p+p$ and $p+\bar{p}$ collisions to compare with data in the

Kevin P. O'Keeffe, Amin Anjomshoaa, Steven H. Strogatz, Paolo Santi

Sensors can measure air quality, traffic congestion, and other aspects of urban environments. The fine-grained diagnostic information they provide could help urban managers to monitor a city's health. Recently, a `drive-by' paradigm has been proposed in which sensors are deployed on third-party vehicles, enabling wide coverage at low cost} Research on drive-

Yingchun Zhang

Continuing our work in \cite{1805.04894}, this article is devoted to proving that open-closed Gromov-Witten invariants of $K_{\mathbb{P}^2/\mu_3}$ are quasi-meromorphic modular forms, and generating functions of open Gromov-Witten invariants are quasi-meromorphic Jacobi forms.

Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin

Vehicle 3D extents and trajectories are critical cues for predicting the future location of vehicles and planning future agent ego-motion based on those predictions. In this paper, we propose a novel online framework for 3D vehicle detection and tracking from monocular videos. The framework can not only associate detections of vehicles in motion over time, b

Carlos Handrey Araujo Ferraz

In this paper, we perform molecular dynamics (MD) simulations to study the random packing of spheres with different particle size distributions. In particular, we deal with non-Gaussian distributions by means of the L\'evy distributions. The initial positions, as well as the radii of five thousand non-overlapping particles, are assigned inside a confining re

Vincent Conitzer

In this article, I discuss what AI can and cannot yet do, and the implications for humanity.

Subba Reddy Oota, Adithya Avvaru, Naresh Manwani, Raju S. Bapi

fMRI semantic category understanding using linguistic encoding models attempt to learn a forward mapping that relates stimuli to the corresponding brain activation. Classical encoding models use linear multi-variate methods to predict the brain activation (all voxels) given the stimulus. However, these methods essentially assume multiple regions as one large

Nikhil Parappurath, Filippo Alpeggiani, L. Kuipers, Ewold Verhagen

Topological protection in photonics offers new prospects for guiding and manipulating classical and quantum information. The mechanism of spin-orbit coupling promises the emergence of edge states that are helical; exhibiting unidirectional propagation that is topologically protected against back-scattering. We directly observe the topological states of a pho

Sebastian Bujwid, Miquel Martí, Hossein Azizpour, Alessandro Pieropan

Synthetic image translation has significant potentials in autonomous transportation systems. That is due to the expense of data collection and annotation as well as the unmanageable diversity of real-words situations. The main issue with unpaired image-to-image translation is the ill-posed nature of the problem. In this work, we propose a novel method for co

Chunlei Sun, Xiangming Wen, Zhaoming Lu, Wenpeng Jing

The rapid development of renewable energy in the energy Internet is expected to alleviate the increasingly severe power problem in data centers, such as the huge power costs and pollution. This paper focuses on the eco-friendly power cost minimization for geo-distributed data centers supplied by multi-source power, where the geographical scheduling of worklo

Ilker Nadi Bozkurt, Waqar Aqeel, Debopam Bhattacherjee, Balakrishnan Chandrasekaran

The recent publication of the `InterTubes' map of long-haul fiber-optic cables in the contiguous United States invites an exciting question: how much faster would the Internet be if routes were chosen to minimize latency? Previous measurement campaigns suggest the following rule of thumb for estimating Internet latency: multiply line-of-sight distance by 2.1

Loren Lugosch, Samuel Myer, Vikrant Singh Tomar

Keyword spotting--or wakeword detection--is an essential feature for hands-free operation of modern voice-controlled devices. With such devices becoming ubiquitous, users might want to choose a personalized custom wakeword. In this work, we present DONUT, a CTC-based algorithm for online query-by-example keyword spotting that enables custom wakeword detectio

Chapman Siu

This work presents an approach to automatically induction for non-greedy decision trees constructed from neural network architecture. This construction can be used to transfer weights when growing or pruning a decision tree, allowing non-greedy decision tree algorithms to automatically learn and adapt to the ideal architecture. In this work, we examine the u

Palash Goyal, Sujit Rokka Chhetri, Ninareh Mehrabi, Emilio Ferrara

DynamicGEM is an open-source Python library for learning node representations of dynamic graphs. It consists of state-of-the-art algorithms for defining embeddings of nodes whose connections evolve over time. The library also contains the evaluation framework for four downstream tasks on the network: graph reconstruction, static and temporal link prediction,

Prolay Kumar Mal

The top quark is the heaviest known elementary particle and plays a special role in the dynamics of fundamental interactions. Since its discovery at the Tevatron, several of its properties have been measured by the Tevatron experiments (CDF and DZERO). However, thanks to its unprecedentedly large production rate at the LHC a new level of precision in these m

Baohua Sun, Daniel Liu, Leo Yu, Jay Li

We designed a device for Convolution Neural Network applications with non-volatile MRAM memory and computing-in-memory co-designed architecture. It has been successfully fabricated using 22nm technology node CMOS Si process. More than 40MB MRAM density with 9.9TOPS/W are provided. It enables multiple models within one single chip for mobile and IoT device ap

Khimya Khetarpal, Shagun Sodhani, Sarath Chandar, Doina Precup

To achieve general artificial intelligence, reinforcement learning (RL) agents should learn not only to optimize returns for one specific task but also to constantly build more complex skills and scaffold their knowledge about the world, without forgetting what has already been learned. In this paper, we discuss the desired characteristics of environments th

Miguel Ángel Martín Contreras, Alfredo Vega, Santiago Cortés

We study light pseudoscalar and axial states using a soft wall model that is modified by introducing two extra parameters: an UV-cutoff and an anomalous term in the conformal dimension of the fields involved such that meson fields with different parities are easily distinguishable. We find that 23 of these light mesonic states, including the scalars and vect

Pierluigi Colli, Shunsuke Kurima

This paper deals with the nonlinear phase field system \begin{equation*} \begin{cases} \partial_t (\theta +\ell \varphi) - \Delta\theta = f & \mbox{in}\ \Omega\times(0, T), \\[1mm] \partial_t \varphi - \Delta\varphi + \xi + \pi(\varphi) = \ell \theta,\ \xi\in\beta(\varphi) & \mbox{in}\ \Omega\times(0, T) \end{cases} \end{equation*} in a general domain $\Omeg

Yang Yu, Ke Han, Washington Ochieng

This paper presents a doubly dynamic day-to-day (DTD) traffic assignment model with simultaneous route-and-departure-time (SRDT) choices while incorporating incomplete and imperfect information as well as bounded rationality. Two SRDT choice models are proposed to incorporate imperfect travel information: One based on multinomial Logit (MNL) model and the ot

Hisao Katsumi, Takuya Hiraoka, Koichiro Yoshino, Kazeto Yamamoto

Argumentation-based dialogue systems, which can handle and exchange arguments through dialogue, have been widely researched. It is required that these systems have sufficient supporting information to argue their claims rationally; however, the systems often do not have enough of such information in realistic situations. One way to fill in the gap is acquiri

Roberto De Leo, Andrei Ya. Maltsev

While quasiperiodic functions in one variable appeared in applications since Eighteen hundreds, for example in connection with the trajectories of mechanical systems with 2n degress of freedom having n commuting first integrals, the first applications of multivariable quasiperiodic functions were found only in Seventies, in connection with solitonic solution

S. P. Preval, N. R. Badnell, M. G. O'Mullane

The experimental thermonuclear reactor, ITER, is currently being constructed in Cadarache, France. The reactor vessel will be constructred with a beryllium coated wall, and a tungsten coated divertor. As a plasma-facing component, the divertor will be under conditions of extreme temperature, resulting in the sputtering of tungsten impurities into the main bo

Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi

We propose a deep network that can be trained to tackle image reconstruction and classification problems that involve detection of multiple object instances, without any supervision regarding their whereabouts. The network learns to extract the most significant top-K patches, and feeds these patches to a task-specific network -- e.g., auto-encoder or classif

Martin Banda-Huarca, Julio Camargo, Josselin Desmars, Ricardo Ogando

Transneptunian objects (TNOs) are a source of invaluable information to access the history and evolution of the outer solar system. However, observing these faint objects is a difficult task. As a consequence, important properties such as size and albedo are known for only a small fraction of them. Now, with the results from deep sky surveys and the Gaia spa

Siddhartha Santra, Sreraman Muralidharan, Martin Lichtman, Liang Jiang

We examine the viability of quantum repeaters based on two-species trapped ion modules for long distance quantum key distribution. Repeater nodes comprised of ion-trap modules of co-trapped ions of distinct species are considered. The species used for communication qubits has excellent optical properties while the other longer lived species serves as a memor

Michael B. Cohen, Jonathan Kelner, Rasmus Kyng, John Peebles

We show how to solve directed Laplacian systems in nearly-linear time. Given a linear system in an $n \times n$ Eulerian directed Laplacian with $m$ nonzero entries, we show how to compute an $\epsilon$-approximate solution in time $O(m \log^{O(1)} (n) \log (1/\epsilon))$. Through reductions from [Cohen et al. FOCS'16] , this gives the first nearly-linear ti

Craig Gin, Prabir Daripa

We study the stability of multi-layer radial flows in porous media within the Hele-Shaw model. We perform a linear stability analysis for radial flows consisting of an arbitrary number of fluid layers with interfaces separating fluids of constant viscosity and with positive viscosity jump at each interface in the direction of flow. Several different time-dep

Justus Thies, Michael Zollhöfer, Christian Theobalt, Marc Stamminger

We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis. The goal of our method is to generate photo-realistic re-renderings of reconstructed objects for virtual and augmented reality applications (e.g., virtual showrooms, virtual tours \& sightseeing, the digital inspection of h

Hiroharu Kato, Tatsuya Harada

There is some ambiguity in the 3D shape of an object when the number of observed views is small. Because of this ambiguity, although a 3D object reconstructor can be trained using a single view or a few views per object, reconstructed shapes only fit the observed views and appear incorrect from the unobserved viewpoints. To reconstruct shapes that look reaso

Kateřina Jiráková, Karol Bartkiewicz, Antonín Černoch, Karel Lemr

The concept of quantum money (QM) was proposed by Wiesner in the 1970s. Its main advantage is that every attempt to copy QM unavoidably leads to imperfect counterfeits. In the Wiesner's protocol, quantum banknotes need to be delivered to the issuing bank for verification. Thus, QM requires quantum communication which range is limited by noise and losses. Rec

Michelle A. Berg, J. Christopher Howk, Nicolas Lehner, Christopher B. Wotta

We present a search for HI in the circumgalactic medium (CGM) of 21 massive ($\langle \log M_\star \rangle \sim 11.4$), luminous red galaxies (LRGs) at $z\sim0.5$. Using UV spectroscopy of QSO sightlines projected within 500 kpc ($\sim R_{vir}$) of these galaxies, we detect HI absorption in 11/21 sightlines, including two partial Lyman limit systems and two

Jianyu Wang, Haichao Zhang

In this paper, we study fast training of adversarially robust models. From the analyses of the state-of-the-art defense method, i.e., the multi-step adversarial training, we hypothesize that the gradient magnitude links to the model robustness. Motivated by this, we propose to perturb both the image and the label during training, which we call Bilateral Adve

Eric Schippers, Wolfgang Staubach

Let $R$ be a compact Riemann surface and $\Gamma$ be a Jordan curve separating $R$ into connected components $\Sigma_1$ and $\Sigma_2$. We consider Calder\'on-Zygmund type operators $T(\Sigma_1,\Sigma_k)$ taking the space of $L^2$ anti-holomorphic one-forms on $\Sigma_1$ to the space of $L^2$ holomorphic one-forms on $\Sigma_k$, which we call the Schiffer op

Justin A. Goodwin, Olivia M. Brown, Taylor W. Killian, Sung-Hyun Son

Radio frequency (RF) sensors are used alongside other sensing modalities to provide rich representations of the world. Given the high variability of complex-valued target responses, RF systems are susceptible to attacks masking true target characteristics from accurate identification. In this work, we evaluate different techniques for building robust classif

Maria Okounkova, Mark A. Scheel, Saul A. Teukolsky

We present a well-posed constraint-preserving scheme for evolving first-order metric perturbations on an arbitrary background with arbitrary source. We use this scheme to evolve the leading-order metric perturbation in order-reduced dynamical Chern-Simons gravity (dCS) on a Kerr background. In particular we test the stability of stationary dCS data on a Kerr

Morgan Le Delliou, Rafael J. F. Marcondes, Gastão B. Lima Neto

As the dark sector remains unknown in composition and interaction between dark energy and dark matter stand out as natural, observations of galaxy clusters out of equilibrium abound, opening a promising window on these questions. We continue here the exploration of dark sector interaction detection via clusters virial equilibrium state for all clusters confi

Jörg Hennig

We introduce a new class of inhomogeneous cosmological models as solutions to the Einstein-Maxwell equations in electrovacuum. The new models can be considered to be nonlinear perturbations, through an electromagnetic field, of the previously studied `smooth Gowdy-symmetric generalised Taub-NUT solutions' in vacuum. Utilising methods from soliton theory, we

Alexander Heinemann, Sean Telg

This paper studies a fixed-design residual bootstrap method for the two-step estimator of Francq and Zako\"ian (2015) associated with the conditional Expected Shortfall. For a general class of volatility models the bootstrap is shown to be asymptotically valid under the conditions imposed by Beutner et al. (2018). A simulation study is conducted revealing th

Caucher Birkar

In this paper we study boundedness properties and singularities of log Calabi-Yau fibrations, particularly those admitting Fano type structures. A log Calabi-Yau fibration roughly consists of a pair $(X,B)$ with good singularities and a projective morphism $X\to Z$ such that $K_X+B$ is numerically trivial over $Z$. This class includes many central ingredient

Marcel Lederle, Benjamin Wilhelm

In this paper, we describe our contribution to Task 2 of the DCASE 2018 Audio Challenge. While it has become ubiquitous to utilize an ensemble of machine learning methods for classification tasks to obtain better predictive performance, the majority of ensemble methods combine predictions rather than learned features. We propose a single-model method that co

Xuancheng Shao

We deduce, as a consequence of the arithmetic removal lemma, an almost-all version of the Balog-Szemer\'{e}di-Gowers theorem: For any $K\geq 1$ and $\varepsilon > 0$, there exists $\delta = \delta(K,\varepsilon)>0$ such that the following statement holds: if $|A+_{\Gamma}A| \leq K|A|$ for some $\Gamma \geq (1-\delta)|A|^2$, then there is a subset $A' \subset

Faouzi Haddouchi

This paper presents some sufficient conditions for the existence of solutions of fractional differential equation with nonlocal multi-point boundary conditions involving Caputo fractional derivative and integral boundary conditions. Our analysis relies on the Banach contraction principle, Boyd and Wong fixed point theorem, Leray-Schauder nonlinear alternativ

Carenne Ludena, Miguel mendez, Nicolas Bolivar

We consider Gallai's graph Modular Decomposition theory for network analytics. On the one hand, by arguing that this is a choice tool for understanding structural and functional similarities among nodes in a network. On the other, by proposing a model for random graphs based on this decomposition. Our approach establishes a well defined context for hierarchi

Shuntaro Takeda, Kan Takase, Akira Furusawa

Quantum information protocols require various types of entanglement, such as Einstein-Podolsky-Rosen (EPR), Greenberger-Horne-Zeilinger (GHZ), and cluster states. In optics, on-demand preparation of these states has been realized by squeezed light sources, but such experiments require different optical circuits for different entangled states, thus lacking ve

Ian R. Edmonds

This paper develops a planetary model to predict the occurrence of intermediate range periodicity in solar activity, in particular the ~155 day Rieger periodicity in flare activity. It is shown that periodicity at half integer multiples of the period of Mercury occurs consistently in indices of solar activity. For this reason the planetary model is based on

Simyung Chang, John Yang, Jaeseok Choi, Nojun Kwak

We introduce the Genetic-Gated Networks (G2Ns), simple neural networks that combine a gate vector composed of binary genetic genes in the hidden layer(s) of networks. Our method can take both advantages of gradient-free optimization and gradient-based optimization methods, of which the former is effective for problems with multiple local minima, while the la

S. I. Mistakidis, G. C. Katsimiga, G. M. Koutentakis, Th. Busch

We monitor the correlated quench induced dynamical dressing of a spinor impurity repulsively interacting with a Bose-Einstein condensate. Inspecting the temporal evolution of the structure factor three distinct dynamical regions arise upon increasing the interspecies interaction. These regions are found to be related to the segregated nature of the impurity

Zhitong Jiang, Richard C. Remsing, Nicholas B. Rego, Amish J. Patel

Hydrophobic effects drive diverse aqueous assemblies, such as micelle formation or protein folding, wherein the solvent plays an important role. Consequently, characterizing the free energetics of solvent density fluctuations can lead to important insights into these processes. Although techniques such as the indirect umbrella sampling (INDUS) method (Patel

Shruti Vyas, Yogesh S Rawat, Mubarak Shah

The recent success in deep learning has lead to various effective representation learning methods for videos. However, the current approaches for video representation require large amount of human labeled datasets for effective learning. We present an unsupervised representation learning framework to encode scene dynamics in videos captured from multiple vie

Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz

Egocentric activity recognition is one of the most challenging tasks in video analysis. It requires a fine-grained discrimination of small objects and their manipulation. While some methods base on strong supervision and attention mechanisms, they are either annotation consuming or do not take spatio-temporal patterns into account. In this paper we propose L

Matthias Wollensak

In this paper, Dirac`s equation in anisotropic Bianchi-type-I background spacetimes is treated w.r.t. orthonormal frames. By specializing to the massless spinor case and metrics with power-law scale factors and planar symmetry, an analytical expression of the approximate time evolution operator is derived. By use of this operator, all approximate spinor solu

Mengshi Qi, Weijian Li, Zhengyuan Yang, Yunhong Wang

Scene graph generation refers to the task of automatically mapping an image into a semantic structural graph, which requires correctly labeling each extracted object and their interaction relationships. Despite the recent success in object detection using deep learning techniques, inferring complex contextual relationships and structured graph representation

C. Verbeke, M. L. Mays, M. Temmer, S. Bingham

Accurate forecasting of the arrival time and subsequent geomagnetic impacts of Coronal Mass Ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress towards defining community-agreed metrics and validation methods to assess the current state of

Sushil K. Sharma, Nikodem Krawczyk, Juhi Raj

The precise measurements of the Compton scatterings of photons originating from the decay of positronium atoms can reveal information about their polarizations. J-PET detector is constructed of 192 plastic scintillators and is unique to study the scattering correlations of the annihilation photons with an angular precision of several degrees. In this work, w

D. Neuffer, V. Shiltsev

We discuss the technical feasibility, key machine parameters and major challenges of a 14 TeV c.m.e. muon-muon collider in the LHC tunnel. The luminosity of the collider is evaluated for three alternative muon sources - the PS synchrotron, one of a type developed by the US Muon Accelerator Program (MAP) and a low-emittance option based on resonant muon pair

Laurent Busé, Thomas Dedieu

The goal of this text is to understand and prove a formula stated by Salmon, which gives the first terms of some Taylor expansion of the discriminant of a plane algebraic curve. Salmon uses his formula to derive various enumerative quantities for surfaces in $\mathbf{P}^3$. We provide complete proofs of this formula and its enumerative applications, and exte

J. A. Toala, L. M. Oskinova, W. -R. Hamann, R. Ignace

Among different types of massive stars in advanced evolutionary stages is the enigmatic WN8h type. There are only a few Wolf-Rayet (WR) stars with this spectral type in our Galaxy. It has long been suggested that WN8h-type stars are the products of binary evolution that may harbor neutron stars (NS). One of the most intriguing WN8h stars is the runaway WR124

Richard Blundell, Joel Horowitz, Matthias Parey

Berkson errors are commonplace in empirical microeconomics. In consumer demand this form of measurement error occurs when the price an individual pays is measured by the (weighted) average price paid by individuals in a specified group (e.g., a county), rather than the true transaction price. We show the importance of such measurement errors for the estimati

Irene Li, Alexander R. Fabbri, Robert R. Tung, Dragomir R. Radev

Recent years have witnessed the rising popularity of Natural Language Processing (NLP) and related fields such as Artificial Intelligence (AI) and Machine Learning (ML). Many online courses and resources are available even for those without a strong background in the field. Often the student is curious about a specific topic but does not quite know where to

Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek, Neill D. F. Campbell

We present a probabilistic model for unsupervised alignment of high-dimensional time-warped sequences based on the Dirichlet Process Mixture Model (DPMM). We follow the approach introduced in (Kazlauskaite, 2018) of simultaneously representing each data sequence as a composition of a true underlying function and a time-warping, both of which are modelled usi

Aleksey O. Zakharov, Yulia V. Kovalenko

We consider the bicriteria asymmetric travelling salesman problem (bi-ATSP). Optimal solution to a multicriteria problem is usually supposed to be the Pareto set, which is rather wide in real-world problems. For the first time we apply to the bi-ATSP the axiomatic approach of the Pareto set reduction proposed by V. Noghin. We identify series of 'quanta of in

Shubhankar Sahai

We show that combinatorial objects called row-strict composition tableaux, introduced by Mason and Remmel in 2014 and closely related to the quasi-symmetric Schur functions of Haglund-Luoto-Mason-van Willigenburg, form a basis for Schur functors of finite free modules over arbitrary commutative rings. When the ring is the complex numbers, this produces a new

Mengting Wan, Xin Chen

We study the problem of providing recommended responses to customer service agents in live-chat dialogue systems. Smart-reply systems have been widely applied in real-world applications (e.g. Gmail, LinkedIn Messaging), where most of them can successfully recommend reactive responses. However, we observe a major limitation of current methods is that they gen

L. A. Lugiato, F. Prati, M. L. Gorodetsky, T. J. Kippenberg

The model, that is usually called Lugiato-Lefever equation (LLE), was introduced in 1987 with the aim of providing a paradigm for dissipative structure and pattern formation in nonlinear optics. This model, describing a driven, detuned and damped nonlinear Schroedinger equation, gives rise to dissipative spatial and temporal solitons. Recently, the rather id

Ruben Asensio-Torres, Thayne Currie, Markus Janson, Silvano Desidera

We present SCExAO/CHARIS 1.1--2.4 micron integral field direct spectroscopy of the young HIP 79124 triple system. HIP 79124 is a member of the Scorpius-Centaurus association, consisting of an A0V primary with two low-mass companions at a projected separation of <1 arcsecond. Thanks to the high quality wavefront corrections provided by SCExAO, both companions

Tobias Kramer, Mirta Rodriguez, Yaroslav Zelinskyy

Time-resolved spectroscopy provides the main tool for analyzing the dynamics of excitonic energy transfer in light-harvesting complexes. To infer time-scales and effective coupling parameters from experimental data requires to develop numerical exact theoretical models. The finite duration of the laser-molecule interactions and the reorganization process dur

Junjie Wang, Qiang Zhu, Zhenhai Wang, Hideo Hosono

A high-throughput screening based on first-principles calculations was performed to search for new ternary inorganic electrides. From the available materials database, we identified three new thermodynamically stable materials (Li$_{12}$Mg$_3$Si$_4$, NaBa$_2$O and Ca$_5$Ga$_2$N$_4$) as potential electrides made by main group elements, in addition to the well

S. I. Kruglov

We propose and investigate the modified Born$-$Infeld-type gravity model with the function $F(R) = [1-(1-\beta R/\sigma)^\sigma]/\beta$. At different values of the dimensionless parameter $\sigma$ the action is converted into some models including general relativity ($\sigma=1$), the Starobinsky model ($\sigma=2$), the exponential model of gravity ($\sigma=\

Titus Cieslewski, Michael Bloesch, Davide Scaramuzza

The extraction and matching of interest points is a prerequisite for many geometric computer vision problems. Traditionally, matching has been achieved by assigning descriptors to interest points and matching points that have similar descriptors. In this paper, we propose a method by which interest points are instead already implicitly matched at detection t

Gioia Rau, Krister E. Nielsen, Kenneth G. Carpenter, Vladimir Airapetian

The photon-scattering winds of M-giants absorb parts of the chromospheric emission lines and produce self-reversed spectral features in high resolution {\it HST}/GHRS spectra. These spectra provide an opportunity to assess fundamental parameters of the wind, including flow and turbulent velocities, the optical depth of the wind above the region of photon cre

Ivan Korolev

This paper studies model selection in semiparametric econometric models. It develops a consistent series-based model selection procedure based on a Bayesian Information Criterion (BIC) type criterion to select between several classes of models. The procedure selects a model by minimizing the semiparametric Lagrange Multiplier (LM) type test statistic from Ko

Adam Clay

The Burns-Hale theorem states that a group G is left-orderable if and only if G is locally projectable onto the class of left-orderable groups. Similar results have appeared in the literature in the case of UPP groups and Conradian left-orderable groups, with proofs using varied techniques in each case. This note presents a streamlined approach to showing th

Qin Ba, Jong-Shi Pang

This paper presents an exact penalization theory of the generalized Nash equilibrium problem (GNEP) that has its origin from the renowned Arrow-Debreu general economic equilibrium model. While the latter model is the foundation of much of mathematical economics, the GNEP provides a mathematical model of multi-agent non-cooperative competition that has found

Sungsoo Kim, Jin Soo Park, Christos G. Bampis, Jaeseong Lee

We propose a video compression framework using conditional Generative Adversarial Networks (GANs). We rely on two encoders: one that deploys a standard video codec and another which generates low-level maps via a pipeline of down-sampling, a newly devised soft edge detector, and a novel lossless compression scheme. For decoding, we use a standard video decod

Alina L. Bendinger, Charlotte Debus, Christin Glowa, Christian P. Karger

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify perfusion and vascular permeability. In most cases a bolus arrival time (BAT) delay exists between the arterial input function (AIF) and the contrast agent arrival in the tissue of interest which needs to be estimated. Existing methods for BAT estimation are tailored to tissue

Bhubanjyoti Bhattacharya, David London

To date, the weak-phase $\gamma$ has been measured using two-body $B$-meson decays such as $B\to D K$ and $B\to D\pi$, whose amplitudes contain only tree-level diagrams. But $\gamma$ can also be extracted from three-body charmless hadronic $B$ decays. Since the amplitudes for such decays contain both tree- and loop-level diagrams, $\gamma$ obtained in this w

Shari Trewin

We consider how fair treatment in society for people with disabilities might be impacted by the rise in the use of artificial intelligence, and especially machine learning methods. We argue that fairness for people with disabilities is different to fairness for other protected attributes such as age, gender or race. One major difference is the extreme divers

Christopher Bowles, Roger Gunn, Alexander Hammers, Daniel Rueckert

Medical imaging is a domain which suffers from a paucity of manually annotated data for the training of learning algorithms. Manually delineating pathological regions at a pixel level is a time consuming process, especially in 3D images, and often requires the time of a trained expert. As a result, supervised machine learning solutions must make do with smal

Emmanouil Kolezakis

Analysing the development process for an ERP solution, in our case SAP, is one of the most critical processes in implementing standard software packages. Modelling of the proposed system can facilitate the development of enterprise systems not from scratch but through use of predefined parts who represents the best knowledge captured from numerous case studi

G. E. Addison, C. L. Bennett, D. Jeong, E. Komatsu

We perform forecasts for how baryon acoustic oscillation (BAO) scale and redshift-space distortion (RSD) measurements from future spectroscopic emission line galaxy (ELG) surveys such as Euclid are degraded in the presence of spectral line misidentification. Using analytic calculations verified with mock galaxy catalogs from log-normal simulations we find th

Fabio De Sousa Ribeiro, Francesco Caliva, Mark Swainson, Kjartan Gudmundsson

Supervised Deep Learning has been highly successful in recent years, achieving state-of-the-art results in most tasks. However, with the ongoing uptake of such methods in industrial applications, the requirement for large amounts of annotated data is often a challenge. In most real world problems, manual annotation is practically intractable due to time/labo

Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun

Embedding models for deterministic Knowledge Graphs (KG) have been extensively studied, with the purpose of capturing latent semantic relations between entities and incorporating the structured knowledge into machine learning. However, there are many KGs that model uncertain knowledge, which typically model the inherent uncertainty of relations facts with a

Matteo Tomei, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara

The applicability of computer vision to real paintings and artworks has been rarely investigated, even though a vast heritage would greatly benefit from techniques which can understand and process data from the artistic domain. This is partially due to the small amount of annotated artistic data, which is not even comparable to that of natural images capture

Christopher D. Rosin

Inductive program synthesis, from input/output examples, can provide an opportunity to automatically create programs from scratch without presupposing the algorithmic form of the solution. For induction of general programs with loops (as opposed to loop-free programs, or synthesis for domain-specific languages), the state of the art is at the level of introd

Alexey Kudin, Denis Vasilyev

In this paper we consider the problem of counting algebraic numbers $\alpha$ of fixed degree $n$ and bounded height $Q$ such that the derivative of the minimal polynomial $P_{\alpha}(x)$ of $\alpha$ is bounded, $|P_{\alpha}'(\alpha)| < Q^{1-v}$. This problem has many applications to the problems of the metric theory of Diophantine approximation. We prove tha

Masato Morita, Roman V. Krems, Timur V. Tscherbul

Currently, quantum scattering calculations cannot be used for quantitative predictions of molecular scattering observables at ultralow temperatures. This is a result of two problems: the extreme sensitivity of the scattering observables to details of potential energy surfaces (PES) for interactions between the collision partners, and the exceedingly large si

Sonia Acinas, Jakub Maksymiuk, Fernando Mazzone

We consider the existence of periodic solutions to Hamiltonian Systems with growth conditions involving G-function. We introduce the notion of symplectic G-function and provide relation for the growth of Hamiltonian in terms of certain constant $C_G$ associated to symplectic G-function $G$. We discuss an optimality of this constant for some special cases. We

Christian Glaser

The ARIANNA detector aims to detect neutrinos with energies above \SI{e16}{eV} by instrumenting 0.5 Teratons of ice with a surface array of a thousand independent radio detector stations in Antarctica. The Antarctic ice is transparent to the radio signals caused by the Askaryan effect which allows for a cost-effective instrumentation of large volumes. Severa

Anna Nelles

The ARIANNA experiment aims to detect the radio signals of cosmogenic neutrinos. It is running in its pilot phase on the Ross Ice-shelf, and one station has been installed at South Pole. The ARIANNA concept is based on installing high-gain log periodic dipole antennas close to the surface monitoring the underlying ice for the radio signals following a neutri