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Computation of Maxwell's equations on manifold using implicit DEC schemeAug 31 2009Dec 29 2009Maxwell's equations can be solved numerically in space manifold and the time by discrete exterior calculus as a kind of lattice gauge theory.Since the stable conditions of this method is very severe restriction, we combine the implicit scheme of time ... More

Hyperuniformity of generalized random organization modelsSep 14 2018Feb 13 2019Studies of random organization models of monodisperse spherical particles have shown that a hyperuniform state is achievable when the system goes through an absorbing phase transition to a critical state. Here we investigate to what extent hyperuniformity ... More

Precise algorithms to compute surface correlation functions of two-phase heterogeneous media and their applicationsJul 31 2018The quantitative characterization of the microstructure of random heterogeneous media in $d$-dimensional Euclidean space $\mathbb{R}^d$ via a variety of $n$-point correlation functions is of great importance, since the respective infinite set determines ... More

The Discrete Stochastic Galerkin Method for Hyperbolic Equations with Non-smooth and Random CoefficientsDec 31 2016We develop a general polynomial chaos (gPC) based stochastic Galerkin (SG) for hyperbolic equations with random and singular coefficients. Due to the singu- lar nature of the solution, the standard gPC-SG methods may suffer from a poor or even non convergence. ... More

Microcausality violation of scalar field on noncommutative spacetime with the time-space noncommutativityMar 07 2006Jul 28 2007Quantum field theories on noncommutative spacetime have many different properties from those on commutative spacetime. In this paper, we study the microcausality of free scalar field on noncommutative spacetime. We expand the scalar field in the form ... More

Geometrically bounding 3-manifold, volume and Betti numberApr 10 2017Apr 10 2018It is well known that an arbitrary closed orientable $3$-manifold can be realized as the unique boundary of a compact orientable $4$-manifold, that is, any closed orientable $3$-manifold is cobordant to zero. In this paper, we consider the geometric cobordism ... More

Simulation of Wave Equation on Manifold using DECSep 28 2009Jan 22 2010The classical numerical methods play important roles in solving wave equation, e.g. finite difference time domain method. However, their computational domain are limited to flat space and the time. This paper deals with the description of discrete exterior ... More

Westervelt Equation Simulation on Manifold using DECJan 13 2010The Westervelt equation is a model for the propagation of finite amplitude ultrasound. The method of discrete exterior calculus can be used to solve this equation numerically. A significant advantage of this method is that it can be used to find numerical ... More

Quantum motion equation and Poincare translation invariance of noncommutative field theoryJan 08 2006Mar 16 2006We study the Moyal commutators and their expectation values between vacuum states and non-vacuum states for noncommutative scalar field theory. For noncommutative $\phi^{\star4}$ scalar field theory, we derive its energy-momentum tensor from translation ... More

Multiple Access Wiretap Channel with Noiseless FeedbackJan 15 2017The physical layer security in the up-link of the wireless communication systems is often modeled as the multiple access wiretap channel (MAC-WT), and recently it has received a lot attention. In this paper, the MAC-WT has been re-visited by considering ... More

Euler numbers of four-dimensional rotating black holes with the Euclidean signatureDec 12 2005Feb 06 2006For a black hole's spacetime manifold in the Euclidean signature, its metric is positive definite and therefore a Riemannian manifold. It can be regarded as a gravitational instanton and a topological characteristic which is the Euler number is associated. ... More

Hawking temperature of Kerr-Newman-AdS black hole from tunnelingAug 03 2009Using the null-geodesic tunneling method of Parikh and Wilczek, we derive the Hawking temperature of a general four-dimensional rotating black hole. In order to eliminate the motion of $\phi$ degree of freedom of a tunneling particle, we have chosen a ... More

Energy-momentum non-conservation on noncommutative spacetime and the existence of infinite spacetime dimensionOct 25 2007From the constructions of the quantum spacetime, a four dimensional quantized spacetime can be embedded in a five dimensional continuous spacetime. Thus to observe from the five dimensional continuous spacetime where the four dimensional quantized spacetime ... More

Two unconditional stable schemes for simulation of heat equation on manifold using DECJan 12 2010To predict the heat diffusion in a given region over time, it is often necessary to find the numerical solution for heat equation. With the techniques of discrete differential calculus, we propose two unconditional stable numerical schemes for simulation ... More

Anticommutators and propagators of Moyal star-products for Dirac field on noncommutative spacetimeJan 15 2006Feb 25 2006We study the Moyal anticommutators and their expectation values between vacuum states and non-vacuum states for Dirac fields on noncommutative spacetime. Then we construct the propagators of Moyal star-products for Dirac fields on noncommutative spacetime. ... More

Multiple-Access Relay Wiretap ChannelMar 31 2014Dec 08 2015In this paper, we investigate the effects of an additional trusted relay node on the secrecy of multiple-access wiretap channel (MAC-WT) by considering the model of multiple-access relay wiretap channel (MARC-WT). More specifically, first, we investigate ... More

Hawking Radiation of Black p-Branes from Gravitational AnomalySep 24 2007Aug 01 2008We investigate the Hawking radiation of black $p$-branes of superstring theories using the method of anomaly cancelation, specially, we use the method of [S. Iso, H. Umetsu and F. Wilczek, {\sl Phys. Rev. Lett.} {\bf 96}, 151302 (2006); {\sl Phys. Rev. ... More

Microcausality of Dirac field on noncommutative spacetimeMar 23 2006May 08 2006We study the microcausality of free Dirac field on noncommutative spacetime. We calculate the vacuum and non-vacuum state expectation values for the Moyal commutator $[\bar{\psi}_{\alpha}(x)\star\psi_{\beta}(x),\bar{\psi}_ {\sigma}(x^{\prime})\star\psi_{\tau}(x^{\prime})]_{\star}$ ... More

Commutators and propagators of Moyal star-products and microcausality for free scalar field on noncommutative spacetimeJan 08 2006Feb 26 2006We study the Moyal commutators and their expectation values between vacuum states and non-vacuum states for free scalar field on noncommutative spacetime. Then from the Moyal commutators, we find that the microcausality is satisfied for the linear operators ... More

Boosted Sparse Non-linear Distance Metric LearningDec 10 2015This paper proposes a boosting-based solution addressing metric learning problems for high-dimensional data. Distance measures have been used as natural measures of (dis)similarity and served as the foundation of various learning methods. The efficiency ... More

Computation of Maxwell's equations on Manifold using DECAug 31 2009Dec 29 2009In this paper, the method of discrete exterior calculus for numerically solving Maxwell's equations in space manifold and the time is discussed, which is a kind of lattice gauge theory. The analysis of its stable condition and error is also accomplished. ... More

Orientable hyperbolic 4-manifolds over the 120-cellJan 26 2018Jun 16 2018Since there is no hyperbolic Dehn filling theorem in higher dimensions, it is difficult to construct concrete hyperbolic manifolds of small volume in dimension at least four. We build up a census of closed hyperbolic 4-manifolds of volume $\frac{34\pi^2}{3}\cdot ... More

Random Scalar Fields and HyperuniformityMay 20 2017Jun 22 2017Disordered many-particle hyperuniform systems are exotic amorphous states of matter that lie between crystals and liquids. Hyperuniform systems have attracted recent attention because they are endowed with novel transport and optical properties. Recently, ... More

The Bekenstein-Hawking Entropy of Higher-Dimensional Rotating Black HolesDec 12 2005May 24 2006A black hole can be regarded as a thermodynamic system described by a grand canonical ensemble. In this paper, we study the Bekenstein-Hawking entropy of higher-dimensional rotating black holes using the Euclidean path-integral method of Gibbons and Hawking. ... More

Simultaneous Translation with Flexible Policy via Restricted Imitation LearningJun 04 2019Simultaneous translation is widely useful but remains one of the most difficult tasks in NLP. Previous work either uses fixed-latency policies, or train a complicated two-staged model using reinforcement learning. We propose a much simpler single model ... More

Uniformly Accurate Machine Learning Based Hydrodynamic Models for Kinetic EquationsJul 09 2019A new framework is introduced for constructing interpretable and truly reliable reduced models for multi-scale problems in situations without scale separation. Hydrodynamic approximation to the kinetic equation is used as an example to illustrate the ... More

Learning to Stop in Structured Prediction for Neural Machine TranslationApr 01 2019Jun 17 2019Beam search optimization resolves many issues in neural machine translation. However, this method lacks principled stopping criteria and does not learn how to stop during training, and the model naturally prefers the longer hypotheses during the testing ... More

TAN: Temporal Affine Network for Real-Time Left Ventricle Anatomical Structure Analysis Based on 2D Ultrasound VideosApr 01 2019With superiorities on low cost, portability, and free of radiation, echocardiogram is a widely used imaging modality for left ventricle (LV) function quantification. However, automatic LV segmentation and motion tracking is still a challenging task. In ... More

Med3D: Transfer Learning for 3D Medical Image AnalysisApr 01 2019Jun 10 2019The performance on deep learning is significantly affected by volume of training data. Models pre-trained from massive dataset such as ImageNet become a powerful weapon for speeding up training convergence and improving accuracy. Similarly, models based ... More

Re-evaluation of neutrino mixing pattern according to latest T2K resultJun 20 2011Jan 05 2012We re-evaluate neutrino mixing patterns according to the latest T2K result for a larger mixing angle $\theta_{13}$, and find that the PMNS mixing matrix has larger deviations from bimaximal (BM) and tribimaximal (TB) mixing patterns than previously expected. ... More

When to Update the sequential patterns of stream data?Mar 27 2002Jan 26 2003In this paper, we first define a difference measure between the old and new sequential patterns of stream data, which is proved to be a distance. Then we propose an experimental method, called TPD (Tradeoff between Performance and Difference), to decide ... More

Schur-Weyl duality for $U_{v,t}(sl_{n})$Jan 23 2017In \cite{fl}, the authors get a new presentation of two-parameter quantum algebra $U_{v,t}(\mathfrak{g})$. Their presentation can cover all Kac-Moody cases. In this paper, we construct a suitable Hopf pairing such that $U_{v,t}(sl_{n})$ can be realized ... More

Distributionally Robust Co-Optimization of Power Dispatch and Do-Not-Exceed LimitsAug 06 2018To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears ... More

Weak solutions for forward--backward SDEs--a martingale problem approachJan 19 2009In this paper, we propose a new notion of Forward--Backward Martingale Problem (FBMP), and study its relationship with the weak solution to the forward--backward stochastic differential equations (FBSDEs). The FBMP extends the idea of the well-known (forward) ... More

Global Closed-form Approximation of Free Boundary for Optimal Investment Stopping ProblemsOct 22 2018In this paper we study a utility maximization problem with both optimal control and optimal stopping in a finite time horizon. The value function can be characterized by a variational equation that involves a free boundary problem of a fully nonlinear ... More

Feedback Coding Schemes for the Broadcast Channel with Mutual Secrecy RequirementApr 10 2018Recently, the physical layer security (PLS) of the communication systems has been shown to be enhanced by using legal receiver's feedback. The present secret key based feedback scheme mainly focuses on producing key from the feedback and using this key ... More

Simultaneous Translation with Flexible Policy via Restricted Imitation LearningJun 04 2019Jun 22 2019Simultaneous translation is widely useful but remains one of the most difficult tasks in NLP. Previous work either uses fixed-latency policies, or train a complicated two-staged model using reinforcement learning. We propose a much simpler single model ... More

Robust Machine Translation with Domain Sensitive Pseudo-Sources: Baidu-OSU WMT19 MT Robustness Shared Task System ReportJun 19 2019This paper describes the machine translation system developed jointly by Baidu Research and Oregon State University for WMT 2019 Machine Translation Robustness Shared Task. Translation of social media is a very challenging problem, since its style is ... More

Set Covering-based Approximation Algorithm for Delay Constrained Relay Node Placement in Wireless Sensor NetworksApr 03 2015The Delay Constrained Relay Node Placement (DCRNP) problem in Wireless Sensor Networks (WSNs) aims to deploy minimum relay nodes such that for each sensor node there is a path connecting this sensor node to the sink without violating delay constraint. ... More

The Extension Dimension of Abelian CategoriesFeb 25 2019Let $\A$ be an abelian category having enough projective objects and enough injective objects. We prove that if $\A$ admits an additive generating object, then the extension dimension and the weak resolution dimension of $\A$ are identical, and they are ... More

Consensus of switched multi-agent systemsJul 12 2014In this paper, we consider the consensus problem of switched multi-agent system composed of continuous-time and discrete-time subsystems. By combining the classical consensus protocols of continuous-time and discrete-time multi-agent systems, we propose ... More

A Linear Strain Energy Function for Hyperelastic Transformation MethodJul 15 2018Sep 27 2018Hyperelastic transformation method provides a promising approach to manipulate elastic waves by utilizing soft materials. However, no existing constitutive model can rigorously achieve the requirement of such method. In this Letter, a linear strain energy ... More

A Connectivity-Aware Approximation Algorithm for Relay Node Placement in Wireless Sensor NetworksJul 08 2015Jul 09 2015In two-tiered Wireless Sensor Networks (WSNs) relay node placement is one of the key factors impacting the network energy consumption and the system overhead. In this paper, a novel connectivity-aware approximation algorithm for relay node placement in ... More

Learning to Stop in Structured Prediction for Neural Machine TranslationApr 01 2019Jun 24 2019Beam search optimization resolves many issues in neural machine translation. However, this method lacks principled stopping criteria and does not learn how to stop during training, and the model naturally prefers the longer hypotheses during the testing ... More

Multi-Reference Training with Pseudo-References for Neural Translation and Text GenerationAug 28 2018Neural text generation, including neural machine translation, image captioning, and summarization, has been quite successful recently. However, during training time, typically only one reference is considered for each example, even though there are often ... More

Geometric Schur Duality of two parameter quantum group of type AJan 22 2017In this paper, we give an geometric description of the Schur-Weyl duality for two-parameter quantum algebras $U_{v, t}(gl_n)$, where $U_{v, t}(gl_n)$ is the deformation of $U_v(I, \cdot)$, the classic Shur-Weyl duality $(U_{r, s}(gl_n), V^{\otimes d}, ... More

Explicit and implicit TVD schemes for conservation laws with Caputo derivativesOct 10 2016Oct 11 2016In this paper, we investigate numerical approximations of the scalar conservation law with the Caputo derivative, which introduces the memory effect. We construct the first order and the second order explicit upwind schemes for such equations, which are ... More

Finite State Markov Wiretap Channel with Delayed FeedbackJun 21 2016Jan 05 2017The finite state Markov channel (FSMC), where the channel transition probability is controlled by a state undergoing a Markov process, is a useful model for the mobile wireless communication channel. In this paper, we investigate the security issue in ... More

Rate Selection for Cooperative HARQ-CC Systems over Time-Correlated Nakagami-m Fading ChannelsMar 10 2015This paper addresses the problem of rate selection for the cooperative hybrid automatic repeat request with chase combination (HARQ-CC) system, where time correlated Nakagami-m fading channels are considered. To deal with this problem, the closed-form ... More

Quantum Cluster SuperalgebrasOct 24 2016Nov 30 2016In this paper, we introduce and study the quantum deformations of the cluster superalgebra. Then we prove the quantum version of the Laurent phenomenon for the super-case.

Geometric RTT realization of $U_v(gl_n)^+$Mar 18 2017In this paper, we give a BLM realization of the positive part of the quantum group of $U_v(gl_n)$ with respect to RTT relations.

Dual control Monte Carlo method for tight bounds of value function under Heston stochastic volatility modelOct 28 2017The aim of this paper is to study the fast computation of the lower and upper bounds on the value function for utility maximization under the Heston stochastic volatility model with general utility functions. It is well known there is a closed form solution ... More

Consensus of Hybrid Multi-agent SystemsDec 10 2015In this paper, we consider the consensus problem of hybrid multi-agent system. First, the hybrid multi-agent system is proposed which is composed of continuous-time and discrete-time dynamic agents. Then, three kinds of consensus protocols are presented ... More

A robust algorithm and convergence analysis for static replications of nonlinear payoffsJun 20 2014In this paper we propose a new robust algorithm to find the optimal static replicating portfolios for general nonlinear payoff functions and give the estimate of the rate of convergence that is absent in the literature. We choose the static replication ... More

PAN: Path Integral Based Convolution for Deep Graph Neural NetworksApr 24 2019Convolution operations designed for graph-structured data usually utilize the graph Laplacian, which can be seen as message passing between the adjacent neighbors through a generic random walk. In this paper, we propose PAN, a new graph convolution framework ... More

Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and TrackingMay 29 2017Jun 13 2018For crowded scenes, the accuracy of object-based computer vision methods declines when the images are low-resolution and objects have severe occlusions. Taking counting methods for example, almost all the recent state-of-the-art counting methods bypass ... More

Relay Broadcast Channel with Confidential MessagesDec 24 2013Dec 08 2015We investigate the effects of an additional relay node on the secrecy of broadcast channels by considering the model of relay broadcast channels with confidential messages. We show that this additional relay node can increase the achievable secrecy rate ... More

Riemann-Hilbert approach for multi-soliton solutions of a fifth-order nonlinear Schrodinger equationOct 30 2018A fifth-order nonlinear Schrodinger equation which describes one-dimensional anisotropic Heisenberg ferromagnetic spin chain is under exploration in this paper. Starting from the spectral analysis of the Lax pair, a Riemann-Hilbert problem is set up. ... More

Joint Transmitter-Receiver Design for the Downlink Multiuser Spatial Multiplexing MIMO SystemNov 03 2008Nov 04 2008This paper proposes a joint transmitter-receiver design to minimize the weighted sum power under the post-processing signal-to-interference-and-noise ratio (post-SINR) constraints for all subchannels. Simulation results demonstrate that the algorithm ... More

Intelligent Search of Correlated Alarms for GSM Networks with Model-based ConstraintsApr 29 2002In order to control the process of data mining and focus on the things of interest to us, many kinds of constraints have been added into the algorithms of data mining. However, discovering the correlated alarms in the alarm database needs deep domain ... More

Few-Example Object Detection with Model CommunicationJun 26 2017Oct 30 2018In this paper, we study object detection using a large pool of unlabeled images and only a few labeled images per category, named "few-example object detection". The key challenge consists in generating trustworthy training samples as many as possible ... More

Long-Term Human Motion Prediction by Modeling Motion Context and Enhancing Motion DynamicMay 07 2018Human motion prediction aims at generating future frames of human motion based on an observed sequence of skeletons. Recent methods employ the latest hidden states of a recurrent neural network (RNN) to encode the historical skeletons, which can only ... More

Asymptotic Outage Analysis of Spatially Correlated Rayleigh MIMO ChannelsApr 15 2019The outage performance of multiple-input multiple-output (MIMO) technique has received intense attention in order to ensure the reliability requirement for mission-critical machine-type communication (cMTC) applications. In this paper, the outage probability ... More

A Novel Brain Decoding Method: a Correlation Network Framework for Revealing Brain ConnectionsDec 01 2017Brain decoding is a hot spot in cognitive science, which focuses on reconstructing perceptual images from brain activities. Analyzing the correlations of collected data from human brain activities and representing activity patterns are two problems in ... More

Haar Transforms for Graph Neural NetworksJul 10 2019Graph Neural Networks (GNNs) have become a topic of intense research recently due to their powerful capability in high-dimensional classification and regression tasks for graph-structured data. However, as GNNs typically define the graph convolution by ... More

Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural NetworksMay 24 2019It remains a puzzle that why deep neural networks (DNNs), with more parameters than samples, often generalize well. An attempt of understanding this puzzle is to discover implicit biases underlying the training process of DNNs, such as the Frequency Principle ... More

Learning to Steer by Mimicking Features from Heterogeneous Auxiliary NetworksNov 07 2018The training of many existing end-to-end steering angle prediction models heavily relies on steering angles as the supervisory signal. Without learning from much richer contexts, these methods are susceptible to the presence of sharp road curves, challenging ... More

Adversarial Network Bottleneck Features for Noise Robust Speaker VerificationJun 11 2017In this paper, we propose a noise robust bottleneck feature representation which is generated by an adversarial network (AN). The AN includes two cascade connected networks, an encoding network (EN) and a discriminative network (DN). Mel-frequency cepstral ... More

Optimal topology of multi-agent systems with two leaders: a zero-sum game perspectiveOct 26 2014It is typical to assume that there is no conflict of interest among leaders. Under such assumption, it is known that, for a multi-agent system with two leaders, if the followers' interaction subgraph is undirected and connected, then followers will converge ... More

DNN Filter Bank Cepstral Coefficients for Spoofing DetectionFeb 13 2017With the development of speech synthesis techniques, automatic speaker verification systems face the serious challenge of spoofing attack. In order to improve the reliability of speaker verification systems, we develop a new filter bank based cepstral ... More

Efficient Network Construction through Structural PlasticityMay 27 2019Deep Neural Networks (DNNs) on hardware is facing excessive computation cost due to the massive number of parameters. A typical training pipeline to mitigate over-parameterization is to pre-define a DNN structure first with redundant learning units (filters ... More

Quark-lepton complementarity revisitedMar 07 2012May 14 2012We reexamine the quark-lepton complementarity (QLC) in nine angle-phase parametrizations with the latest result of a large lepton mixing angle $\vartheta_{13}$ from the T2K, MINOS and Double Chooz experiments. We find that there are still two QLC relations ... More

Ensemble Sequence Level Training for Multimodal MT: OSU-Baidu WMT18 Multimodal Machine Translation System ReportAug 31 2018This paper describes multimodal machine translation systems developed jointly by Oregon State University and Baidu Research for WMT 2018 Shared Task on multimodal translation. In this paper, we introduce a simple approach to incorporate image information ... More

Modeling and Analysis of Non-Orthogonal MBMS Transmission in Heterogeneous NetworksMar 16 2017Broadcasting/multicasting is an efficient mechanism for multimedia communications due to its high spectrum efficiency, which achieves point-to-multipoint transmission on the same radio resources. To satisfy the increasing demands for multimedia broadcast ... More

Transport Properties of Topological Insulators Films and NanowiresMay 28 2013The last several years have witnessed the rapid developments in the study and understanding of topological insulators. In this review, after a brief summary of the history of topological insulators, we focus on the recent progress made in transport experiments ... More

Hyperspectral Image Classification in the Presence of Noisy LabelsSep 12 2018Apr 02 2019Label information plays an important role in supervised hyperspectral image classification problem. However, current classification methods all ignore an important and inevitable problem---labels may be corrupted and collecting clean labels for training ... More

Theory of the Frequency Principle for General Deep Neural NetworksJun 21 2019Jul 02 2019Along with fruitful applications of Deep Neural Networks (DNNs) to realistic problems, recently, some empirical studies of DNNs reported a universal phenomenon of Frequency Principle (F-Principle): a DNN tends to learn a target function from low to high ... More

Quantum cluster algebra structure on the finite dimensional representations of $U_q(\widehat{sl_{2}})$Jun 10 2014In this paper, we give a quantum cluster algebra structure on the deformed Grothendieck ring of $\CC_{n}$, where $\CC_{n}$ is a full subcategory of finite dimensional representations of $U_q(\widehat{sl_{2}})$ defined in section II.

RaFM: Rank-Aware Factorization MachinesMay 18 2019Factorization machines (FM) are a popular model class to learn pairwise interactions by a low-rank approximation. Different from existing FM-based approaches which use a fixed rank for all features, this paper proposes a Rank-Aware FM (RaFM) model which ... More

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture DesignJul 30 2018Currently, the neural network architecture design is mostly guided by the \emph{indirect} metric of computation complexity, i.e., FLOPs. However, the \emph{direct} metric, e.g., speed, also depends on the other factors such as memory access cost and platform ... More

A counterpart of the WKI soliton hierarchy associated with so(3,R)May 05 2014A counterpart of the Wadati-Konno-Ichikawa (WKI) soliton hierarchy, associated with so(3,R), is presented through the zero curvature formulation. Its spectral matrix is defined by the same linear combination of basis vectors as the WKI one, and its Hamiltonian ... More

Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic SegmentationMar 10 2018As the demand for enabling high-level autonomous driving has increased in recent years and visual perception is one of the critical features to enable fully autonomous driving, in this paper, we introduce an efficient approach for simultaneous object ... More

Generating Text Sequence Images for RecognitionJan 21 2019Recently, methods based on deep learning have dominated the field of text recognition. With a large number of training data, most of them can achieve the state-of-the-art performances. However, it is hard to harvest and label sufficient text sequence ... More

Theory of the Frequency Principle for General Deep Neural NetworksJun 21 2019Along with fruitful applications of Deep Neural Networks (DNNs) to realistic problems, recently, some empirical studies of DNNs reported a universal phenomenon of Frequency Principle (F-Principle): a DNN tends to learn a target function from low to high ... More

Defect Solitons in Parity-Time Symmetric Optical Lattices with Nonlocal NonlinearityJul 07 2011Apr 15 2012The existence and stability of defect solitons in parity-time (PT) symmetric optical lattices with nonlocal nonlinearity are reported. It is found that nonlocality can expand the stability region of defect solitons. For positive or zero defects, fundamental ... More

The Algorithms of Updating Sequential PatternsMar 27 2002Because the data being mined in the temporal database will evolve with time, many researchers have focused on the incremental mining of frequent sequences in temporal database. In this paper, we propose an algorithm called IUS, using the frequent and ... More

Kazhdan-Lusztig coefficients for the lowest two-sided cell of type $\tilde{G_{2}}$Oct 28 2013Mar 25 2014This paper studies the Kazhdan-Lusztig coefficients $\mu(u,w)$ of the Kazhdan-Lusztig polynomials $P_{u,w}$ for the lowest cell ${c_{0}}$ of an affine Weyl group of type $\widetilde{G_{2}}$ and gives an estimation $\mu(u,w)\leqslant 3$ for $u,w\in c_{0}$. ... More

Moving Deep Learning into Web Browser: How Far Can We Go?Jan 27 2019Mar 24 2019Recently, several JavaScript-based deep learning frameworks have emerged, making it possible to perform deep learning tasks directly in browsers. However, little is known on what and how well we can do with these frameworks for deep learning in browsers. ... More

Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-Scale BoosterJul 09 2019Accurate lesion detection in computer tomography (CT) slices benefits pathologic organ analysis in the medical diagnosis process. More recently, it has been tackled as an object detection problem using the Convolutional Neural Networks (CNNs). Despite ... More

A type of generalization error induced by initialization in deep neural networksMay 19 2019How different initializations and loss functions affect the learning of a deep neural network (DNN), specifically its generalization error, is an important problem in practice. In this work, focusing on regression problems, we develop a kernel-norm minimization ... More

A Dual Symmetric Gauss-Seidel Alternating Direction Method of Multipliers for Hyperspectral Sparse UnmixingFeb 25 2019Since sparse unmixing has emerged as a promising approach to hyperspectral unmixing, some spatial-contextual information in the hyperspectral images has been exploited to improve the performance of the unmixing recently. The total variation (TV) has been ... More

Finite State Multiple-Access Wiretap Channel with Delayed FeedbackApr 05 2017Feb 18 2018Recently, it has been shown that the time-varying multiple-access channel (MAC) with perfect channel state information (CSI) at the receiver and delayed feedback CSI at the transmitters can be modeled as the finite state MAC (FS-MAC) with delayed state ... More

Experimental Progress on Layered Topological SemimetalsFeb 19 2019We review recent experimental progresses on layered topological materials, mainly focusing on transitional metal dichalcogenides with various lattice types including 1T, Td and 1T' structural phases. Their electronic quantum states are interestingly rich, ... More

Mathematical modeling of hysteresis loops in ferroelectric materialsNov 13 2016In published papers, the Gibbs free energy of ferroelectric materials has usually been quantified by the retention of 6th or 8th order polarization terms. In this paper, a newly analytical model of Gibbs free energy, thereout, a new model of polarization-electric ... More

Modeling of hysteresis loop and its applications in ferroelectric materialsJul 27 2017In order to understand the physical hysteresis loops clearly, we constructed a novel model, which is combined with the electric field, the temperature, and the stress as one synthetically parameter. This model revealed the shape of hysteresis loop was ... More

Pyramid Network with Online Hard Example Mining for Accurate Left Atrium SegmentationDec 14 2018Accurately segmenting left atrium in MR volume can benefit the ablation procedure of atrial fibrillation. Traditional automated solutions often fail in relieving experts from the labor-intensive manual labeling. In this paper, we propose a deep neural ... More

AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical DataJul 12 2019Anomaly detection is facing with emerging challenges in many important industry domains, such as cyber security and online recommendation and advertising. The recent trend in these areas calls for anomaly detection on time-evolving data with high-dimensional ... More

Ultrafast quantum random number generation based on quantum phase fluctuationsSep 03 2011Jul 05 2012A quantum random number generator (QRNG) can generate true randomness by exploiting the fundamental indeterminism of quantum mechanics. Most approaches to QRNG employ single-photon detection technologies and are limited in speed. Here, we propose and ... More

Untwisting and Disintegration of a Solar Filament Associated with Photospheric Flux CancellationDec 18 2018Using the high-resolution observations from New Vacuum Solar Telescope (NVST) jointly with the Solar Dynamics Observatory data, we investigate two successive confined eruptions (Erup1 and Erup2) of a small filament in a decaying active region on 2017 ... More

1.064-um-band up-conversion single-photon detectorMar 31 2017Based on the technique of periodically poled lithium niobate (PPLN) waveguide, up-conversion single-photon detection at 1.064-{\mu}m is demonstrated. We have achieved a system photon detection efficiency (DE) of 32.5% with a very low noise count rate ... More