February 2019 arXiv papers — page 11

David J. Nott, Max Seah, Luai Al-Labadi, Michael Evans

Any Bayesian analysis involves combining information represented through different model components, and when different sources of information are in conflict it is important to detect this. Here we consider checking for prior-data conflict in Bayesian models by expanding the prior used for the analysis into a larger family of priors, and considering a margi

Rongqian Wang, Jincheng Lu, Jian-Hua Jiang

Graphene---hexagonal-boron-nitride---InSb near-field structures are designed and optimized to enhance the output power and energy efficiency of the thermophotovoltaic systems working in the temperature range of common industrial waste heat, $400~\rm K \sim 800~\rm K$, which is also the working temperature range for conventional thermoelectric devices. We sho

Fabian Steiner, Emna Ben Yacoub, Balazs Matuz, Gianluigi Liva

Low complexity decoding algorithms are necessary to meet data rate requirements in excess of 1 Tbps. In this paper, we study one and two bit message passing algorithms for belief propagation decoding of low-density parity-check (LDPC) codes and analyze them by density evolution. The variable nodes (VNs) exploit soft information from the channel output. To de

G. Buldgen, S. J. A. J. Salmon, A. Noels, V. A. Baturin

The Sun is the most studied of stars and a laboratory of fundamental physics. However, the understanding of our star is stained by the solar modelling problem which can stem from various causes. We combine inversions of sound speed, an entropy proxy and the Ledoux discriminant with the position of the base of the convective zone and the photospheric helium a

Y. Zhao, L. Rezac, P. Hartogh, J. Ji

Our aim is to investigate early activity (July 2014) of 67P/CG with 3D coma and radiative transfer modeling of MIRO measurements, accounting for nucleus shape, illumination, and orientation of the comet. We investigate MIRO line shape information for spatial distribution of water activity on the nucleus during the onset of activity. During this period we sho

Itsikiantsoa Randrianantenaina, Megumi Kaneko, Hayssam Dahrouj, Hesham ElSawy

Non-Orthogonal Multiple Access (NOMA) and Fog Radio Access Networks (FRAN) are promising candidates within the 5G and beyond systems. This work examines the benefit of adopting NOMA in an FRAN architecture with constrained capacity fronthaul. The paper proposes methods for optimizing joint scheduling and power adaptation in the downlink of a NOMA-based FRAN

Wen Chen

In this paper, the reduction of Feynman integrals in the parametric representation is considered. This method proves to be more efficient than the integration-by-part (IBP) method in the momentum space. Tensor integrals can directly be parametrized without performing tensor reductions. The integrands of parametric integrals are functions of Lorentz scalars,

Donatella Iacono, Marco Manetti

We investigate the deformations of pairs $(X,L)$, where $L$ is a line bundle on a smooth projective variety $X$, defined over an algebraically closed field $\mathbb{K}$ of characteristic 0. In particular, we prove that the DG-Lie algebra controlling the deformations of the pair $(X,L)$ is homotopy abelian whenever $X$ has trivial canonical bundle, and so the

Sebastiaan Koning, Caspar Greeven, Eric Postma

Despite their successes in the field of self-learning AI, Convolutional Neural Networks (CNNs) suffer from having too many trainable parameters, impacting computational performance. Several approaches have been proposed to reduce the number of parameters in the visual domain, the Inception architecture [Szegedy et al., 2016] being a prominent example. This r

Haggai Roitman, Avigdor Gal, Louiqa Raschid

Advances in Web technology enable personalization proxies that assist users in satisfying their complex information monitoring and aggregation needs through the repeated querying of multiple volatile data sources. Such proxies face a scalability challenge when trying to maximize the number of clients served while at the same time fully satisfying clients' co

Jonathan Mayzel, Victor Steinberg, Atul Varshney

Electron transport in two-dimensional conducting materials such as graphene, with dominant electron-electron interaction, exhibits unusual vortex flow that leads to a nonlocal current-field relation (negative resistance), distinct from the classical Ohm's law. The transport behavior of these materials is best described by low Reynolds number hydrodynamics, w

James H. Matthews, Anthony R. Bell, Anabella T. Araudo, Katherine M. Blundell

The origin of ultrahigh energy cosmic rays (UHECRs) is an open question. In this proceeding, we first review the general physical requirements that a source must meet for acceleration to 10-100 EeV, including the consideration that the shock is not highly relativistic. We show that shocks in the backflows of radio galaxies can meet these requirements. We dis

Rainer Dahlhaus, Stefan Richter

Two adaptive bandwidth selection methods for nonparametric estimators in locally stationary processes are proposed. We investigate a cross validation approach and a method based on contrast minimization and derive asymptotic properties of both methods. The results are applicable for different statistics under a broad setting of locally stationarity including

Andreas Maurischat

In this short note, we answer a question raised by M. Papikian on a universal upper bound for the degree of the extension of $K_\infty$ given by adjoining the periods of a Drinfeld module of rank 2. We show that contrary to the rank 1 case such a universal upper bound does not exist, and the proof generalises to higher rank. Moreover, we give an upper and lo

Hao Zhang, Xiuyan Yang, Jianwei Ma

We propose a convolutional neural network (CNN) denoising based method for seismic data interpolation. It provides a simple and efficient way to break though the lack problem of geophysical training labels that are often required by deep learning methods. The new method consists of two steps: (1) Train a set of CNN denoisers from natural image clean-noisy pa

Gisa Schäfer, Yasuyoshi Yonezawa

We consider colored operads and their actions on categories. As a special example we construct a cobordism category with a colored operad action arising from oriented planar arc diagrams. This is used to construct an invariant of oriented tangle diagrams with values in the homotopy category attached to the cobordism category. Motivated by Bar-Natan's categor

Vincenzo Macrí, Franco Nori, Salvatore Savasta, David Zueco

It has been shown elsewhere that two spatially separated atoms can jointly absorb one photon, whose frequency is equal to the sum of the transition frequencies of the two atoms. We describe this process in the presence of an ensemble of many two-level atoms, and show that it can be used to generate spin squeezing and entanglement. This resonant collective pr

Bo Yang, Wenbin Lin

We present the analytical post-Newtonian solutions for the test particle's motion in the Reissner-Nordstr\"{o}m spacetime. The solutions are formulated in the Wagoner-Will representation, the Epstein-Haugan representation, the Brumberg representation, and the Damour-Deruelle representation, respectively. The relations between the (post-)Keplerian parameters

Nikola Tomasevic, Dejan Paunovic, Sanja Vranes

A content recommender system or a recommendation system represents a subclass of information filtering systems which seeks to predict the user preferences, i.e. the content that would be most likely positively "rated" by the user. Nowadays, the recommender systems of OpenCourseWare (OCW) platforms typically generate a list of recommendations in one of two wa

F. Chu, F. Skiff

Extensive information, such as ion temperature and wave-particle interactions, can be obtained by direct measurement of ion distribution functions using laser-induced fluorescence (LIF). This nonintrusive plasma diagnostic provides an important window into the ion motions in phase-space. Previous simulation results suggest that LIF measurements, which are pe

Tomoyuki Obuchi, Ayaka Sakata

We investigate the signal reconstruction performance of sparse linear regression in the presence of noise when piecewise continuous nonconvex penalties are used. Among such penalties, we focus on the SCAD penalty. The contributions of this study are three-fold: We first present a theoretical analysis of a typical reconstruction performance, using the replica

Peng Jiang, Yingrui Yang, Gann Bierner, Fengjie Alex Li

Genealogy research is the study of family history using available resources such as historical records. Ancestry provides its customers with one of the world's largest online genealogical index with billions of records from a wide range of sources, including vital records such as birth and death certificates, census records, court and probate records among m

Hao Zhou, Minlie Huang, Yishun Mao, Changlei Zhu

Advertising (ad for short) keyword suggestion is important for sponsored search to improve online advertising and increase search revenue. There are two common challenges in this task. First, the keyword bidding problem: hot ad keywords are very expensive for most of the advertisers because more advertisers are bidding on more popular keywords, while unpopul

K. Dajani, M. R. de Lepper, E. A. Robinson

We introduce the concept of Minkowski normality, a different type of normality for the regular continued fraction expansion. We use the ordering \[ \frac{1}{2},\quad \frac{1}{3}, \frac{2}{3},\quad \frac{1}{4}, \frac{3}{4},\frac{2}{5}, \frac{3}{5},\quad \frac{1}{5}, \cdots \] of rationals obtained from the Kepler tree to give a concrete construction of an inf

Detchat Samart

The congruent number elliptic curves are defined by $E_d: y^2=x^3-d^2x$, where $d\in \mathbb{N}.$ We give a simple proof of a formula for $L(\mathrm{Sym}^2(E_d),3)$ in terms of the determinant of the elliptic trilogarithm evaluated at some degree zero divisors supported on the torsion points on $E_d(\overline{\mathbb{Q}})$.

Haggai Roitman

This work presents a general query term weighting approach based on query performance prediction (QPP). To this end, a given term is weighed according to its predicted effect on query performance. Such an effect is assumed to be manifested in the responses made by the underlying retrieval method for the original query and its (simple) variants in the form of

Yiming Hu, Jianquan Li, Xianlei Long, Shenhua Hu

Deep neural networks (DNNs) have achieved great success in a wide range of computer vision areas, but the applications to mobile devices is limited due to their high storage and computational cost. Much efforts have been devoted to compress DNNs. In this paper, we propose a simple yet effective method for deep networks compression, named Cluster Regularized

Yael Hitron, Merav Parter

We consider the task of measuring time with probabilistic threshold gates implemented by bio-inspired spiking neurons. In the model of spiking neural networks, network evolves in discrete rounds, where in each round, neurons fire in pulses in response to a sufficiently high membrane potential. This potential is induced by spikes from neighboring neurons that

S. N. Kudryavtsev

The article examines Nikolskii and Besov spaces with norms defined using "$L_p$-averaged" mixed moduli of continuity of functions of appropriate orders, instead of mixed moduli of continuity of known orders for certain mixed derivative functions. The author builds continuous linear mappings of such spaces of functions defined on cube $ I^d, $ to ordinary Nik

Rabin Banerjee

In his 1963 paper, Dirac [1] gave `A Remarkable Representation of the 3 + 2 de- Sitter Group'. We reproduce this representation using a generalised Jordan map which is motivated by the infinitesimal symplectic transformations related to the four dimensional symplectic group Sp(4). A physical picture of Dirac's representation is also discussed.

Soumajyoti Sarkar, Hamidreza Alvari, Paulo Shakarian

Information diffusion mechanisms based on social influence models are mainly studied using likelihood of adoption when active neighbors expose a user to a message. The problem arises primarily from the fact that for the most part, this explicit information of who-exposed-whom among a group of active neighbors in a social network, before a susceptible node is

Masoud Badiei Khuzani, Hongyi Ren, Md Tauhidul Islam, Lei Xing

We propose a novel data-driven method to learn a mixture of multiple kernels with random features that is certifiabaly robust against adverserial inputs. Specifically, we consider a distributionally robust optimization of the kernel-target alignment with respect to the distribution of training samples over a distributional ball defined by the Kullback-Leible

Yiming Hu, Siyang Sun, Jianquan Li, Jiagang Zhu

Channel pruning, which seeks to reduce the model size by removing redundant channels, is a popular solution for deep networks compression. Existing channel pruning methods usually conduct layer-wise channel selection by directly minimizing the reconstruction error of feature maps between the baseline model and the pruned one. However, they ignore the feature

Navoneel Chakrabarty

Now-a-days, derogatory comments are often made by one another, not only in offline environment but also immensely in online environments like social networking websites and online communities. So, an Identification combined with Prevention System in all social networking websites and applications, including all the communities, existing in the digital world

Benjamin J. Meyer, Tom Drummond

State-of-the-art deep neural network recognition systems are designed for a static and closed world. It is usually assumed that the distribution at test time will be the same as the distribution during training. As a result, classifiers are forced to categorise observations into one out of a set of predefined semantic classes. Robotic problems are dynamic an

Malte Gerhold, Orr Shalit

Let $q = e^{i \theta} \in \mathbb{T}$ (where $\theta \in \mathbb{R}$), and let $u,v$ be $q$-commuting unitaries, i.e., $u$ and $v$ are unitaries such that $vu = quv$. In this paper we find the optimal constant $c = c_\theta$ such that $u,v$ can be dilated to a pair of operators $c U, c V$, where $U$ and $V$ are commuting unitaries. We show that \[ c_\theta =

Alban Urvoy, Zachary Vendeiro, Joshua Ramette, Albert Adiyatullin

We present a method for producing three-dimensional Bose-Einstein condensates using only laser cooling. The phase transition to condensation is crossed with $2.5 {\times} 10^{4}$ $^{87}\mathrm{Rb}$ atoms at a temperature of $T_{\mathrm{c}} = 0.6\ \mu\mathrm{K}$ after 1.4 s of cooling. Atoms are trapped in a crossed optical dipole trap and cooled using Raman

Xinsheng Xuan, Bo Peng, Wei Wang, Jing Dong

Recently the GAN generated face images are more and more realistic with high-quality, even hard for human eyes to detect. On the other hand, the forensics community keeps on developing methods to detect these generated fake images and try to guarantee the credibility of visual contents. Although researchers have developed some methods to detect generated ima

Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki

We suggest a new idea of Editorial Network - a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted sentences. Our network tries to imitate the decision process of a human editor during summarization. Within such a process, each extracted sentence may be either kept untouched, reph

Seo-Jin Kim, K. -W. Lee

Using ab initio calculations based on the correlated band theory, we have investigated the quasi-one-dimensional chain system $\beta$-V$_2$O(PO$_4$), showing both charge and spin orderings. Even in the uncorrelated region, the pure transition from the tetragonal to the monoclinic structure leads to a sizable charge difference between the two types of V ions,

Manuel de la Cruz, Néstor Gaspar, Román Linares

In this paper we revisit the construction by which the $SL(2,\mathbb{R})$ symmetry of the Euler equations allows to obtain the simple pendulum from the rigid body. We begin reviewing the original relation found by Holm and Marsden in which, starting from the two Casimir functions of the extended rigid body with Lie algebra $ISO(2)$ and introducing a proper m

Michael Haythorpe, Alex Newcombe

The exact crossing number is only known for a small number of families of graphs. Many of the families for which crossing numbers have been determined correspond to cartesian products of two graphs. Here, the cartesian product of the Sunlet graph, denoted $\mathcal{S}_n$, and the Star graph, denoted $K_{1,m}$, is considered for the first time. It is proved t

Vladimir Ejov, Jerzy A Filar, Michael Haythorpe, John F Roddick

An instance of Hamiltonian cycle problem can be solved by converting it to an instance of Travelling salesman problem, assigning any choice of weights to edges of the underlying graph. In this note we demonstrate that, for difficult instances, choosing the edge weights to be the resistance distance between its two incident vertices is often a good choice. We

Zlatko K. Minev

A quantum system driven by a weak deterministic force while under strong continuous energy measurement exhibits quantum jumps between its energy levels (Nagourney et al., 1986, Sauter et al., 1986, Bergquist et al., 1986). This celebrated phenomenon is emblematic of the special nature of randomness in quantum physics. The times at which the jumps occur are r

Michael Haythorpe, Jerzy Filar

We consider a direct conversion of the, classical, set splitting problem to the directed Hamiltonian cycle problem. A constructive procedure for such a conversion is given, and it is shown that the input size of the converted instance is a linear function of the input size of the original instance. A proof that the two instances are equivalent is given, and

Chong Yu, Qiong Liu, Cong Chen, Jin Wang

Heterogeneity is ubiquitous in stem cells (SC), cancer cells (CS), and cancer stem cells (CSC). SC and CSC heterogeneity is manifested as diverse sub-populations with self-renewing and unique regeneration capacity. Moreover, the CSC progeny possesses multiple plasticity and cancerous characteristics. Many studies have demonstrated that cancer heterogeneity i

Michael Haythorpe

The FHCP Challenge Set, comprising of 1001 instances of Hamiltonian cycle problem, is introduced. This set is the first to contain instances of Hamiltonian cycle problem for which the primary difficulty is the underlying graph structure, rather than simply size. A summary of the kinds of graphs contained in the FHCP Challenge Set is given. A discussion of th

Michael Haythorpe

A constructive method is provided that outputs a directed graph which is named a broken crown graph, containing $5n-9$ vertices and $k$ Hamiltonian cycles for any choice of integers $n \geq k \geq 4$. The construction is not designed to be minimal in any sense, but rather to ensure that the graphs produced remain non-trivial instances of the Hamiltonian cycl

Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov

Active learning methods for neural networks are usually based on greedy criteria which ultimately give a single new design point for the evaluation. Such an approach requires either some heuristics to sample a batch of design points at one active learning iteration, or retraining the neural network after adding each data point, which is computationally ineff

Jerzy A Filar, Michael Haythorpe, Richard Taylor

We address the question of whether it may be worthwhile to convert certain, now classical, NP-complete problems to one of a smaller number of kernel NP-complete problems. In particular, we show that Karp's classical set of 21 NP-complete problems contains a kernel subset of six problems with the property that each problem in the larger set can be converted t

Imon Banerjee, Luis de Sisternes, Joelle Hallak, Theodore Leng

We propose a hybrid sequential deep learning model to predict the risk of AMD progression in non-exudative AMD eyes at multiple timepoints, starting from short-term progression (3-months) up to long-term progression (21-months). Proposed model combines radiomics and deep learning to handle challenges related to imperfect ratio of OCT scan dimension and train

Jerzy A Filar, Michael Haythorpe, Walter Murray

We present an algorithm to find the determinant and its first and second derivatives of a rank-one corrected generator matrix of a doubly stochastic Markov chain. The motivation arises from the fact that the global minimiser of this determinant solves the Hamiltonian cycle problem. It is essential for algorithms that find global minimisers to evaluate both f

Raj Agrawal, Chandler Squires, Karren Yang, Karthik Shanmugam

Determining the causal structure of a set of variables is critical for both scientific inquiry and decision-making. However, this is often challenging in practice due to limited interventional data. Given that randomized experiments are usually expensive to perform, we propose a general framework and theory based on optimal Bayesian experimental design to se

Diego Berti

We consider the (viscosity) solution $u(x,t)$ of the nonlinear evolution equation $u_t-\Delta^G_p u=0$ in a (not necessarily bounded) domain $\Omega$, such that $u=0$ in $\Omega$ at time $t=0$ and $u=1$ on the boundary of $\Omega$ at all times. Here, $\Delta_p^G$ is the game-theoretic $p$-laplacian, a $1$-homogeneous version of the standard $p$-laplacian. Al

Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider

The ubiquity of accelerators in high-performance computing has driven programming complexity beyond the skill-set of the average domain scientist. To maintain performance portability in the future, it is imperative to decouple architecture-specific programming paradigms from the underlying scientific computations. We present the Stateful DataFlow multiGraph

Michael Haythorpe

It is well known that 3--regular graphs with arbitrarily large girth exist. Three constructions are given that use the former to produce non-Hamiltonian 3--regular graphs without reducing the girth, thereby proving that such graphs with arbitrarily large girth also exist. The resulting graphs can be 1--, 2-- or 3--edge-connected depending on the construction

Jerzy A Filar, Michael Haythorpe, Serguei Rossomakhine

We analyse a polyhedron which contains the convex hull of all Hamiltonian cycles of a given undirected connected cubic graph. Our constructed polyhedron is defined by polynomially-many linear constraints in polynomially-many continuous (relaxed) variables. Clearly, the emptiness of the constructed polyhedron implies that the graph is non-Hamiltonian. However

Tejaswi Venumadhav, Barak Zackay, Javier Roulet, Liang Dai

In this paper, we report on the construction of a new and independent pipeline for analyzing the public data from the first observing run of advanced LIGO for mergers of compact binary systems. The pipeline incorporates different techniques and makes independent implementation choices in all its stages including the search design, the method to construct tem

Kaori Fuyuto, Xiao-Gang He, Gang Li, Michael Ramsey-Musolf

We introduce a scenario for CP-violating (CPV) dark photon interactions in the context of non-abelian kinetic mixing. Assuming an effective field theory that extends the Standard Model (SM) field content with an additional $U(1)$ gauge boson ($X$) and a $SU(2)_L$ triplet scalar, we show that there exist both CP-conserving and CPV dimension five operators inv

Wenhu Chen, Yu Su, Yilin Shen, Zhiyu Chen

With the rapid development in deep learning, deep neural networks have been widely adopted in many real-life natural language applications. Under deep neural networks, a pre-defined vocabulary is required to vectorize text inputs. The canonical approach to select pre-defined vocabulary is based on the word frequency, where a threshold is selected to cut off

Tomoyuki Kimoto, Tatsuya Uezu

We study correspondence between a phase oscillator network with distributed natural frequencies and a classical XY model at finite temperatures with the same random and frustrated interactions used in the Sherrington-Kirkpatrick model. We perform numerical calculations of the spin glass order parameter $q$ and the distributions of the local fields. As a resu

Pouya Baniasadi, Vladimir Ejov, Jerzy A Filar, Michael Haythorpe

We present a polynomial complexity, deterministic, heuristic for solving the Hamiltonian Cycle Problem (HCP) in an undirected graph of order $n$. Although finding a Hamiltonian cycle is not theoretically guaranteed, we have observed that the heuristic is successful even in cases where such cycles are extremely rare, and it also performs very well on all HCP

Richeng Jin, Xiaofan He, Huaiyu Dai

The recent advances in sensor technologies and smart devices enable the collaborative collection of a sheer volume of data from multiple information sources. As a promising tool to efficiently extract useful information from such big data, machine learning has been pushed to the forefront and seen great success in a wide range of relevant areas such as compu

Jike Lyu, Ignasi Fina, Raul Solanas, Josep Fontcuberta

The metastable orthorhombic phase of hafnia is generally obtained in polycrystalline films, whereas in epitaxial films, its formation has been much less investigated. We have grown Hf0.5Zr0.5O2 films by pulsed laser deposition, and the growth window (temperature and oxygen pressure during deposition and film thickness) for epitaxial stabilization of the ferr

Sofiya Ostrovska, Mikhail Ostrovskii

The paper is devoted to the geometry of transportation cost spaces and their generalizations introduced by Melleray, Petrov, and Vershik (2008). Transportation cost spaces are also known as Arens-Eells, Lipschitz-free, or Wasserstein $1$ spaces. In this work, the existence of metric spaces with the following properties is proved: (1) uniformly discrete infin

F. Yang, Y. Zhao, Y. Qi, Y. Z. Tan

Hydrogen detection is of great importance in chemical and energy industries. Optical fiber hydrogen sensors show flexibility and compactness and have the potential for distributed analysis. However, traditional fiber sensors encounter a challenge for light to interact with hydrogen directly since hydrogen only display weak quadrupole absorption, and metallic

Jun Geng, Jinping Zhuge

In this paper, we consider a family of second-order elliptic systems subject to a periodically oscillating Robin boundary condition. We establish the qualitative homogenization theorem on any Lipschitz domains satisfying a non-resonance condition. We also use the quantitative estimates of oscillatory integrals to obtain the dimension-dependent convergence ra

Barak Zackay, Tejaswi Venumadhav, Liang Dai, Javier Roulet

We report a new binary black hole merger in the publicly available LIGO First Observing Run (O1) data release. The event has an inverse false alarm rate of one per six years in the detector-frame chirp-mass range $\mathcal{M}^{\rm det} \in [20,40]M_\odot$ in a new independent analysis pipeline that we developed. Our best estimate of the probability that the

Shuai Wang, Minghua Xia, Yik-Chung Wu

Collecting data from massive Internet of Things (IoT) devices is a challenging task, since communication circuits are power-demanding while energy supply at IoT devices is limited. To overcome this challenge, backscatter communication emerges as a promising solution as it eliminates radio frequency components in IoT devices. Unfortunately, the transmission r

Jonas B. Araujo, A. H. Blin, Marcos Sampaio, Manoel M. Ferreira

The electric dipole moment (EDM) of an atom could arise also from $P$-odd and $T$-odd electron-nucleon couplings. In this work we investigate a general class of dimension-$6$ electron-nucleon ($e$-$N$) nonminimal interactions mediated by Lorentz-violating (LV) tensors of rank ranging from $1$ to $4$. The possible couplings are listed as well as their behavio

Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff

We study the Maximum Independent Set problem for geometric objects given in the data stream model. A set of geometric objects is said to be independent if the objects are pairwise disjoint. We consider geometric objects in one and two dimensions, i.e., intervals and disks. Let $\alpha$ be the cardinality of the largest independent set. Our goal is to estimat

Zhenyu Duan, Martin Renqiang Min, Li Erran Li, Mingbo Cai

In spite of achieving revolutionary successes in machine learning, deep convolutional neural networks have been recently found to be vulnerable to adversarial attacks and difficult to generalize to novel test images with reasonably large geometric transformations. Inspired by a recent neuroscience discovery revealing that primate brain employs disentangled s

Aleksey Buzmakov

In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons that are likely to buy a new product would reduce the amount of spam. In this chapter, we review the methods to estimate

Jindong Chen, Ao Wang, Jiangjie Chen, Yanghua Xiao

Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very rare. In this paper, we focus on automatic Chinese taxonomy construction and propose an effective generation and verification framework to build a large-scale and high-quality Chine

Pedro Pérez-Aros

In this work, we show the consistency of an approach for solving robust optimization problems using sequences of sub-problems generated by ergodic measure preserving transformations. The main result of this paper is that the minimizers and the optimal value of the sub-problems converge, in some sense, to the minimizers and the optimal value of the initial pr

Takuya Hosokawa

We study the weighted composition operators between the Lipschitz space and the space of bounded functions on the set of vertices of an infinite tree. We characterized the boundedness, the compactness, and the boundedness from below of weighted composition operators. We also determine the isometric weighted composition operators.

Carlos Floyd, Garegin A. Papoian, Christopher Jarzynski

Quantifying entropy production in various active matter phases will open new avenues for probing self-organization principles in these far-from-equilibrium systems. It has been hypothesized that the dissipation of free energy by active matter systems may be optimized to produce highly dissipative dynamical states, hence, leading to spontaneous emergence of m

Debdeep Sarkar, Said Mikki, Yahia Antar

In this paper, we completely eliminate all numerical integrations needed to compute the far-field envelope cross-correlation (ECC) in multiple-input-multiple-output (MIMO) systems by deriving accurate and efficient analytical expressions for the frequency-domain cross-correlation Green's functions (CGF), the most fundamental electromagnetic kernel needed for

Nayyer Aafaq, Naveed Akhtar, Wei Liu, Syed Zulqarnain Gilani

Automatic generation of video captions is a fundamental challenge in computer vision. Recent techniques typically employ a combination of Convolutional Neural Networks (CNNs) and Recursive Neural Networks (RNNs) for video captioning. These methods mainly focus on tailoring sequence learning through RNNs for better caption generation, whereas off-the-shelf vi

Maryam Hasani-Shoreh, María-Yaneli Ameca-Alducin, Wilson Blaikie, Frank Neumann

Evolutionary algorithms have been widely applied for solving dynamic constrained optimization problems (DCOPs) as a common area of research in evolutionary optimization. Current benchmarks proposed for testing these problems in the continuous spaces are either not scalable in problem dimension or the settings for the environmental changes are not flexible. M

Pengyu Chen, Xuping Zhang, Yongxiang Li

This paper deals with the following Cauchy problem to nonlinear time fractional non-autonomous integro-differential evolution equation of mixed type via measure of noncompactness $$ \left\{\begin{array}{ll} ^CD^{\alpha}_tu(t)+A(t)u(t)= f(t,u(t),(Tu)(t), (Su)(t)),\quad t\in [0,a], \\[12pt] u(0)=A^{-1}(0)u_0 \end{array} \right. $$ in infinite-dimensional Banac

Eric Liang, Hang Zhu, Xin Jin, Ion Stoica

Packet classification is a fundamental problem in computer networking. This problem exposes a hard tradeoff between the computation and state complexity, which makes it particularly challenging. To navigate this tradeoff, existing solutions rely on complex hand-tuned heuristics, which are brittle and hard to optimize. In this paper, we propose a deep reinfor

Myung Hwan Seo, Sueyoul Kim, Young-Joo Kim

We develop a Stata command xthenreg to implement the first-differenced GMM estimation of the dynamic panel threshold model, which Seo and Shin (2016, Journal of Econometrics 195: 169-186) have proposed. Furthermore, We derive the asymptotic variance formula for a kink constrained GMM estimator of the dynamic threshold model and include an estimation algorith

Mehmet Celik, Sonmez Sahutoglu, Emil J. Straube

Let $1\leq q\leq (n-1)$. We first show that a necessary condition for a Hankel operator on $(0,q-1)$-forms on a convex domain to be compact is that its symbol is holomorphic along $q$-dimensional analytic varieties in the boundary. Because maximal estimates (equivalently, a comparable eigenvalues condition on the Levi form of the boundary) turn out to be fav

Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie

TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production. TensorFlow, which TensorFlow Eager extends, requires users to represent computations as dataflow graphs; this permits compiler optimizations and simplifies deployment but hinders rapid p

Shuchi Chawla, Yifeng Teng, Christos Tzamos

Multi-item mechanisms can be very complex offering many different bundles to the buyer that could even be randomized. Such complexity is thought to be necessary as the revenue gaps between randomized and deterministic mechanisms, or deterministic and simple mechanisms are huge even for additive valuations. We challenge this conventional belief by showing tha

Federico Paratore, Evgeniy Boyko, Govind V. Kaigala, Moran Bercovici

We experimentally demonstrate the phenomenon of electroosmotic dipole flow that occurs around a localized surface charge region under the application of an external electric field in a Hele-Shaw cell. We use localized deposition of polyelectrolytes to create well-controlled surface charge variations, and show that for a disk-shaped spot, the internal pressur

Kyoung-Duck Park, Molly A. May, Haixu Leng, Jiarong Wang

Optical cavities can enhance and control light-matter interactions. This has recently been extended to the nanoscale, and with single emitter strong coupling regime even at room temperature using plasmonic nano-cavities with deep sub-diffraction-limited mode volumes. However, with emitters in static nano-cavities, this limits the ability to tune coupling str

Mishall Al-Zubaidie, Zhongwei Zhang, Ji Zhang

Public-key cryptography algorithms, especially elliptic curve cryptography (ECC) and elliptic curve digital signature algorithm (ECDSA) have been attracting attention from many researchers in different institutions because these algorithms provide security and high performance when being used in many areas such as electronic-healthcare, electronic-banking, e

Chenyang Xu, Liangde Tao, Huajingling Wu, Deshi Ye

In this paper, we consider the bandwidth-delay-hop constrained routing problem in large-scaled software defined networks. A number of demands, each of which specifies a source vertex and a sink vertex, are required to route in a given network. We are asked to select a subset of demands, and assign a routing path for each selected demand without violating the

Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas Kolala Venkataramanaiah

The computational demands of computer vision tasks based on state-of-the-art Convolutional Neural Network (CNN) image classification far exceed the energy budgets of mobile devices. This paper proposes FixyNN, which consists of a fixed-weight feature extractor that generates ubiquitous CNN features, and a conventional programmable CNN accelerator which proce

Yao Liu, Ying Tai, Jilin Li, Shouhong Ding

In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-world systems serving for millions of users. Specifically, our method first extracts the normal cues via light reflection analysis, and then uses an end-to-end trainable multi-task Co

Yang Lu, Xiaolu Liu, Hongwei Liu, Yun Wang

homo/heterojunction renders fascinating electronic, optical, mechanical, chemical properties, yet a facile synthesis of this structure remains a challenge.

H. O. Jeschke, H. Nakano, T. Sakai

We investigate the connection between highly frustrated kagome based Hamiltonians and a recently synthesized family of materials containing Ti3+ S=1/2 ions. Employing a combination of all electron density functional theory and numerical diagonalization techniques, we establish the Heisenberg Hamiltonians for the distorted kagome antiferromagnets Rb2NaTi3F12,

Paul Sobaje

We show that the characters of tilting modules can be used, in a concrete and explicit way, to obtain the simple characters of a connected reductive algebraic group $G$ over an algebraically closed field $\Bbbk$ of characteristic $p$, for all $p$. Thus, once a formula for the characters of the indecomposable tilting $G$-modules has been found, a formula for

Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu

Network alignment, in general, seeks to discover the hidden underlying correspondence between nodes across two (or more) networks when given their network structure. However, most existing network alignment methods have added assumptions of additional constraints to guide the alignment, such as having a set of seed node-node correspondences across the networ

Eiji Akiyama, Eduard I. Vorobyov, Hauyu Baobabu Liu, Ruobing Dong

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the CO ($J$=2--1) line emission from the protoplanetary disk around T-Tauri star SU Aurigae (hereafter SU Aur). Previous observations in optical and near infrared wavelengths find a unique structure in SU Aur. One of the highlights of the observational results is that an extended

Kazunori Shinohara

Addition formulas exist in trigonometric functions. Double-angle and half-angle formulas can be derived from these formulas. Moreover, the relation equation between the trigonometric function and the hyperbolic function can be derived using an imaginary number. The inverse hyperbolic function $\mathrm{arsinh}(r)=\int_{0}^{r} \frac{1}{\sqrt{1+t^2} }\mathrm{d}

Jin Hyoun Kang, Jeong Ho Han, Yong-il Shin

We report the experimental realization of a topological Creutz ladder for ultracold fermionic atoms in a resonantly driven 1D optical lattice. The two-leg ladder consists of the two lowest orbital states of the optical lattice and the cross inter-leg links are generated via two-photon resonant coupling between the orbitals by periodic lattice shaking. The ch

Ramandeep Gill, Jonathan Granot, Fabio De Colle, Gerardo Urrutia

The afterglow of GRB$\,$170817A/GW$\,$170817 was very unusual, slowly rising as $F_\nu\propto{}t_{\rm{}obs}^{0.8}\nu^{-0.6}$, peaking at $t_{\rm{obs,pk}}\sim\,150\;$days, and sharply decaying as $\sim{}t_{\rm{}obs}^{-2.2}$. VLBI observations revealed an unresolved radio afterglow image whose flux centroid moved superluminally with $v_{\rm{app}}\approx4c$, cl