total 18312took 0.12s

Semitransparent anisotropic and spin Hall magnetoresistance sensor enabled by spin-orbit toque biasingJul 02 2017We demonstrate an ultrathin and semitransparent anisotropic and spin Hall magnetoresistance sensor based on NiFe/Pt heterostructure. The use of spin-orbit torque effective field for transverse biasing allows to reduce the total thickness of the sensors ... More

Macro-spin Modeling and Experimental Study of Spin-orbit Torque Biased Magnetic SensorsOct 31 2017We reported a systematic study of spin-orbit torque biased magnetic sensors based on NiFe/Pt bilayers through both macro-spin modeling and experiments. The simulation results show that it is possible to achieve a linear sensor with a dynamic range of ... More

Disentangle magnon magnetoresistance from anisotropic and spin Hall magnetoresistance in NiFe/Pt bilayersAug 26 2019Aug 30 2019We conducted a systematic angular dependence study of nonlinear magnetoresistance in NiFe/Pt bilayers at variable temperature and field using the Wheatstone bridge method. We successfully disentangled magnon magnetoresistance from other types of magnetoresistances ... More

Ultrathin All-in-one Spin Hall Magnetic Sensor with Built-in AC Excitation Enabled by Spin CurrentMay 15 2018Magnetoresistance (MR) sensors provide cost-effective solutions for diverse industrial and consumer applications, including emerging fields such as internet-of-things (IoT), artificial intelligence and smart living. Commercially available MR sensors such ... More

Static and Dynamic Magnetic Properties of FeMn/Pt MultilayersMay 26 2017Recently we have demonstrated the presence of spin-orbit toque in FeMn/Pt multilayers which, in combination with the anisotropy field, is able to rotate its magnetization consecutively from 0o to 360o without any external field. Here, we report on an ... More

Scale Invariant Fully Convolutional Network: Detecting Hands EfficientlyJun 11 2019Existing hand detection methods usually follow the pipeline of multiple stages with high computation cost, i.e., feature extraction, region proposal, bounding box regression, and additional layers for rotated region detection. In this paper, we propose ... More

Entropy Rate Estimation for Markov Chains with Large State SpaceFeb 22 2018Sep 24 2018Estimating the entropy based on data is one of the prototypical problems in distribution property testing and estimation. For estimating the Shannon entropy of a distribution on $S$ elements with independent samples, [Paninski2004] showed that the sample ... More

Anomalous Hall magnetoresistance in a ferromagnetJun 08 2018The anomalous Hall effect, observed in conducting ferromagnets with broken time-reversal symmetry, offers the possibility to couple spin and orbital degrees of freedom of electrons in ferromagnets. In addition to charge, the anomalous Hall effect also ... More

Classify Participants in Online CommunitiesMar 09 2012As online communities become increasingly popular, researchers have tried to examine participating activities in online communities as well as how to sustain online communities. However, relatively few studies have tried to understand what kinds of participants ... More

Multiplicative Coevolution Regression Models for Longitudinal Networks and Nodal AttributesDec 07 2017We introduce a simple and extendable coevolution model for the analysis of longitudinal network and nodal attribute data. The model features parameters that describe three phenomena: homophily, contagion and autocorrelation of the network and nodal attribute ... More

Disentangle magnon magnetoresistance from anisotropic and spin Hall magnetoresistance in NiFe/Pt bilayersAug 26 2019We conducted a systematic angular dependence study of nonlinear magnetoresistance in NiFe/Pt bilayers at variable temperature and field using the Wheatstone bridge method. We successfully disentangled magnon magnetoresistance from other types of magnetoresistances ... More

Optimal rates of entropy estimation over Lipschitz ballsNov 06 2017Oct 19 2018We consider the problem of minimax estimation of the entropy of a density over Lipschitz balls. Dropping the usual assumption that the density is bounded away from zero, we obtain the minimax rates $(n\ln n)^{-\frac{s}{s+d}} + n^{-1/2}$ for $0<s\leq 2$ ... More

Magnetic angular position sensor enabled by spin-orbit torqueJun 18 2018We propose a simple scheme for magnetic angular position sensor based on current-induced spin-orbit torque effect. A full range detection of 360o is realized with a pair of Hall crosses made of heavy metal/ferromagnet heterostructures. The current axes ... More

Self-current induced spin-orbit torque in FeMn/Pt multilayersMay 17 2016Extensive efforts have been devoted to the study of spin-orbit torque in ferromagnetic metal/heavy metal bilayers and exploitation of it for magnetization switching using an in-plane current. As the spin-orbit torque is inversely proportional to the thickness ... More

Thickness dependence of spin Hall magnetoresistance in FeMn/Pt bilayersSep 24 2016Oct 12 2016We investigated spin Hall magnetoresistance in FeMn/Pt bilayers, which was found to be one order of magnitude larger than that of heavy metal and insulating ferromagnet or antiferromagnet bilayer systems, and comparable to that of NiFe/Pt bilayers. The ... More

A Theoretical Study of Process Dependence for Critical Statistics in Standard Serial Models and Standard Parallel ModelsMar 19 2018Feb 11 2019Critical parts of the definitions of standard serial and standard parallel modes refer to stochastic independence. Standard serial models are defined by stochastic independence and identical distributions of their processing times. Processing times in ... More

A Theoretical Study of Process Dependence for Standard Two-Process Serial Models and Standard Two-Process Parallel ModelsDec 02 2017In this article we differentiate and characterize the standard two-process serial models and the standard two process parallel models by investigating the behavior of (conditional) distributions of the total completion times and survivals of intercompletion ... More

A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical ModelsMay 11 2016Jun 02 2016The flood of multi-context measurement data from many scientific domains have created an urgent need to reconstruct context-specific variable networks, that can significantly simplify network-driven studies. Computationally, this problem can be formulated ... More

Data Priming Network for Automatic Check-OutApr 10 2019Aug 07 2019Automatic Check-Out (ACO) receives increased interests in recent years. An important component of the ACO system is the visual item counting, which recognizes the categories and counts of the items chosen by the customers. However, the training of such ... More

Spin-Orbit Torque in a Single Ferromagnetic Layer with Large Spin-Orbit CouplingMay 28 2019Spin-orbit torque in heavy metal/ferromagnet heterostructures with broken spatial inversion symmetry provides an efficient mechanism for manipulating magnetization using a charge current. Here, we report the presence of a spin torque in a single ferromagnetic ... More

Data Priming Network for Automatic Check-OutApr 10 2019Aug 01 2019Automatic Check-Out (ACO) receives increased interests in recent years. An important component of the ACO system is the visual item counting, which recognizes the categories and counts of the items chosen by the customers. However, the training of such ... More

Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural NetworksAug 12 2016Aug 15 2016Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals ... More

DeMo Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural NetworksAug 12 2016Oct 04 2016Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals ... More

Deep Motif: Visualizing Genomic Sequence ClassificationsMay 04 2016Jun 02 2016This paper applies a deep convolutional/highway MLP framework to classify genomic sequences on the transcription factor binding site task. To make the model understandable, we propose an optimization driven strategy to extract "motifs", or symbolic patterns ... More

On constructions and properties of $(n,m)$-functions with maximal number of bent componentsMay 25 2019For any positive integers $n=2k$ and $m$ such that $m\geq k$, in this paper we show the maximal number of bent components of any $(n,m)$-functions is equal to $2^{m}-2^{m-k}$, and for those attaining the equality, their algebraic degree is at most $k$. ... More

Data Priming Network for Automatic Check-OutApr 10 2019Automatic Check-Out (ACO) receives increased interests in recent years. An important component of the ACO system is the visual item counting, which recognize the categories and counts of the items chosen by the customers. However, the training of such ... More

Search for High-Mass Resonances Decaying into Leptons of Different Flavor ($eμ$, $eτ$, $μτ$)Sep 01 2008We present a search for high-mass resonances decaying into two leptons of different flavor: $e\mu$, $e\tau$ and $\mu\tau$. These resonances are predicted by several models for Physics Beyond the Standard Model, such as R-parity-violating MSSM. The search ... More

Electrical Oscillation in Pt/VO2 Bilayer StripsFeb 02 2015We report on the observation of stable electrical oscillation in Pt/VO2 bilayer strips, in which the Pt overlayer serves the dual purposes of heating up the VO2 and weakening the electric field in the VO2 layer. Systematic measurements in an ultrahigh ... More

Constructing vectorial bent functions via second-order derivativesMay 25 2019Let $n$ be an even positive integer, and $m<n$ be one of its positive divisors. In this paper, inspired by a nice work of Tang et al. on constructing large classes of bent functions from known bent functions [27, IEEE TIT, 63(10): 6149-6157, 2017], we ... More

Field-like spin orbit torque in ultra-thin polycrystalline FeMn filmsSep 24 2016Field-like spin orbit torque in FeMn/Pt bilayers with ultra-thin polycrystalline FeMn has been characterized through planar Hall effect measurements. A large effective field is obtained for FeMn in the thickness range of 2 to 5 nm. The experimental observations ... More

Unveiling the role of Co-O-Mg bond in magnetic anisotropy of Pt/Co/MgO using atomically controlled deposition and in-situ electrical measurementFeb 25 2017Despite the crucial role of interfacial perpendicular magnetic anisotropy in Co(Fe)/MgO based magnetic tunnel junction, the underlying mechanism is still being debated. Here, we report an anatomical study of oxygen and Mg effect on Pt/Co bilayers through ... More

Expectation of the Largest bet size in Labouchere SystemJul 31 2018Jan 07 2019For Labouchere system with winning probability $p$ at each coup, we prove that the expectation of the largest bet size under any initial list is finite if $p>\frac{1}{2}$, and is infinite if $p\le \frac{1}{2}$, solving the open conjecture in Grimmett ... More

Kramers escape rate in overdamped systems with the power-law distributionFeb 10 2014Feb 11 2014Kramers escape rate in the overdamped systems with the power-law distribution is studied. By using the mean first passage time, we derive the escape rate for the power-law distribution and obtain the Kramers' infinite barrier escape rate in this case. ... More

Escape rate for the power-law distribution in low-to-intermediate dampingFeb 28 2014Mar 03 2014Escape rate in the low-to-intermediate damping connecting the low damping with the intermediate damping is established for the power-law distribution on the basis of flux over population theory. We extend the escape rate in the low damping to the low-to-intermediate ... More

The mean first passage time in an energy-diffusion controlled regime with power-law distributionsOct 27 2013Nov 17 2013Based on the mean first passage time (MFPT) theory, we derive the expression of the MFPT in the energy-diffusion controlled regime with a power-law distribution. We discuss the finite barrier effect (i.e. thermal energy is not small with respect to the ... More

The varieties of semi-conformal vectors of affine vertex operator algebrasSep 17 2017This is a continuation of our work to understand vertex operator algebras using the geometric properties of varieties attached to vertex operator algebras. For a class of vertex operator algebras including affine vertex operator algebras associated to ... More

Achieving while maintaining: A logic of knowing how with intermediate constraintsOct 17 2016In this paper, we propose a ternary knowing how operator to express that the agent knows how to achieve $\phi$ given $\psi$ while maintaining $\chi$ in-between. It generalizes the logic of goal-directed knowing how proposed by Yanjing Wang 2015 'A logic ... More

Intrinsic Quantum Noise in Faraday Rotation Measurements of a Single Electron SpinOct 28 2008Oct 31 2008Faraday rotation is one way to realize quantum non-demolition measurement of electron spin in quantum dots. To describe Faraday rotation, semiclassical models are typically used, based on quantized electron spin states and classical electromagnetic fields. ... More

Adversarial-Playground: A Visualization Suite for Adversarial Sample GenerationJun 06 2017Jun 16 2017With growing interest in adversarial machine learning, it is important for machine learning practitioners and users to understand how their models may be attacked. We propose a web-based visualization tool, Adversarial-Playground, to demonstrate the efficacy ... More

Joint Dimensionality Reduction for Two Feature VectorsFeb 13 2016Oct 31 2016Many machine learning problems, especially multi-modal learning problems, have two sets of distinct features (e.g., image and text features in news story classification, or neuroimaging data and neurocognitive data in cognitive science research). This ... More

Electronic and spin dynamics in the insulating iron pnictide NaFe$_{0.5}$Cu$_{0.5}$AsAug 27 2017NaFe$_{0.5}$Cu$_{0.5}$As represents a rare exception in the metallic iron pnictide family, in which a small insulating gap is opened. Based on first-principles study, we provide a comprehensive theoretical characterization of this insulating compound. ... More

Contagion processes on the static and activity driven coupling networksDec 07 2015The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this ... More

Determination of the thermopower of microscale samples with an AC methodMar 17 2017A modified AC method based on micro-fabricated heater and resistive thermometers has been applied to measure the thermopower of microscale samples. A sinusoidal current with frequency {\omega} is passed to the heater to generate an oscillatory temperature ... More

Compressed Baryonic Matter of AstrophysicsApr 15 2013Jul 22 2013Baryonic matter in the core of a massive and evolved star is compressed significantly to form a supra-nuclear object, and compressed baryonic matter (CBM) is then produced after supernova. The state of cold matter at a few nuclear density is pedagogically ... More

Strange Matter: a state before black holeJan 21 2016Normal baryonic matter inside an evolved massive star can be intensely compressed by gravity after a supernova. General relativity predicts formation of a black hole if the core material is compressed into a singularity, but the real state of such compressed ... More

The varieties of Heisenberg vertex operator algebrasAug 12 2015Nov 14 2016For a vertex operator algebra $V$ with conformal vector $\omega$, we consider a class of vertex operator subalgebras and their conformal vectors. They are called semi-conformal vertex operator subalgebras and semi-conformal vectors of $(V,\omega)$, respectively, ... More

The varieties of Heisenberg vertex operator algebrasAug 12 2015Aug 30 2016For a vertex operator algebra V with conformal vector \omega, we consider a class of vertex operator subalgebras and their conformal vectors. They are called semi- conformal vertex operator subalgebras and semi-conformal vectors of (V,\omega), respectively, ... More

Multichannel Sparse Blind Deconvolution on the SphereMay 26 2018Mar 16 2019Multichannel blind deconvolution is the problem of recovering an unknown signal $f$ and multiple unknown channels $x_i$ from their circular convolution $y_i=x_i \circledast f$ ($i=1,2,\dots,N$). We consider the case where the $x_i$'s are sparse, and convolution ... More

Style Transfer Generative Adversarial Networks: Learning to Play Chess DifferentlyFeb 22 2017May 07 2017The idea of style transfer has largely only been explored in image-based tasks, which we attribute in part to the specific nature of loss functions used for style transfer. We propose a general formulation of style transfer as an extension of generative ... More

Application of RWA leads to false conclusions about the transition probability for the near or exact resonanceNov 19 2015Apr 28 2016Rotating wave approximation (RWA) plays a key rule in quantum optics to solve some Schr\"{o}dinger equation approximately. For example, it is well known that RWA has been used to calculate the transition probability. However, so far no one shows the validity ... More

The anomalous distributions and Soret coefficient in a nonequilibrium colloid systemApr 27 2014Oct 15 2015The density distributions and Soret coefficient in a nonequilibrium colloidal system with nonuniform temperature are studied by the overdamped Langevin equation for Brownian motion in an inhomogeneous strong friction medium. Based on the relation between ... More

Probabilistic Population Projections for Countries with Generalized HIV/AIDS EpidemicsSep 14 2016The United Nations (UN) issued official probabilistic population projections for all countries to 2100 in July 2015. This was done by simulating future levels of total fertility and life expectancy from Bayesian hierarchical models, and combining the ... More

Moduli spaces of conformal structures on Heisenberg vertex algebrasDec 29 2018This paper is a continuation to understand Heisenberg vertex algebras in terms of moduli spaces of their conformal structures. We study the moduli space of the conformal structures on a Heisenberg vertex algebra that have the standard fixed conformal ... More

Detection and localization of continuous gravitational waves with pulsar timing arrays: the role of pulsar termsJun 14 2016Jul 05 2016A pulsar timing array is a Galactic-scale detector of nanohertz gravitational waves (GWs). Its target signals contain two components: the `Earth term' and the `pulsar term' corresponding to GWs incident on the Earth and pulsar respectively. In this work ... More

Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal ImagesJul 26 2019Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual annotation which is often time-consuming and can some time be infeasible. ... More

Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep LearningAug 01 2017Recent studies have shown that attackers can force deep learning models to misclassify so-called "adversarial examples": maliciously generated images formed by making imperceptible modifications to pixel values. With growing interest in deep learning ... More

An efficient and compact quantum switch for quantum circuitsMay 22 2016The engineering of quantum devices has reached the stage where we now have small scale quantum processors containing multiple interacting qubits within them. Simple quantum circuits have been demonstrated and scaling up to larger numbers is underway. ... More

A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical ModelsMay 11 2016Oct 18 2016Identifying context-specific entity networks from aggregated data is an important task, arising often in bioinformatics and neuroimaging. Computationally, this task can be formulated as jointly estimating multiple different, but related, sparse Undirected ... More

Adaptive Estimation of Shannon EntropyFeb 01 2015We consider estimating the Shannon entropy of a discrete distribution $P$ from $n$ i.i.d. samples. Recently, Jiao, Venkat, Han, and Weissman, and Wu and Yang constructed approximation theoretic estimators that achieve the minimax $L_2$ rates in estimating ... More

Thermodynamics of charged accelerating AdS black holes and holographic heat enginesAug 29 2018Feb 19 2019Using a reasonable choice in normalizing the timelike Killing vector, we investigate the thermodynamic properties of charged accelerating Anti-de Sitter (AdS) black holes. We find that the expression of the thermodynamic mass in the first law of thermodynamics ... More

Neural Message Passing for Multi-Label ClassificationApr 17 2019Multi-label classification (MLC) is the task of assigning a set of target labels for a given sample. Modeling the combinatorial label interactions in MLC has been a long-haul challenge. We propose Label Message Passing (LaMP) Neural Networks to efficiently ... More

Memory Matching Networks for Genomic Sequence ClassificationFeb 22 2017When analyzing the genome, researchers have discovered that proteins bind to DNA based on certain patterns of the DNA sequence known as "motifs". However, it is difficult to manually construct motifs due to their complexity. Recently, externally learned ... More

Minimax Rate-Optimal Estimation of Divergences between Discrete DistributionsMay 30 2016Nov 24 2016We refine the general methodology in [1] for the construction and analysis of essentially minimax estimators for a wide class of functionals of finite dimensional parameters, and elaborate on the case of discrete distributions with support size $S$ comparable ... More

Reading molecular messages from the intersections of high-order harmonic spectra at different orientationsMar 03 2008Nov 13 2008We investigate the orientation dependence of high-order harmonic generation (HHG) from H$_2^+$ with different internuclear distances irradiated by intense laser fields both numerically and analytically. The calculated molecular HHG spectra are found to ... More

Feature Squeezing: Detecting Adversarial Examples in Deep Neural NetworksApr 04 2017Dec 05 2017Although deep neural networks (DNNs) have achieved great success in many tasks, they can often be fooled by \emph{adversarial examples} that are generated by adding small but purposeful distortions to natural examples. Previous studies to defend against ... More

Response of initial field to stiffness perturbationMar 18 2014Mar 19 2014Response of initial elastic field to stiffness perturbation and its possible application is investigated. Virtual thermal softening is used to produce the stiffness reduction for demonstration. It is interpreted that the redistribution of the initial ... More

Global small solutions to the compressible 2D magnetohydrodynamic system without magnetic diffusionMar 30 2017This paper establishes the global existence and uniqueness of smooth solutions to the two-dimensional compressible magnetohydrodynamic system when the initial data is close to an equilibrium state. In addition, explicit large-time decay rates for various ... More

A Simple Dual-decoder Model for Generating Response with SentimentMay 16 2019How to generate human like response is one of the most challenging tasks for artificial intelligence. In a real application, after reading the same post different people might write responses with positive or negative sentiment according to their own ... More

Optimal Sample Complexity for Stable Matrix RecoveryFeb 13 2016Tremendous efforts have been made to study the theoretical and algorithmic aspects of sparse recovery and low-rank matrix recovery. This paper fills a theoretical gap in matrix recovery: the optimal sample complexity for stable recovery without constants ... More

A Theoretical Framework for Robustness of (Deep) Classifiers Under Adversarial NoiseDec 01 2016Dec 05 2016Recent literature has pointed out that machine learning classifiers, including deep neural networks (DNN), are vulnerable to adversarial samples that are maliciously created inputs that force a machine learning classifier to produce wrong output labels. ... More

Complementarity via error-free measurement in a two-path interferometerNov 01 2016We study both the wave-like behavior and particle-like behavior in a general Mach-Zehnder interferometer with its asymmetric beam splitter. A error-free measurement in the detector is used to extract the which-path information. The fringe visibility V ... More

Optimal Sample Complexity for Stable Matrix RecoveryDec 05 2017Dec 22 2017Tremendous efforts have been made to study the theoretical and algorithmic aspects of sparse recovery and low-rank matrix recovery. This paper fills a theoretical gap in matrix recovery: the optimal sample complexity for stable recovery without constants ... More

Optimal Sample Complexity for Blind Gain and Phase CalibrationDec 22 2015Blind gain and phase calibration (BGPC) is a structured bilinear inverse problem, which arises in many applications, including inverse rendering in computational relighting (albedo estimation with unknown lighting), blind phase and gain calibration in ... More

Optimal Sample Complexity for Stable Matrix RecoveryFeb 13 2016Dec 22 2017Tremendous efforts have been made to study the theoretical and algorithmic aspects of sparse recovery and low-rank matrix recovery. This paper fills a theoretical gap in matrix recovery: the optimal sample complexity for stable recovery without constants ... More

Massive Pulsars and Ultraluminous X-ray SourcesAug 03 2015The detection of 1.37$\, $s pulsations from NuSTAR J095551+6940.8 implies the existence of an accreting pulsar, which challenges the conventional understanding of ultraluminous X-ray source. This kind of sources are proposed to be massive pulsars in this ... More

Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model StructureOct 30 2017May 23 2018We focus on the problem of estimating the change in the dependency structures of two $p$-dimensional Gaussian Graphical models (GGMs). Previous studies for sparse change estimation in GGMs involve expensive and difficult non-smooth optimization. We propose ... More

A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity GraphsSep 13 2017Sep 21 2017Determining functional brain connectivity is crucial to understanding the brain and neural differences underlying disorders such as autism. Recent studies have used Gaussian graphical models to learn brain connectivity via statistical dependencies across ... More

The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-OptimalNov 23 2017Sep 12 2018We analyze the Kozachenko--Leonenko (KL) nearest neighbor estimator for the differential entropy. We obtain the first uniform upper bound on its performance over H\"older balls on a torus without assuming any conditions on how close the density could ... More

Bias Correction with Jackknife, Bootstrap, and Taylor SeriesSep 18 2017Sep 05 2018We analyze the bias correction methods using jackknife, bootstrap, and Taylor series. We focus on the binomial model, and consider the problem of bias correction for estimating $f(p)$, where $f \in C[0,1]$ is arbitrary. We characterize the supremum norm ... More

Quantum Criticality of the Two-dimensional Bose Gas with the Lifshitz dispersionSep 14 2015Bosonic systems with the synthetic spin-orbit coupling and Zeeman field can be tuned into a quantum Lifshitz point exhibiting the $q^4$-dispersion. They are fundamentally different from the conventional ones with the $q^2$-dispersion, and are also connected ... More

Designing optimal quantum cloning machine for qubit systemApr 29 2010Following the work of Niu and Griffiths, in \emph{Phys.Rev.A 58, 4377(1998)}, we shall investigate the problem, how to design the optimal quantum cloning machines (QCMs) for qubit system, with the help of Bloch-sphere representation. In stead of the quality ... More

Mean Values for a Class of Arithmetic Functions in Short IntervalsJul 24 2018In this paper, we shall establish a rather general asymptotic formula in short intervals for a classe of arithmetic functions and announce two applications about the distribution of divisors of square-full numbers and integers representable as sums of ... More

Modelling Data Dispersion Degree in Automatic Robust Estimation for Multivariate Gaussian Mixture Models with an Application to Noisy Speech ProcessingMay 19 2014The trimming scheme with a prefixed cutoff portion is known as a method of improving the robustness of statistical models such as multivariate Gaussian mixture models (MG- MMs) in small scale tests by alleviating the impacts of outliers. However, when ... More

A Theoretical Framework for Robustness of (Deep) Classifiers Under Adversarial NoiseDec 01 2016Recent literature has pointed out that machine learning classifiers, including deep neural networks (DNN), are vulnerable to adversarial samples that are maliciously created inputs that force a machine learning classifier to produce wrong output labels. ... More

A Dynamic Epistemic Framework for Conformant PlanningJun 24 2016In this paper, we introduce a lightweight dynamic epistemic logical framework for automated planning under initial uncertainty. We reduce plan verification and conformant planning to model checking problems of our logic. We show that the model checking ... More

Identifiability and Stability in Blind Deconvolution under Minimal AssumptionsJul 06 2015Dec 23 2015Blind deconvolution (BD) arises in many applications. Without assumptions on the signal and the filter, BD does not admit a unique solution. In practice, subspace or sparsity assumptions have shown the ability to reduce the search space and yield the ... More

A Unified Framework for Identifiability Analysis in Bilinear Inverse Problems with Applications to Subspace and Sparsity ModelsJan 25 2015Bilinear inverse problems (BIPs), the resolution of two vectors given their image under a bilinear mapping, arise in many applications. Without further constraints, BIPs are usually ill-posed. In practice, properties of natural signals are exploited to ... More

Identifiability in Blind Deconvolution with Subspace or Sparsity ConstraintsMay 13 2015Blind deconvolution (BD), the resolution of a signal and a filter given their convolution, arises in many applications. Without further constraints, BD is ill-posed. In practice, subspace or sparsity constraints have been imposed to reduce the search ... More

Cooperative output regulation of multi-agent network systems with dynamic edgesFeb 08 2016This paper investigates a new class of linear multi-agent network systems, in which nodes are coupled by dynamic edges in the sense that each edge has a dynamic system attached as well. The outputs of the edge dynamic systems form the external inputs ... More

A Novel Interleaving Scheme for Polar CodesMar 02 2016Mar 20 2016It's known that the bit errors of polar codes with successive cancellation (SC) decoding are coupled. We call the coupled information bits the correlated bits. In this paper, concatenation schemes are studied for polar codes (as inner codes) and LDPC ... More

A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical ModelsFeb 09 2017Mar 20 2018Estimating multiple sparse Gaussian Graphical Models (sGGMs) jointly for many related tasks (large $K$) under a high-dimensional (large $p$) situation is an important task. Most previous studies for the joint estimation of multiple sGGMs rely on penalized ... More

Adaptive Estimation of Shannon EntropyFeb 01 2015Jan 01 2019We consider estimating the Shannon entropy of a discrete distribution $P$ from $n$ i.i.d. samples. Recently, Jiao, Venkat, Han, and Weissman, and Wu and Yang constructed approximation theoretic estimators that achieve the minimax $L_2$ rates in estimating ... More

Lower Bounds for Learning Distributions under Communication Constraints via Fisher InformationFeb 07 2019May 31 2019We consider the problem of learning high-dimensional, nonparametric and structured (e.g. Gaussian) distributions in distributed networks, where each node in the network observes an independent sample from the underlying distribution and can use $k$ bits ... More

Minimax Estimation of KL Divergence between Discrete DistributionsMay 30 2016We consider the problem of estimating the KL divergence between two discrete probability measures $P$ and $Q$ from empirical data in a non-asymptotic and possibly large alphabet setting. We construct minimax rate-optimal estimators for $D(P\|Q)$ when ... More

On the Error Performance of Systematic Polar CodesApr 16 2015Systematic polar codes are shown to outperform non-systematic polar codes in terms of the bit-error-rate (BER) performance. However theoretically the mechanism behind the better performance of systematic polar codes is not yet clear. In this paper, we ... More

Learning Distributions from their Samples under Communication ConstraintsFeb 07 2019We consider the problem of learning high-dimensional, nonparametric and structured (e.g. Gaussian) distributions in distributed networks, where each node in the network observes an independent sample from the underlying distribution and can use $k$ bits ... More

The period ratio for standing kink and sausage modes in solar structures with siphon flow. I. magnetized slabsMar 07 2013In the applications of solar magneto-seismology(SMS), employing the ratio of the period of the fundamental mode to twice the one of its first overtone, $P_1/2P_2$, plays an important role. We examine how field-aligned flows affect the dispersion properties, ... More

The Universality of CancerJun 01 2015Cancer has been characterized as a constellation of hundreds of diseases differing in underlying mutations and depending on cellular environments. Carcinogenesis as a stochastic physical process has been studied for over sixty years, but there is no accepted ... More

The Power of Complementary Regularizers: Image Recovery via Transform Learning and Low-Rank ModelingAug 03 2018Recent works on adaptive sparse and on low-rank signal modeling have demonstrated their usefulness in various image / video processing applications. Patch-based methods exploit local patch sparsity, whereas other works apply low-rankness of grouped patches ... More

Synchronized output regulation of nonlinear multi-agent systemsJun 30 2013This paper considers the synchronized output regulation (SOR) problem of nonlinear multi-agent systems with switching graph. The SOR means that all agents regulate their outputs to synchronize on the output of a predefined common exosystem. Each agent ... More