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Jie Wang

Publications and source records attributed to Jie Wang.

At least 523 records · Page 29Linked to original sources

Classification of tetravalent $2$-transitive non-normal Cayley graphs of finite simple groups

A graph $Γ$ is called $(G, s)$-arc-transitive if $G \le \mathrm{Aut}(Γ)$ is transitive on the set of vertices of $Γ$ and the set of $s$-arcs of $Γ$, where for an integer $s \ge 1$ an $s$-arc of $Γ$ is a sequence of $s+1$ vertices $(v_0,v_1,\ldots,v_s)$ of $Γ$ such that $v_{i-1}$ and $v_i$ are adjacent for $1 \le i \le s$ and $v_{i-1}\ne v_{i+1}$ for $1 \le i \le s-1$. $Γ$ is called 2-transitive if it is $(\mathrm{Aut}(Γ), 2)$-arc-transitive but not $(\mathrm{Aut}(Γ), 3)$-arc-transitive. A Cayley graph $Γ$ of a group $G$ is called normal if $G$ is normal in $\mathrm{Aut}(Γ)$ and non-normal otherwise. It was proved by X. G. Fang, C. H. Li and M. Y. Xu that if $Γ$ is a tetravalent 2-transitive Cayley graph of a finite simple group $G$, then either $Γ$ is normal or $G$ is one of the groups $\mathrm{PSL}_2(11)$, $M_{11}$, $M_{23}$ and $A_{11}$. However, it was unknown whether $Γ$ is normal when $G$ is one of these four groups. In the present paper we answer this question by proving that among these four groups only $M_{11}$ produces connected tetravalent 2-transitive non-normal Cayley graphs. We prove further that there are exactly two such graphs which are non-isomorphic and both determined in the paper. As a consequence, the automorphism group of any connected tetravalent 2-transitive Cayley graph of any finite simple group is determined.

math.CO↗

PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack

The studies on black-box adversarial attacks have become increasingly prevalent due to the intractable acquisition of the structural knowledge of deep neural networks (DNNs). However, the performance of emerging attacks is negatively impacted when fooling DNNs tailored for high-resolution images. One of the explanations is that these methods usually focus on attacking the entire image, regardless of its spatial semantic information, and thereby encounter the notorious curse of dimensionality. To this end, we propose a pixel correlation-based attentional black-box adversarial attack, termed as PICA. Firstly, we take only one of every two neighboring pixels in the salient region as the target by leveraging the attentional mechanism and pixel correlation of images, such that the dimension of the black-box attack reduces. After that, a general multiobjective evolutionary algorithm is employed to traverse the reduced pixels and generate perturbations that are imperceptible by the human vision. Extensive experimental results have verified the effectiveness of the proposed PICA on the ImageNet dataset. More importantly, PICA is computationally more efficient to generate high-resolution adversarial examples compared with the existing black-box attacks.

cs.CV↗

Topological charge engineering in lasing bound states in continuum

Recently, optical bound states in continuum in various passive photonic crystals have been identified and similar structures incorporated with optical gain have been reported to exhibit lasing. However, no explicit control over the type of lasing BIC has been reported. In this work, we utilize all four fundamental BICs related to the lowest energy Gamma-point of a square photonic crystal lattice. We identify the associated topological charges from experimentally obtained dispersions, finite element method simulations, as well as from spherical decomposition method based on the microscopic polarization currents in the photonic crystal plane. By tailoring the periodicity and the hole diameter of the photonic crystal slab, we selectively bring each of the four BIC resonances to a wavelength regime, where fluorescent IR702 molecules overlaid with the photonic crystal provide sufficient gain for the onset of lasing. We experimentally analyze all four observed lasing BICs by imaging their far-field polarization vortices and their associated topological charges. The results correspond excellently with the transmission results as well as the simulation results in the absence of gain. Finally, we experimentally present a case where the lasing signal reveals the coexistence of two BICs with opposite topological charges, resulting in a unique polarization pattern. We believe our results enable tailoring the properties, such as polarization winding and topological charge of BICs, by a priori design and thus pave the way for a more general utilization of their appealing properties.

physics.optics↗

Review of Text Style Transfer Based on Deep Learning

Text style transfer is a hot issue in recent natural language processing,which mainly studies the text to adapt to different specific situations, audiences and purposes by making some changes. The style of the text usually includes many aspects such as morphology, grammar, emotion, complexity, fluency, tense, tone and so on. In the traditional text style transfer model, the text style is generally relied on by experts knowledge and hand-designed rules, but with the application of deep learning in the field of natural language processing, the text style transfer method based on deep learning Started to be heavily researched. In recent years, text style transfer is becoming a hot issue in natural language processing research. This article summarizes the research on the text style transfer model based on deep learning in recent years, and summarizes, analyzes and compares the main research directions and progress. In addition, the article also introduces public data sets and evaluation indicators commonly used for text style transfer. Finally, the existing characteristics of the text style transfer model are summarized, and the future development trend of the text style transfer model based on deep learning is analyzed and forecasted.

cs.CL↗

Exploiting constant trace property in large-scale polynomial optimization

We prove that every semidefinite moment relaxation of a polynomial optimization problem (POP) with a ball constraint can be reformulated as a semidefinite program involving a matrix with constant trace property (CTP). As a result such moment relaxations can be solved efficiently by first-order methods that exploit CTP, e.g., the conditional gradient-based augmented Lagrangian method. We also extend this CTP-exploiting framework to large-scale POPs with different sparsity structures. The efficiency and scalability of our framework are illustrated on second-order moment relaxations for various randomly generated quadratically constrained quadratic programs.

math.OC↗

On Radically Expanding the Landscape of Potential Applications for Automated Proof Methods

In this paper we examine the potential of computer-assisted proof methods to be applied much more broadly than commonly recognized. More specifically, we contend that there are vast opportunities to derive useful mathematical results and properties that are extremely narrow in scope, and of practical relevance only to highly-specialized engineering applications, that are presently overlooked because they have characteristics atypical of those that are conventionally pursued in the areas of pure and applied mathematics. As a concrete example, we demonstrate use of automated methods for certifying polynomial nonnegativity as a part of a dimension-pinning strategy to prove that the inverse of the relative gain array (RGA) of a d-dimensional positive-definite matrix is doubly-stochastic for $d\leq 4$.

cs.LO↗

Baryon acoustic oscillations reconstruction using convolutional neural networks

We propose a new scheme to reconstruct the baryon acoustic oscillations (BAO) signal, which contains key cosmological information, based on deep convolutional neural networks (CNN). Trained with almost no fine-tuning, the network can recover large-scale modes accurately in the test set: the correlation coefficient between the true and reconstructed initial conditions reaches $90\%$ at $k\leq 0.2 h\mathrm{Mpc}^{-1}$, which can lead to significant improvements of the BAO signal-to-noise ratio down to $k\simeq0.4h\mathrm{Mpc}^{-1}$. Since this new scheme is based on the configuration-space density field in sub-boxes, it is local and less affected by survey boundaries than the standard reconstruction method, as our tests confirm. We find that the network trained in one cosmology is able to reconstruct BAO peaks in the others, i.e. recovering information lost to non-linearity independent of cosmology. The accuracy of recovered BAO peak positions is far less than that caused by the difference in the cosmology models for training and testing, suggesting that different models can be distinguished efficiently in our scheme. It is very promising that Our scheme provides a different new way to extract the cosmological information from the ongoing and future large galaxy surveys.

astro-ph.CO↗

Optimal Power Control for DoS Attack over Fading Channel: A Game-Theoretic Approach

In this paper, we investigate remote state estimation against an intelligent denial-of-service (DoS) attack over a vulnerable wireless network whose channel undergoes attenuation and distortion caused by fading. We use the sensor to observe system states and transmit its local state estimates to the remote center. Meanwhile, the attacker injects a jamming signal to destroy the packet accepted by the remote center and causes the performance degradation. Most of the existing works are built on a time-invariant channel state information (CSI) model in which the channel fading is stationary. However, the wireless communication channels are more prone to dynamic changes. To capture this time-variant property in the channel quality of the real-world networks, we study the fading channel network whose channel model is characterized by a generalized finite-state Markov chain. With the goals of two players in infinite-time horizon, we describe the conflicting characteristic between the attacker and the sensor with a general-sum stochastic game. Moreover, the Q-learning techniques are applied to obtain an optimal strategy pair at a Nash equilibrium. Also the monotone structure of the optimal stationary strategy is constructed under a sufficient condition. Besides, when channel gain is known a priori, except for the full Channel State Information (CSI), we also investigate the partial CSI, where Bayesian games are employed. Based on the player's own channel information and the belief on the channel distribution of other players, the energy strategy at a Nash equilibrium is obtained.

eess.SY↗

Extracting Body Text from Academic PDF Documents for Text Mining

Accurate extraction of body text from PDF-formatted academic documents is essential in text-mining applications for deeper semantic understandings. The objective is to extract complete sentences in the body text into a txt file with the original sentence flow and paragraph boundaries. Existing tools for extracting text from PDF documents would often mix body and nonbody texts. We devise and implement a system called PDFBoT to detect multiple-column layouts using a line-sweeping technique, remove nonbody text using computed text features and syntactic tagging in backward traversal, and align the remaining text back to sentences and paragraphs. We show that PDFBoT is highly accurate with average F1 scores of, respectively, 0.99 on extracting sentences, 0.96 on extracting paragraphs, and 0.98 on removing text on tables, figures, and charts over a corpus of PDF documents randomly selected from arXiv.org across multiple academic disciplines.

cs.IR↗

Generating Adequate Distractors for Multiple-Choice Questions

This paper presents a novel approach to automatic generation of adequate distractors for a given question-answer pair (QAP) generated from a given article to form an adequate multiple-choice question (MCQ). Our method is a combination of part-of-speech tagging, named-entity tagging, semantic-role labeling, regular expressions, domain knowledge bases, word embeddings, word edit distance, WordNet, and other algorithms. We use the US SAT (Scholastic Assessment Test) practice reading tests as a dataset to produce QAPs and generate three distractors for each QAP to form an MCQ. We show that, via experiments and evaluations by human judges, each MCQ has at least one adequate distractor and 84\% of MCQs have three adequate distractors.

cs.CL↗

Line Graph Neural Networks for Link Prediction

We consider the graph link prediction task, which is a classic graph analytical problem with many real-world applications. With the advances of deep learning, current link prediction methods commonly compute features from subgraphs centered at two neighboring nodes and use the features to predict the label of the link between these two nodes. In this formalism, a link prediction problem is converted to a graph classification task. In order to extract fixed-size features for classification, graph pooling layers are necessary in the deep learning model, thereby incurring information loss. To overcome this key limitation, we propose to seek a radically different and novel path by making use of the line graphs in graph theory. In particular, each node in a line graph corresponds to a unique edge in the original graph. Therefore, link prediction problems in the original graph can be equivalently solved as a node classification problem in its corresponding line graph, instead of a graph classification task. Experimental results on fourteen datasets from different applications demonstrate that our proposed method consistently outperforms the state-of-the-art methods, while it has fewer parameters and high training efficiency.

cs.LG↗

Gradient estimates for a class of elliptic and parabolic equations on Riemannian manifolds

Let $(N, g)$ be a complete noncompact Riemannian manifold with Ricci curvature bounded from below. In this paper, we study the gradient estimates of positive solutions to a class of nonlinear elliptic equations $$Δu(x)+a(x)u(x)\log u(x)+b(x)u(x)=0$$ on $N$ where $a(x)$ is $C^{2}$-smooth while $b(x)$ is $C^{1}$ and its parabolic counterparts $$(Δ-\frac{\partial}{\partial t})u(x,t)+a(x,t)u(x,t)\log u(x,t) + b(x,t)u(x,t)=0$$ on $N\times[0, \infty)$ where $a(x,t)$ and $b(x,t)$ are $C^{2} $ with respect to $x\in N$ while are $C^{1}$ with respect to the time $t$. In contrast with lots of similar results, here we do not assume the coefficients of equations are constant, so our results can be viewed as extensions to several classical estimates.

math.DG↗

Exploiting term sparsity in Noncommutative Polynomial Optimization

We provide a new hierarchy of semidefinite programming relaxations, called NCTSSOS, to solve large-scale sparse noncommutative polynomial optimization problems. This hierarchy features the exploitation of term sparsity hidden in the input data for eigenvalue and trace optimization problems. NCTSSOS complements the recent work that exploits correlative sparsity for noncommutative optimization problems by Klep, Magron and Povh in arXiv:1909.00569, and is the noncommutative analogue of the TSSOS framework by Wang, Magron and Lasserre in arXiv:1912.08899. We also propose an extension exploiting simultaneously correlative and term sparsity, as done previously in the commutative case arXiv:2005.02828. Under certain conditions, we prove that the optimums of the NCTSSOS hierarchy converge to the optimum of the corresponding dense SDP relaxation. We illustrate the efficiency and scalability of NCTSSOS by solving eigenvalue/trace optimization problems from the literature as well as randomly generated examples involving up to several thousands of variables.

math.OC↗

When HLS Meets FPGA HBM: Benchmarking and Bandwidth Optimization

With the recent release of High Bandwidth Memory (HBM) based FPGA boards, developers can now exploit unprecedented external memory bandwidth. This allows more memory-bounded applications to benefit from FPGA acceleration. However, we found that it is not easy to fully utilize the available bandwidth when developing some applications with high-level synthesis (HLS) tools. This is due to the limitation of existing HLS tools when accessing HBM board's large number of independent external memory channels. In this paper, we measure the performance of three recent representative HBM FPGA boards (Intel's Stratix 10 MX and Xilinx's Alveo U50/U280 boards) with microbenchmarks and analyze the HLS overhead. Next, we propose HLS-based optimization techniques to improve the effective bandwidth when a PE accesses multiple HBM channels or multiple PEs access an HBM channel. Our experiment demonstrates that the effective bandwidth improves by 2.4X-3.8X. We also provide a list of insights for future improvement of the HBM FPGA HLS design flow.

cs.AR↗

DcardNet: Diabetic Retinopathy Classification at Multiple Levels Based on Structural and Angiographic Optical Coherence Tomography

Objective: Optical coherence tomography (OCT) and its angiography (OCTA) have several advantages for the early detection and diagnosis of diabetic retinopathy (DR). However, automated, complete DR classification frameworks based on both OCT and OCTA data have not been proposed. In this study, a convolutional neural network (CNN) based method is proposed to fulfill a DR classification framework using en face OCT and OCTA. Methods: A densely and continuously connected neural network with adaptive rate dropout (DcardNet) is designed for the DR classification. In addition, adaptive label smoothing was proposed and used to suppress overfitting. Three separate classification levels are generated for each case based on the International Clinical Diabetic Retinopathy scale. At the highest level the network classifies scans as referable or non-referable for DR. The second level classifies the eye as non-DR, non-proliferative DR (NPDR), or proliferative DR (PDR). The last level classifies the case as no DR, mild and moderate NPDR, severe NPDR, and PDR. Results: We used 10-fold cross-validation with 10% of the data to assess the networks performance. The overall classification accuracies of the three levels were 95.7%, 85.0%, and 71.0% respectively. Conclusion/Significance: A reliable, sensitive and specific automated classification framework for referral to an ophthalmologist can be a key technology for reducing vision loss related to DR.

eess.IV↗

Universal structure of dark matter haloes over a mass range of 20 orders of magnitude

Cosmological models in which dark matter consists of cold elementary particles predict that the dark halo population should extend to masses many orders of magnitude below those at which galaxies can form. Here we report a cosmological simulation of the formation of present-day haloes over the full range of observed halo masses (20 orders of magnitude) when dark matter is assumed to be in the form of weakly interacting massive particles of mass approximately 100 gigaelectronvolts. The simulation has a full dynamic range of 30 orders of magnitude in mass and resolves the internal structure of hundreds of Earth-mass haloes in as much detail as it does for hundreds of rich galaxy clusters. We find that halo density profiles are universal over the entire mass range and are well described by simple two-parameter fitting formulae. Halo mass and concentration are tightly related in a way that depends on cosmology and on the nature of the dark matter. For a fixed mass, the concentration is independent of the local environment for haloes less massive than those of typical galaxies. Haloes over the mass range of 10^3 to 10^11 solar masses contribute about equally (per logarithmic interval) to the luminosity produced by dark matter annihilation, which we find to be smaller than all previous estimates by factors ranging up to one thousand.

astro-ph.CO↗

The conformity of HI galaxies in ALFALFA-SDSS sample

The conformity effect, indicating the evolution of a galaxy is related to its surrounding neighbour galaxies as far as a few Mpc, is an interesting phenomenon in the modeling of galaxy and evolution. Here we study the conformity effect of HI galaxies in a matched galaxy sample between SDSS DR7 and ALFALFA surveys. By checking the probability difference for the detected HI galaxies as a function of distance around a normal or an HI galaxy, we find that this effect is significant out to 5 Mpc. It also shows a dependence on the stellar mass of galaxies, with the strength the strongest in the stellar mass range of 10^10~10^10.5. However, when the sample is confined to central galaxies in groups with virial radii smaller than 1 Mpc, the 1-halo conformity signal is still evident, while the 2-halo conformity signal is reduced to a very weak amplitude. Our results confirm the previous study in the optical band that the 2-halo term is possibly caused by the bias effect in the sample selection. Furthermore, we confirm the existence of the 1-halo conformity discovered in the optical and radio band in previous lectures. Our results provide another viewpoint of the conformity effect and hope to shed the light on the co-evolution of the galaxies and their neighbours in the current galaxy formation models.

astro-ph.GA↗

Creating topological polar structure in a nonpolar matter

Nontrivial topological structures offer rich playground in condensed matter physics including fluid dynamics, superconductivity, and ferromagnetism, and they promise alternative device configurations for post-Moore spintronics and electronics. Indeed, magnetic skyrmions are actively pursued for high-density data storage, while polar vortices with exotic negative capacitance may enable ultralow power consumption in microelectronics. Following extensive investigations on a variety of magnetic textures including vortices, domain walls and skyrmions in the past decades, studies on polar topologies have taken off in recent years, resulting in discoveries of closure domains, vortices, and skyrmions in ferroelectric materials. Nevertheless, the atomic-scale creation of topological polar structures is largely confined in a single ferroelectric system, PbTiO3 (PTO) with large polarization, casting doubt on the generality of polar topologies and limiting their potential applications. In this work, we successfully create previously unrealized atomic-scale polar antivortices in the nominally nonpolar SrTiO3 (STO), expanding the reaches of topological structures and completing an important missing link in polar topologies. The work shed considerable new insight into the formation of topological polar structures, and offers guidance in searching for new polar textures.

cond-mat.mtrl-sci↗