June 2019 arXiv papers — page 38

Antonia W. Bluher

Let $G$ be a subgroup of ${\rm PGL}_2({\mathbb F}_q)$, where $q$ is any prime power, and let $Q \in {\mathbb F}_q[x]$ such that ${\mathbb F}_q(x)/{\mathbb F}_q(Q(x))$ is a Galois extension with group $G$. By explicitly computing the Artin map on unramified degree-1 primes in ${\mathbb F}_q(Q)$ for various groups $G$, interesting new results emerge about fini

Evan B. Bauer, Christopher J. White, Lars Bildsten

Some binary systems composed of a white dwarf (WD) and a hot subdwarf (sdB) helium star will make contact within the helium burning lifetime of the sdB star. The accreted helium on the WD inevitably undergoes a thermonuclear instability, causing a detonation that is expected to transition into the WD core and lead to a thermonuclear supernova while the donor

Weijia Shi, Muhao Chen, Yingtao Tian, Kai-Wei Chang

Bilingual word embeddings, which representlexicons of different languages in a shared em-bedding space, are essential for supporting se-mantic and knowledge transfers in a variety ofcross-lingual NLP tasks. Existing approachesto training bilingual word embeddings requireoften require pre-defined seed lexicons that areexpensive to obtain, or parallel sentence

Ke-Wen Huang, Hui-Ming Wang, Don Towsley, H. Vincent Poor

In this paper, we establish a framework for low probability of detection (LPD) communication from a sequential change-point detection (SCPD) perspective, where a transmitter, Alice, wants to hide her signal transmission to a receiver, Bob, under the surveillance of an adversary, Willie. The new framework facilitates to model LPD communication and further eva

Qiang Hao, Jack P Wilson, Camille Ottaway, Naitra Iriumi

This study investigated the essential of meaningful automated feedback for programming assignments. Three different types of feedback were tested, including (a) What's wrong - what test cases were testing and which failed, (b) Gap - comparisons between expected and actual outputs, and (c) Hint - hints on how to fix problems if test cases failed. 46 stude

Team Rocket, Maofan Yin, Kevin Sekniqi, Robbert van Renesse

This paper introduces a family of leaderless Byzantine fault tolerance protocols, built around a metastable mechanism via network subsampling. These protocols provide a strong probabilistic safety guarantee in the presence of Byzantine adversaries while their concurrent and leaderless nature enables them to achieve high throughput and scalability. Unlike blo

Ligeng Zhu, Zhijian Liu, Song Han

Exchanging gradients is a widely used method in modern multi-node machine learning system (e.g., distributed training, collaborative learning). For a long time, people believed that gradients are safe to share: i.e., the training data will not be leaked by gradient exchange. However, we show that it is possible to obtain the private training data from the pu

Baihan Lin, Marieke Mur, Tim Kietzmann, Nikolaus Kriegeskorte

Representational similarity analysis (RSA) has been shown to be an effective framework to characterize brain-activity profiles and deep neural network activations as representational geometry by computing the pairwise distances of the response patterns as a representational dissimilarity matrix (RDM). However, how to properly analyze and visualize the repres

Jorge Madrid, Hugo Jair Escalante, Eduardo Morales

Recent progress in AutoML has lead to state-of-the-art methods (e.g., AutoSKLearn) that can be readily used by non-experts to approach any supervised learning problem. Whereas these methods are quite effective, they are still limited in the sense that they work for tabular (matrix formatted) data only. This paper describes one step forward in trying to autom

Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf, Jenna Reinen

Drawing an inspiration from behavioral studies of human decision making, we propose here a more general and flexible parametric framework for reinforcement learning that extends standard Q-learning to a two-stream model for processing positive and negative rewards, and allows to incorporate a wide range of reward-processing biases -- an important component o

Shimpei Goto, Ippei Danshita

A recent experiment has observed the antiferromagnetic interaction between the ground state $^1S_0$ and the metastable state $^3P_0$ of $^{171}$Yb atoms, which are fermionic. This observation combined with the use of state-dependent optical lattices allows for quantum simulation of the Kondo model. We propose that in this Kondo simulator the anomalous temper

H. Nakada

Influence of magic numbers on nuclear radii is investigated via the Hartree-Fock-Bogolyubov calculations and available experimental data. With the $\ell s$ potential including additional density-dependence suggested from the chiral effective field theory, kinks are universally predicted at the $jj$-closed magic numbers and anti-kinks (\textit{i.e.} inverted

Junlong Lyu, Zhongjian Wang, Jack Xin, Zhiwen Zhang

In this paper, we propose stochastic structure-preserving schemes to compute the effective diffusivity for particles moving in random flows. We first introduce the motion of particles using the Lagrangian formulation, which is modeled by stochastic differential equations (SDEs). We also discuss the definition of the corrector problem and effective diffusivit

Vishnu S. Chipade, Dimitra Panagou

This paper studies a defense approach against a swarm of adversarial agents. We employ a closed formation (`StringNet') of defending agents around the adversarial agents to restrict their motion and guide them to a safe area while navigating in an obstacle-populated environment. Control laws for forming the StringNet and guiding it to a safe area are dev

Akbar Jahangiri, James P. Shaffer, Luís Felipe Gonçalves, Luis Gustavo Marcassa

We calculate pair potential curves for interacting Rydberg atoms in a constant electric field and use them to determine the effective $C_3$ dipole-dipole and $C_6$ van der Waals coefficients. We compare the $C_3$ and $C_6$ with experiments where the angle of a polarizing electric field is varied with respect to the axis of a quasi-1-dimensional trap at ultra

Semyon Dyatlov, Long Jin, Stéphane Nonnenmacher

We prove a microlocal lower bound on the mass of high energy eigenfunctions of the Laplacian on compact surfaces of negative curvature, and more generally on surfaces with Anosov geodesic flows. This implies controllability for the Schr\"odinger equation by any nonempty open set, and shows that every semiclassical measure has full support. We also prove expo

Yulan Liu, Shaohua Pan

For the rank regularized minimization problem, we introduce several kinds of stationary points by the problem itself and its equivalent reformulations including the mathematical program with an equilibrium constraint (MPEC), the global exact penalty of the MPEC,the surrogate yielded by eliminating the dual part in the exact penalty. A clear relation chart is

Miles I. Collins, Dane R. McCamey, Murad J. Y. Tayebjee

Several recent electron spin resonance studies have observed a quintet multiexciton state during the singlet fission process. Here we provide a general theoretical explanation for the generation of this state by invoking a time-varying exchange coupling between pairs of triplet excitons, and subsequently solving the relevant time-varying spin Hamiltonian for

Ryo Nakashima, Ryo Ozaki, Tadahiro Taniguchi

This paper describes a new unsupervised machine learning method for simultaneous phoneme and word discovery from multiple speakers. Human infants can acquire knowledge of phonemes and words from interactions with his/her mother as well as with others surrounding him/her. From a computational perspective, phoneme and word discovery from multiple speakers is a

I. V. Borzenets, J. Shim, J. Chen, A. Ludwig

When a magnetic impurity exists in a metal, conduction electrons form a spin cloud that screens the impurity spin. This basic phenomenon is called the Kondo effect. Contrary to electric charge screening, the spin screening cloud occurs quantum coherently, forming spin-singlet entanglement with the impurity. Although the spins interact locally around the impu

Mauricio Hippert, David Dobrigkeit Chinellato, Matthew Luzum, Jorge Noronha

In heavy-ion collisions, momentum-dependent pair correlations can be characterized by a principal component analysis (PCA), in which subleading modes are expected to reveal new information on flow fluctuations. However, we find that, as currently measured, these modes can be dominated by multiplicity fluctuations, which serve as an unwanted background. Here,

Masaomi Tanaka, Daiji Kato, Gediminas Gaigalas, Kyohei Kawaguchi

Coalescence of neutron stars gives rise to kilonova, thermal emission powered by radioactive decays of freshly synthesized r-process nuclei. Although observational properties are largely affected by bound-bound opacities of r-process elements, available atomic data have been limited. In this paper, we study element-to-element variation of the opacities in th

Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi

Drawing an inspiration from behavioral studies of human decision making, we propose here a general parametric framework for a reinforcement learning problem, which extends the standard Q-learning approach to incorporate a two-stream framework of reward processing with biases biologically associated with several neurological and psychiatric conditions, includ

Vivek Kale, Christian Iwainsky, Michael Klemm, Jonas H. Muller Korndorfer

Parallel loops are an important part of OpenMP programs. Efficient scheduling of parallel loops can improve performance of the programs. The current OpenMP specification only offers three options for loop scheduling, which are insufficient in certain instances. Given the large number of other possible scheduling strategies, it is infeasible to standardize ea

Riis R. A. Bachega, Andre A. Costa, E. Abdalla, K. S. F. Fornazier

Gravitational Waves (GW's) can determine the luminosity distance of the progenitor directly from the amplitude of the wave, without assuming any specific cosmological model. Thus, it can be considered as a standard siren. The coalescence of binary neutron stars (BNS) or neutron star-black hole pair (NSBH) can generate GW's as well as the electromagnetic coun

Oliver B. Linton, Haihan Tang

We propose a new estimator, the quadratic form estimator, of the Kronecker product model for covariance matrices. We show that this estimator has good properties in the large dimensional case (i.e., the cross-sectional dimension $n$ is large relative to the sample size $T$). In particular, the quadratic form estimator is consistent in a relative Frobenius no

Yanxia Zhang, Jingyi Zhang, Xin Jin, Yongheng Zhao

Based on the SDSS and SDSS-WISE quasar datasets, we put forward two schemes to estimate the photometric redshifts of quasars. Our schemes are based on the idea that the samples are firstly classified into subsamples by a classifier and then photometric redshift estimation of different subsamples is performed by a regressor. Random Forest is adopted as the co

Chen Ding, Tian-Yi Bao, He-Liang Huang

Support vector machine (SVM) is a particularly powerful and flexible supervised learning model that analyzes data for both classification and regression, whose usual algorithm complexity scales polynomially with the dimension of data space and the number of data points. To tackle the big data challenge, a quantum SVM algorithm was proposed, which is claimed

Eli Sennesh, Zulqarnain Khan, Yiyu Wang, Jennifer Dy

Neuroimaging studies produce gigabytes of spatio-temporal data for a small number of participants and stimuli. Rarely do researchers attempt to model and examine how individual participants vary from each other -- a question that should be addressable even in small samples given the right statistical tools. We propose Neural Topographic Factor Analysis (NTFA

K. C. Matthew Cheung, Jerome P. Gauntlett, Christopher Rosen

We construct a consistent Kaluza-Klein reduction of $D=11$ supergravity on $\Sigma_2\times S^4$, where $\Sigma_2=S^2,\mathbb{R}^2$ or $H^2$, or a quotient thereof, at the level of the bosonic fields. The result is a gauged $N=4$, $D=5$ supergravity theory coupled to three vector multiplets, with the gauging lying in an $SO(2)\times SE(3)\subset SO(5,3)$ subg

Ang Yang, Cheng Li, Santu Rana, Sunil Gupta

We propose a novel sparse spectrum approximation of Gaussian process (GP) tailored for Bayesian optimization. Whilst the current sparse spectrum methods provide desired approximations for regression problems, it is observed that this particular form of sparse approximations generates an overconfident GP, i.e. it produces less epistemic uncertainty than the o

Yayuan Tian, Yan Zhao, Fengwen Kang, Fucong Lyu

A new type of nontoxic low-cost sensor is reported here, whose photoluminescence (PL) intensity is instantly responsive to the external strain applied over a large range (up to 250% strain). Highly stretchable fluorescent composites of carbon dots (CDs) and polyurethane (PU) are fabricated via a scalable green chemistry method by conveniently dispersing CDs

Christian Wuthrich

Most approaches to quantum gravity suggest that relativistic spacetime is not fundamental, but instead emerges from some non-spatiotemporal structure. This paper investigates the implications of this suggestion for the possibility of time travel in the sense of the existence of closed timelike curves in some relativistic spacetimes. In short, will quantum gr

Huibo Bi, Erol Gelenbe

Owing to the increasing frequency and destruction of natural and manmade disasters to modern highly-populated societies, emergency management, which provides solutions to prevent or address disasters, have drawn considerable research over the last few decades and become a multidisciplinary area. Because of its open and inclusive nature, new technologies alwa

An Yan, Bill Howe

Emerging transportation modes, including car-sharing, bike-sharing, and ride-hailing, are transforming urban mobility but have been shown to reinforce socioeconomic inequities. Spatiotemporal demand prediction models for these new mobility regimes must therefore consider fairness as a first-class design requirement. We present FairST, a fairness-aware model

Absos Ali Shaikh, Mohamd Saleem Lone, Pinaki Ranjan Ghosh

The main aim of this paper is to investigate the nature of invariancy of rectifying curve under conformal transformation and obtain a sufficient condition for which such a curve remains conformally invariant. It is shown that the normal component and the geodesic curvature of the rectifying curve is homothetic invariant.

Syrine Krichene, Mike Gartrell, Clement Calauzenes

Embedding models, which learn latent representations of users and items based on user-item interaction patterns, are a key component of recommendation systems. In many applications, contextual constraints need to be applied to refine recommendations, e.g. when a user specifies a price range or product category filter. The conventional approach, for both cont

Nikolay Koshev, Nikolay Yavich, Mikhail Malovichko, Ekaterina Skidchenko

We propose an approach and the numerical algorithm for pre-processing of the electroencephalography (EEG) data, enabling to generate an accurate mapping of the potential from the measurement area - scalp - to the brain surface. The algorithm based on the solution of ill-posed Cauchy problem for the Laplace's equation using tetrahedral finite elements lin

Xinyi Li, Yinchuan Li, Yuancheng Zhan, Xiao-Yang Liu

Portfolio allocation is crucial for investment companies. However, getting the best strategy in a complex and dynamic stock market is challenging. In this paper, we propose a novel Adaptive Deep Deterministic Reinforcement Learning scheme (Adaptive DDPG) for the portfolio allocation task, which incorporates optimistic or pessimistic deep reinforcement learni

Francesco Ferdinando Summa

In this article we have illustrated how is possible to formulate Maxwell's equations in vacuum in an independent form of the usual systems of units. Maxwell's equations, are then specialized to the most commonly used systems of units: International system of units (SI), Gaussian normal, Gaussian rational (Heaviside-Lorentz), C.G.S. (electric), C.G.S.

B. S. Bleier

The subjective experience of consciousness is at once familiar and yet deeply mysterious. Strategies exploring the top-down mechanisms of conscious thought within the human brain have been unable to produce a generalized explanatory theory that scales through evolution and can be applied to artificial systems. Information Flow Theory (IFT) provides a novel f

Lu Haonan, Seth H. Huang, Tian Ye, Guo Xiuyan

In this work, we present graph star net (GraphStar), a novel and unified graph neural net architecture which utilizes message-passing relay and attention mechanism for multiple prediction tasks - node classification, graph classification and link prediction. GraphStar addresses many earlier challenges facing graph neural nets and achieves non-local represent

Yongqiang Huang, Yu Sun

Pouring is the second most frequently executed motion in cooking scenarios. In this work, we present our system of accurate pouring that generates the angular velocities of the source container using recurrent neural networks. We collected demonstrations of human pouring water. We made a physical system on which the velocities of the source container were ge

Alessandro Lanza, Serena Morigi, Monica Pragliola, Fiorella Sgallari

We propose two new variational models aimed to outperform the popular total variation (TV) model for image restoration with L$_2$ and L$_1$ fidelity terms. In particular, we introduce a space-variant generalization of the TV regularizer, referred to as TV$_p^{SV}$, where the so-called shape parameter $p\,$ is automatically and locally estimated by applying a

Paloma De-La-Cal-Sabater, Irma Caro, Javier Mateo, Maria J. Castro

Cronobacter sakazakii is an opportunistic pathogen associated with outbreaks of neonatal necrotizing enterocolitis, septicemia, and meningitis. Reconstituted powdered infant formulae (PIF) is the most common vehicle of infection. Plate count methods do not provide direct information on the physiological status of cells. Flow cytometry (FC) has been used to g

Minkyu Lim, Ji-Hwan Kim

While the Kaldi framework provides state-of-the-art components for speech recognition like feature extraction, deep neural network (DNN)-based acoustic models, and a weighted finite state transducer (WFST)-based decoder, it is difficult to implement a new flexible DNN model. By contrast, a general-purpose deep learning framework, such as TensorFlow, can easi

Ehsan Adeli, Hermann G. Matthies

To evaluate the cyclic behavior under different loading conditions using the kinematic and isotropic hardening theory of steel, a Chaboche viscoplastic material model is employed. The parameters of a constitutive model are usually identified by minimization of the difference between model response and experimental data. However, measurement errors and differ

Jan S. Rellermeyer, Sobhan Omranian Khorasani, Dan Graur, Apourva Parthasarathy

Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the traditional ways of sca

Edgar Marcelino

Schottky Conjecture is analytically proved for multi-stage field emitters consisting on the superposition of rectangular or trapezoidal protrusions on a line under some specific limit. The case in which a triangular protrusion is present on the top of each emitter is also considered as an extension of the model. The results presented here are obtained via Sc

D. V. Fastovets, Yu. I. Bogdanov, B. I. Bantysh, V. F. Lukichev

Classical machine learning theory and theory of quantum computations are among of the most rapidly developing scientific areas in our days. In recent years, researchers investigated if quantum computing can help to improve classical machine learning algorithms. The quantum machine learning includes hybrid methods that involve both classical and quantum algor

Zhan Gao, Mark Eisen, Alejandro Ribeiro

Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space optical networks. This paper investigates the optimal design of power allocation for Wavelength Division Multiplexing (WDM) transmission in RoFSO systems. The proposed problem is a w

Shuai Hou, Ruipu Bai

For any $n$-dimensional 3-Lie algebra $A$ over a field of characteristic zero with an involutive derivation $D$, we investigate the structure of the 3-Lie algebra $B_1=A\ltimes_{ad^*} A^* $ associated with the coadjoint representation $(A^*, ad^*)$. We then discuss the structure of the dual 3-Lie algebra $B_2$ of the local cocycle 3-Lie bialgebra $(A\ltimes_

Abraham D. Falcone, Ralph P. Kraft, Marshall W. Bautz, Jessica A. Gaskin

Four NASA Science and Technology Definition Teams have been convened in order to develop and study four mission concepts to be evaluated by the upcoming 2020 Decadal Survey. The Lynx x-ray surveyor mission is one of these four large missions. Lynx will couple fine angular resolution (<0.5 arcsec HPD) x-ray optics with large effective area (~2 m^2 at 1 keV),

Daniel Rivero, Enrique Fernandez-Blanco, Alejandro Pazos

This paper proposes a new model for music prediction based on Variational Autoencoders (VAEs). In this work, VAEs are used in a novel way in order to address two different problems: music representation into the latent space, and using this representation to make predictions of the future values of the musical piece. This approach was trained with different

Qianqian Yang, Parisa Hassanzadeh, Deniz Gündüz, Elza Erkip

Content delivery in a multi-user cache-aided broadcast network is studied, where a server holding a database of correlated contents communicates with the users over a Gaussian broadcast channel (BC). The minimum transmission power required to satisfy all possible demand combinations is studied, when the users are equipped with caches of equal size. Assuming

Ronan Gourgues, Johannes W. N. Los, Julien Zichi, Jin Chang

We experimentally investigate the performance of NbTiN superconducting nanowire single photon detectors above the base temperature of a conventional Gifford-McMahon cryocooler (2.5 K). By tailoring design and thickness (8 - 13 nm) of the detectors, high performance, high operating temperature, single-photon detection from the visible to telecom wavelengths a

Sergei Buyalo

SRA-free condition for metric spaces (that is, spaces without Small Rough Angles) was introduced by Zolotov to study rectifiability of self-contracted curves in various metric spaces. We give a Moebius invariant version of this notion which allows to show that zz-distance associated with a respective Moebius structure on the circle is nondegenerate. This res

Muthucumaru Maheswaran, Robert Wenger, Richard Olaniyan, Salman Memon

For effective use of edge computing in an IoT application, we need to partition the application into tasks and map them into the cloud, fog (edge server), device levels such that the resources at the different levels are optimally used to meet the overall quality of service requirements. In this paper, we consider four concerns about application-to-fog mappi

Chao Wang, Richard Gerlach

A joint conditional autoregressive expectile and Expected Shortfall framework is proposed. The framework is extended through incorporating a measurement equation which models the contemporaneous dependence between the realized measures and the latent conditional expectile. Nonlinear threshold specification is further incorporated into the proposed framework.

Md. Helal Ahmed, Jagmohan Tanti

The determination of Jacobi sums, their congruences and cyclotomic numbers have been the object of attention for many years and there are large number of interesting results related to these in the literature. This survey aims at reviewing results concerning the diophantine systems for finding the cyclotomic numbers and coefficients of Jacobi sums and to ind

Alexander Fel&#39;shtyn, Malwina Zietek

In this paper we continue to study the Reidemeister zeta function. We prove Pólya -- Carlson dichotomy between rationality and a natural boundary for analytic behavior of the Reidemeister zeta function for a large class of automorphisms of Abelian groups. We also study dynamical representation theory zeta functions counting numbers of fixed irreducible repre

Miroslava Jordovic Pavlovic, Aleksandar Kupusinac, Marica Popovic

This paper presents a classification model for microphone type recognition in photoacoustic experiment. The classification model is obtained by applying a multilayer perceptron network on a large dataset of simulated experimental values. The model satisfies the basic requirements of a photoacoustic experiment: accuracy, reliability and real time operations.

Weiyao Zhao, Lei Chen, Zengji Yue, Zhi Li

As personal electronic devices increasingly rely on cloud computing for energy-intensive calculations, the power consumption associated with the information revolution is rapidly becoming an important environmental issue. Several approaches have been proposed to construct electronic devices with low energy consumption. Among these, the low-dissipation surfac

Bhavya Ajani

Fast and automatic algorithm to segment Brain (intracranial region) from computed tomography (CT) head images using combination of HU thresholding, identification of intracranial voxels through ray intersection with cranium, special binary erosion and connected components per slice.

Alexandros Karargyris, Ken C. L. Wong, Joy T. Wu, Mehdi Moradi

In many screening applications, the primary goal of a radiologist or assisting artificial intelligence is to rule out certain findings. The classifiers built for such applications are often trained on large datasets that derive labels from clinical notes written for patients. While the quality of the positive findings described in these notes is often reliab

John M. Abowd, Ian M. Schmutte, William Sexton, Lars Vilhuber

With vast databases at their disposal, private tech companies can compete with public statistical agencies to provide population statistics. However, private companies face different incentives to provide high-quality statistics and to protect the privacy of the people whose data are used. When both privacy protection and statistical accuracy are public good

J. Cernicharo, L. Velilla-Prieto, M. Agúndez, J. R. Pardo

We report on the detection of calcium isocyanide, CaNC, in the carbon-rich evolved star IRC+10216. We derived a column density for this species of (2.0$\pm$0.5)$\times$10$^{11}$ cm$^{-2}$. Based on the observed line profiles and the modelling of its emission through the envelope, the molecule has to be produced in the intermediate and outer layers of the cir

Joshua D Carmichael, Robert J Nemzek

Explosions near ground generate multiple geophysical waveforms in the radiation-dominated range of their signature fields. Multi-phenomological explosion monitoring (MultiPEM) at these ranges requires the predictive capability to forecast trigger rates of digital detectors that process such waveform data, and thereby accurately anticipate the probability tha

Anne E. Hafner, Johannes Krausser, Anđela Šarić

The molecular machinery of life is largely created via self-organisation of individual molecules into functional assemblies. Minimal coarse-grained models, where a whole macromolecule is represented by a small number of particles, can be of great value in identifying the main driving forces behind self-organisation in cell biology. Such models can incorporat

Francesco Muia, Michele Cicoli, Katy Clough, Francisco Pedro

Long-lived pseudo-solitonic objects, known as oscillons/oscillatons, which we collectively call real scalar stars, are ubiquitous in early Universe cosmology of scalar field theories. Typical examples are axions stars and moduli stars. Using numerical simulations in full general relativity to include the effects of gravity, we study the fate of real scalar s

Shabnam Sodagari

Non-orthogonal multiple access (NOMA) is a part of 5th generation (5G) communication systems. This article presents the underpinnings and underlying structures of the problem of NOMA user-channel allocation. Unlike the heuristics for NOMA user-channel allocation, the presented results are guaranteed to converge to a solution. In addition, the solutions are s

Nikki Lijing Kuang, Clement H. C. Leung

Rewards and punishments in different forms are pervasive and present in a wide variety of decision-making scenarios. By observing the outcome of a sufficient number of repeated trials, one would gradually learn the value and usefulness of a particular policy or strategy. However, in a given environment, the outcomes resulting from different trials are subjec

Fu Liu, Bhakti Chowkwale, Sergei A. Tretyakov

We show that a capacitive wireless power transfer device can be designed as a self-oscillating circuit using operational amplifiers. As the load and the capacitive wireless channels are part of the feedback circuit of the oscillator, the wireless power transfer can self-adjust to the optimal condition under the change of the load resistance and the transfer

Markus Tobias Prim

The Belle II experiment at the SuperKEKB energy-asymmetric $e^+e^-$ collider is a substantial upgrade of the B factory facility at the Japanese KEK laboratory. The design luminosity of the machine is $8\times10^{35}\, \mathrm{cm}^{-2}\mathrm{s}^{-1}$ and the Belle II experiment aims to record $50\, \mathrm{ab}^{-1}$ of data, a factor of 50 more than its pred

Tanveer Syeda-Mahmood, Hassan M. Ahmad, Nadeem Ansari, Yaniv Gur

Chest X-rays are the most common diagnostic exams in emergency rooms and hospitals. There has been a surge of work on automatic interpretation of chest X-rays using deep learning approaches after the availability of large open source chest X-ray dataset from NIH. However, the labels are not sufficiently rich and descriptive for training classification tools.

Alexey Drutsa

We study revenue optimization learning algorithms for repeated second-price auctions with reserve where a seller interacts with multiple strategic bidders each of which holds a fixed private valuation for a good and seeks to maximize his expected future cumulative discounted surplus. We propose a novel algorithm that has strategic regret upper bound of $O(\l

Chris J Mitchell

A recently proposed authenticated key agreement protocol is shown to be insecure. In particular, one of the two parties is not authenticated, allowing an active man in the middle opponent to replay old messages. The protocol is essentially an authenticated Diffie-Hellman key agreement scheme, and the lack of authentication allows an attacker to replay old me

Matías Valdés, Marcelo Fiori

We consider an important problem in signal processing, which consists in finding the sparsest solution of a linear system $Φx=b$. This problem has applications in several areas, but is NP-hard in general. Usually an alternative convex problem is considered, based on minimizing the (weighted) $\ell_{1}$ norm. For this alternative to be useful, weights should

Yufang Hou, Charles Jochim, Martin Gleize, Francesca Bonin

While the fast-paced inception of novel tasks and new datasets helps foster active research in a community towards interesting directions, keeping track of the abundance of research activity in different areas on different datasets is likely to become increasingly difficult. The community could greatly benefit from an automatic system able to summarize scien

Eric Smith

2-field functional integrals (2FFI) are an important class of solution methods for generating functions of dissipative processes, including discrete-state stochastic processes, dissipative dynamical systems, and decohering quantum densities. The stationary trajectories of these integrals describe a conserved current by Liouville&#39;s theorem, despite the fa

Aslı D. Uğurlu, Henri Thyrrestrup, Ravitej Uppu, Claudéric Ouellet-Plamondon

We report on the realization of a highly efficient optical spot-size converter for the end-face coupling of single photons from GaAs-based nanophotonic waveguides with embedded quantum dots. The converter is realized using an inverted taper and an epoxy polymer overlay providing a 1.3~$μ$m output mode field diameter. We demonstrate the collection of single p

Layla El Asri, Adam Trischler

End-to-end reinforcement learning agents learn a state representation and a policy at the same time. Recurrent neural networks (RNNs) have been trained successfully as reinforcement learning agents in settings like dialogue that require structured prediction. In this paper, we investigate the representations learned by RNN-based agents when trained with both

Deep Chatterjee, Peter E. Nugent, Patrick R. Brady, Chris Cannella

The last couple of decades have seen an emergence of transient detection facilities in various avenues of time domain astronomy which has provided us with a rich dataset of transients. The rates of these transients have implications in star formation, progenitor models, evolution channels and cosmology measurements. The crucial component of any rate calculat

Todd Eisworth

We prove a compactness theorem for pseudopower operations of the form $pp_{Γ(μ,σ)}(μ)$ where $\aleph_0<σ=cf(σ)\leq cf(μ)$. Our main tool is a result that has Shelah&#39;s cov vs. pp Theorem as a consequence. We also show that the failure of compactness in other situations has significant consequences for pcf theory, in particular, implying the existence of a

Bahadir Kucukgok, David J. Mandia, Jacob H. Leach, Keith R. Evans

We report the optical, electrical, and structural properties of Si doped $β$-Ga$_2$O$_3$ films grown on (010)-oriented $β$-Ga$_2$O$_3$ substrate via HVPE. Our results show that, despite growth rates that are more than one order of magnitude faster than MOCVD, films with mobility values of up to 95 cm$^2$V$^{-1}$s$^{-1}$ at a carrier concentration of 1.3$\tim

Xiaoyu Yin, Dagmar Gromann, Sebastian Rudolph

SPARQL is a highly powerful query language for an ever-growing number of Linked Data resources and Knowledge Graphs. Using it requires a certain familiarity with the entities in the domain to be queried as well as expertise in the language&#39;s syntax and semantics, none of which average human web users can be assumed to possess. To overcome this limitation

Mónica Clapp, Filomena Pacella

We study the critical Neumann problem \begin{equation*} \begin{cases} -Δu = |u|^{2^*-2}u &\text{in }Σ_ω,\\ \quad\frac{\partial u}{\partialν}=0 &\text{on }\partialΣ_ω, \end{cases} \end{equation*} in the unbounded cone $Σ_ω:=\{tx:x\inω\text{ and }t>0\}$, where $ω$ is an open connected subset of the unit sphere $\mathbb{S}^{N-1}$ in $\mathbb{R}^N$ with smooth b

Héctor Ramírez

In this Thesis by publication, we cover both phenomenological and theoretical approaches to the study of inflation: from model-independent parametrizations to modifications of gravity. In a review style, we provide a short introduction to the standard cosmological model and an overview of the dynamics of the canonical single-field inflationary scenario---inc

Mohammad Khatibi, Sara Ahmed

The growing penetration of distributed energy resources (DERs) has increased the complexity of the power system due to their intermittent characteristics and lower inertial response, such as photovoltaic (PV) systems and wind turbines. This restructuring of the power system has a considerable effect on the transient response of the system resulting in inter-

Jared Strader, Jennifer Nguyen, Christopher Tatsch, Yixin Du

Robotic pollinators not only can aid farmers by providing more cost effective and stable methods for pollinating plants but also benefit crop production in environments not suitable for bees such as greenhouses, growth chambers, and in outer space. Robotic pollination requires a high degree of precision and autonomy but few systems have addressed both of the

Shubham Rathi

With the advent of GDPR, the domain of explainable AI and model interpretability has gained added impetus. Methods to extract and communicate visibility into decision-making models have become legal requirement. Two specific types of explanations, contrastive and counterfactual have been identified as suitable for human understanding. In this paper, we propo

Urs Braun, Anais Harneit, Giulio Pergola, Tommaso Menara

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brainwide switching between activity states. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and p

Yuezun Li, Xin Yang, Baoyuan Wu, Siwei Lyu

Recent years have seen fast development in synthesizing realistic human faces using AI technologies. Such fake faces can be weaponized to cause negative personal and social impact. In this work, we develop technologies to defend individuals from becoming victims of recent AI synthesized fake videos by sabotaging would-be training data. This is achieved by di

Takuto Kawakami, Masatoshi Sato

In iron-based superconductors, band inversion of $d$- and $p$-orbitals yields Dirac semimetallic states. We theoretically investigate their topological properties in normal and superconducting phases, based on the tight-binding model involving full symmetry of the materials. We demonstrate that a Cooper pair between electrons with $d$- and $p$-orbitals relev

Zhen Wang, Xiang Yue, Soheil Moosavinasab, Yungui Huang

Unstructured clinical texts contain rich health-related information. To better utilize the knowledge buried in clinical texts, discovering synonyms for a medical query term has become an important task. Recent automatic synonym discovery methods leveraging raw text information have been developed. However, to preserve patient privacy and security, it is usua

M. Klasen

We review current results on physics with photons at the LHC and discuss realistic perspectives of photon physics at future colliders. In particular, we focus on Standard Model (SM) measurements with photons at the upcoming high-luminosity and a possible high-energy LHC as well as jet measurements at an Electron-Ion Collider (EIC) to be constructed either at

Félix Cabello Sánchez, Sheldon Dantas, Vladimir Kadets, Sun Kwang Kim

We study Banach spaces whose group of isometries acts micro-transitively on the unit sphere. We introduce a weaker property, which one-complemented subspaces inherit, that we call uniform micro-semitransitivity. We prove a number of results about both micro-transitive and uniformly micro-semitransitive spaces, including that they are uniformly convex and uni

Ivan Vitev

n these proceedings I discuss several recent developments in the physics of heavy flavor jets in heavy ion collisions. i) The dijet mass modification in nucleus-nucleus reactions has been proposed as a new observable with enhanced sensitivity to parton energy loss in nuclear matter. It also enables more precise studies of heavy quark mass effects on parton s

E. J. Watkins, N. Peretto, K. Marsh, G. A. Fuller

Feedback from high-mass stars shapes the ISM of galaxies and thereby impacts gas that will form future generations of stars. However, due to our inability to track the time evolution of individual molecular clouds, quantifying the exact role of feedback on their star formation history is an observationally challenging task. In the present study, we take adva

Yonglong Xie, Biao Lian, Berthold Jäck, Xiaomeng Liu

The discovery of superconducting and insulating states in magic angle twisted bilayer graphene (MATBG) has ignited considerable interest in understanding the nature of electronic interactions in this chemically pristine material system. The phenomenological similarity of the MATBG transport properties as a function of doping with those of the high-Tc cuprate