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LSTM with Working MemoryMay 06 2016May 13 2016LSTM is arguably the most successful RNN architecture for many tasks that involve sequential information. In the past few years there have been several proposed improvements to LSTM. We propose an improvement to LSTM which allows communication between ... More

Multi-Scale Structure-Aware Network for Human Pose EstimationMar 27 2018Sep 16 2018We develop a robust multi-scale structure-aware neural network for human pose estimation. This method improves the recent deep conv-deconv hourglass models with four key improvements: (1) multi-scale supervision to strengthen contextual feature learning ... More

Interpretation and Generalization of Score MatchingMay 09 2012Score matching is a recently developed parameter learning method that is particularly effective to complicated high dimensional density models with intractable partition functions. In this paper, we study two issues that have not been completely resolved ... More

Exposing DeepFake Videos By Detecting Face Warping ArtifactsNov 01 2018May 22 2019In this work, we describe a new deep learning based method that can effectively distinguish AI-generated fake videos (referred to as {\em DeepFake} videos hereafter) from real videos. Our method is based on the observations that current DeepFake algorithm ... More

A Univariate Bound of Area Under ROCApr 16 2018May 25 2018Area under ROC (AUC) is an important metric for binary classification and bipartite ranking problems. However, it is difficult to directly optimizing AUC as a learning objective, so most existing algorithms are based on optimizing a surrogate loss to ... More

LSTM with Working MemoryMay 06 2016Mar 30 2017Previous RNN architectures have largely been superseded by LSTM, or "Long Short-Term Memory". Since its introduction, there have been many variations on this simple design. However, it is still widely used and we are not aware of a gated-RNN architecture ... More

Exposing DeepFake Videos By Detecting Face Warping ArtifactsNov 01 2018Mar 29 2019In this work, we describe a new deep learning based method that can effectively distinguish AI-generated fake videos (referred to as {\em DeepFake} videos hereafter) from real videos. Our method is based on the observations that current DeepFake algorithm ... More

De-identification without losing facesFeb 12 2019Training of deep learning models for computer vision requires large image or video datasets from real world. Often, in collecting such datasets, we need to protect the privacy of the people captured in the images or videos, while still preserve the useful ... More

Exposing DeepFake Videos By Detecting Face Warping ArtifactsNov 01 2018In this work, we describe a new deep learning based method that can effectively distinguish AI-generated fake videos (referred to as DeepFake videos hereafter) from real videos. Our method is based on the observations that current DeepFake algorithm can ... More

Strong contraction mapping and topological non-convex optimizationJul 08 2018Mar 22 2019The strong contraction mapping, a self-mapping that the range is always a subset of the domain, admits a unique fixed-point which can be pinned down by the iteration of the mapping. We introduce a topological non-convex optimization method as an application ... More

Discussion on the origin of magic numbers in clustersNov 01 2014The distribution of the sizes of clusters is not continuous, but rather has local maxima. The numbers of atoms of those maxima distribution is called magic numbers. Two methods of determining magic numbers are firstly introduced, followed by three different ... More

Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity RecognitionJul 03 2018We present a bootstrapping framework to simultaneously improve multi-person tracking and activity recognition at individual, interaction and social group activity levels. The inference consists of identifying trajectories of all pedestrian actors, individual ... More

Word and Document Embeddings based on Neural Network ApproachesNov 18 2016Data representation is a fundamental task in machine learning. The representation of data affects the performance of the whole machine learning system. In a long history, the representation of data is done by feature engineering, and researchers aim at ... More

Contrast Enhancement Estimation for Digital Image ForensicsJun 13 2017Inconsistency in contrast enhancement can be used to expose image forgeries. In this work, we describe a new method to estimate contrast enhancement from a single image. Our method takes advantage of the nature of contrast enhancement as a mapping between ... More

In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye BlinkingJun 07 2018Jun 11 2018The new developments in deep generative networks have significantly improve the quality and efficiency in generating realistically-looking fake face videos. In this work, we describe a new method to expose fake face videos generated with neural networks. ... More

Exposing Deep Fakes Using Inconsistent Head PosesNov 01 2018Nov 13 2018In this paper, we propose a new method to expose AI-generated fake face images or videos (commonly known as the Deep Fakes). Our method is based on the observations that Deep Fakes are created by splicing synthesized face region into the original image, ... More

Simple and accurate finite difference methods for the d-dimensional tempered fractional Laplacian and their applicationsAug 08 2018In this paper, we propose new and accurate finite difference methods to discretize the d-dimensional (d >=1) tempered fractional Laplacian and apply them to study the tempered effects on the solution of the fractional problems. Our finite difference methods ... More

Robust Adversarial Perturbation on Deep Proposal-based ModelsSep 16 2018Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms. In this paper, we describe a robust adversarial perturbation (R-AP) method to attack deep proposal-based object detectors and instance segmentation ... More

Improving Image Restoration with Soft-RoundingAug 20 2015Several important classes of images such as text, barcode and pattern images have the property that pixels can only take a distinct subset of values. This knowledge can benefit the restoration of such images, but it has not been widely considered in current ... More

Evolvement Constrained Adversarial Learning for Video Style TransferNov 06 2018Video style transfer is a useful component for applications such as augmented reality, non-photorealistic rendering, and interactive games. Many existing methods use optical flow to preserve the temporal smoothness of the synthesized video. However, the ... More

Multi-label Learning with Missing Labels using Mixed Dependency GraphsMar 31 2018This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels. The key point to handle ... More

Exposing GAN-synthesized Faces Using Landmark LocationsMar 30 2019Generative adversary networks (GANs) have recently led to highly realistic image synthesis results. In this work, we describe a new method to expose GAN-synthesized images using the locations of the facial landmark points. Our method is based on the observations ... More

Learning Non-Uniform Hypergraph for Multi-Object TrackingDec 10 2018The majority of Multi-Object Tracking (MOT) algorithms based on the tracking-by-detection scheme do not use higher order dependencies among objects or tracklets, which makes them less effective in handling complex scenarios. In this work, we present a ... More

Learning with Average Top-k LossMay 24 2017Dec 20 2017In this work, we introduce the {\em average top-$k$} (\atk) loss as a new aggregate loss for supervised learning, which is the average over the $k$ largest individual losses over a training dataset. We show that the \atk loss is a natural generalization ... More

STS Classification with Dual-stream CNNMay 20 2018The structured time series (STS) classification problem requires the modeling of interweaved spatiotemporal dependency. most previous STS classification methods model the spatial and temporal dependencies independently. Due to the complexity of the STS ... More

Hiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial PerturbationsJun 21 2019Recent years have seen fast development in synthesizing realistic human faces using AI technologies. Such fake faces can be weaponized to cause negative personal and social impact. In this work, we develop technologies to defend individuals from becoming ... More

Computing the ground and first excited states of the fractional Schrodinger equation in an infinite potential wellApr 30 2014In this paper, we numerically study the ground and first excited states of the fractional Schrodinger equation in an infinite potential well. Due to the non-locality of the fractional Laplacian, it is challenging to find the eigenvalues and eigenfunctions ... More

Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background PatchesSep 16 2018Nov 17 2018Recent works succeeded to generate adversarial perturbations on the entire image or the object of interests to corrupt CNN based object detectors. In this paper, we focus on exploring the vulnerability of the Single Shot Module (SSM) commonly used in ... More

Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background PatchesSep 16 2018Jul 02 2019Recent works succeeded to generate adversarial perturbations on the entire image or the object of interests to corrupt CNN based object detectors. In this paper, we focus on exploring the vulnerability of the Single Shot Module (SSM) commonly used in ... More

Multi-Scale Supervised Network for Human Pose EstimationAug 05 2018Human pose estimation is an important topic in computer vision with many applications including gesture and activity recognition. However, pose estimation from image is challenging due to appearance variations, occlusions, clutter background, and complex ... More

Finite difference methods for two and three dimensional fractional Laplacian with applications to solve the fractional reaction-diffusion equationsApr 08 2018In this paper, we propose an accurate finite difference method to discretize the two and three dimensional fractional Laplacian $(-\Delta)^{\alpha/2}$ in the hypersingular integral form and apply it to solve the fractional reaction-diffusion equations. ... More

Thompson Sampling for Combinatorial Semi-BanditsMar 13 2018Jun 21 2018We study the application of the Thompson sampling (TS) methodology to the stochastic combinatorial multi-armed bandit (CMAB) framework. We analyze the standard TS algorithm for the general CMAB, and obtain the first distribution-dependent regret bound ... More

Finite size effects for spiking neural networks with spatially dependent couplingMay 09 2018Nov 30 2018We study finite-size fluctuations in a network of spiking deterministic neurons coupled with non-uniform synaptic coupling. We generalize a previously developed theory of finite size effects for uniform globally coupled neurons. In the uniform case, mean ... More

Few-Shot Learning-Based Human Activity RecognitionMar 25 2019Few-shot learning is a technique to learn a model with a very small amount of labeled training data by transferring knowledge from relevant tasks. In this paper, we propose a few-shot learning method for wearable sensor based human activity recognition, ... More

A Note on Graph Characteristics and Hadwiger's ConjectureMar 16 2012Nov 27 2012This is a note on three graph parameters motivated by the Euler-Poincare characteristic for simplicial complex. We show those three graph parameters of a given connected graph $G$ is greater than or equal to that of the complete graph with $\max(h(G),\chi(G))$ ... More

Phase synchronization of pulse-coupled excitable clocksApr 28 2016Consider a distributed network on a simple graph $G=(V,E)$ where each node has a phase oscillator revolving on $S^{1}=\mathbb{R}/\mathbb{Z}$ with natural period of 1 second. Pulse-coupling is a class of distributed time evolution rule for such networked ... More

Geometric Hypergraph Learning for Visual TrackingMar 18 2016Graph based representation is widely used in visual tracking field by finding correct correspondences between target parts in consecutive frames. However, most graph based trackers consider pairwise geometric relations between local parts. They do not ... More

Object-driven Text-to-Image Synthesis via Adversarial TrainingFeb 27 2019In this paper, we propose Object-driven Attentive Generative Adversarial Newtorks (Obj-GANs) that allow object-centered text-to-image synthesis for complex scenes. Following the two-step (layout-image) generation process, a novel object-driven attentive ... 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

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

Robust Localized Multi-view Subspace ClusteringMay 22 2017In multi-view clustering, different views may have different confidence levels when learning a consensus representation. Existing methods usually address this by assigning distinctive weights to different views. However, due to noisy nature of real-world ... More

Phase transition in firefly cellular automata on finite treesOct 04 2016We study a one-parameter family of discrete dynamical systems called the $\kappa$-color firefly cellular automata, proposed by the author in [13] as discrete models for finite-state pulse-coupled inhibitory oscillators. At each discrete time $t$, each ... More

Tagging like Humans: Diverse and Distinct Image AnnotationMar 31 2018In this work we propose a new automatic image annotation model, dubbed {\bf diverse and distinct image annotation} (D2IA). The generative model D2IA is inspired by the ensemble of human annotations, which create semantically relevant, yet distinct and ... 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

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

Chromatic number, induced cycles, and non-separating cyclesNov 03 2012Oct 05 2016We show that connected graphs with large chromatic number must contain a large number of induced cycles, and that 3-connected graphs with large clique minor contains many induced non-separating cycles, which are known to generate the cycle space of any ... More

Knowledge-Based Sequential Decision-Making Under UncertaintyMay 16 2019Deep reinforcement learning (DRL) algorithms have achieved great success on sequential decision-making problems, yet is criticized for the lack of data-efficiency and explainability. Especially, explainability of subtasks is critical in hierarchical decision-making ... More

Synchronization of finite-state pulse-coupled oscillatorsJul 04 2014Mar 30 2015We propose a novel generalized cellular automaton(GCA) model for discrete-time pulse-coupled oscillators and study the emergence of synchrony. Given a finite simple graph and an integer $n\ge 3$, each vertex is an identical oscillator of period $n$ with ... More

Deep learning tutorial for denoisingOct 27 2018We herein introduce deep learning to seismic noise attenuation. Compared with traditional seismic noise attenuation algorithms that depend on signal models and their corresponding prior assumptions, a deep neural network is trained based on a large training ... More

Universal generation of the cylinder homomorphism of cubic hypersurfacesOct 29 2018Dec 16 2018In this article, we prove that the Chow group of algebraic cycles of a smooth cubic hypersurface $X$ over an arbitrary field $k$ is generated, via the natural cylinder homomorphism, by the algebraic cycles of its Fano variety of lines $F(X)$, under an ... More

Precise high moment asymptotics for parabolic Anderson model with log-correlated Gaussian fieldSep 03 2019Sep 04 2019In this paper, we consider the continuous parabolic Anderson model (PAM) driven by a time-independent log-correlated Gaussian field (LGF). We obtain an asymptotic result of $$\mathbb{E}\exp\Bigg\{\frac{1}{2}\sum\limits_{ j,k=1}^N\int_0^t\int_0^t\gamma(B_j(s)-B_k(r))drds\Bigg\}\qquad(N\rightarrow ... More

Direct numerical simulation of statistically stationary and homogeneous shear turbulence and its relation to other shear flowsJan 07 2016Mar 02 2016Statistically stationary and homogeneous shear turbulence (SS-HST) is investigated by means of a new direct numerical simulation code, spectral in the two horizontal directions and compact-finite-differences in the direction of the shear. No remeshing ... More

Permissionless Blockchains and Secure LoggingMar 10 2019The blockchain technology enables mutually untrusting participants to reach consensus on the state of a distributed and decentralized ledger (called a blockchain) in a permissionless setting. The consensus protocol of the blockchain imposes a unified ... More

Attention-driven Tree-structured Convolutional LSTM for High Dimensional Data UnderstandingJan 29 2019Modeling the sequential information of image sequences has been a vital step of various vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its superb performance in such spatiotemporal problems. Nevertheless, the hierarchical ... More

UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and TrackingNov 13 2015Sep 04 2016In recent years, numerous effective multi-object tracking (MOT) methods are developed because of the wide range of applications. Existing performance evaluations of MOT methods usually separate the object tracking step from the object detection step by ... More

Remarks on Automorphism and Cohomology of Cyclic CoveringsMay 18 2017We show that the automorphism group of a smooth cyclic covering acts on its cohomology faithfully with a few well known exceptions. Firstly, we prove the faithfulness of the action in characteristic zero. The main ingredients of the proof are equivariant ... More

Tunneling magnetoresistance in diluted magnetic semiconductor tunnel junctionsJan 15 2001Using the spin-polarized tunneling model and taking into account the basic physics of ferromagnetic semiconductors, we study the temperature dependence of the tunneling magnetoresistance (TMR) in the diluted magnetic semiconductor (DMS) trilayer heterostructure ... More

The largest eigenvalue distribution of the Laguerre unitary ensembleNov 03 2015We study the probability that all eigenvalues of the Laguerre unitary ensemble of n by n matrices are between 0 and t, i.e., the largest eigenvalue distribution. Associated with this probability, in the ladder operator approach for orthogonal polynomials, ... More

The phase structure of asymmetric ballistic annihilationNov 20 2018Mar 24 2019In ballistic annihilation, particles are placed throughout the real line with independent spacings and each is assigned a velocity. The particles then move at their assigned velocity and annihilate upon colliding. We develop a framework based on a mass ... More

Learning color space adaptation from synthetic to real images of cirrus cloudsOct 24 2018Training on synthetic data is becoming popular in vision due to the convenient acquisition of accurate pixel-level labels. But the domain gap between synthetic and real images significantly degrades the performance of the trained model. We propose a color ... More

Network-Connected UAV: 3D System Modeling and Coverage Performance AnalysisJan 19 2019With growing popularity, unmanned aerial vehicles (UAVs) are pivotally extending conventional terrestrial Internet of Things (IoT) into the sky. To enable high-performance two-way communications of UAVs with their ground pilots/users, cellular network-connected ... More

Median Binary-Connect Method and a Binary Convolutional Neural Nework for Word RecognitionNov 07 2018We propose and study a new projection formula for training binary weight convolutional neural networks. The projection formula measures the error in approximating a full precision (32 bit) vector by a 1-bit vector in the l_1 norm instead of the standard ... More

Evaluating Complex Task through Crowdsourcing: Multiple Views ApproachMar 30 2017With the popularity of massive open online courses, grading through crowdsourcing has become a prevalent approach towards large scale classes. However, for getting grades for complex tasks, which require specific skills and efforts for grading, crowdsourcing ... More

Blocking Probability and Spatial Throughput Characterization for Cellular-Enabled UAV Network with Directional AntennaOct 28 2017The past few years have witnessed a tremendous increase on the use of unmanned aerial vehicles (UAVs) in civilian applications, which call for high-performance communication between UAVs and their ground clients, especially when they are densely deployed. ... More

Large deviations and one-sided scaling limit of randomized multicolor box-ball systemAug 24 2018Sep 02 2019The basic $\kappa$-color box-ball (BBS) system is an integrable cellular automaton on one dimensional lattice whose local states take $\{0,1,\cdots,\kappa \}$ with $0$ regarded as an empty box. The time evolution is defined by a combinatorial rule of ... More

A Channel-Pruned and Weight-Binarized Convolutional Neural Network for Keyword SpottingSep 12 2019We study channel number reduction in combination with weight binarization (1-bit weight precision) to trim a convolutional neural network for a keyword spotting (classification) task. We adopt a group-wise splitting method based on the group Lasso penalty ... More

Road Segmentation Using CNN with GRUApr 14 2018This paper presents an accurate and fast algorithm for road segmentation using convolutional neural network (CNN) and gated recurrent units (GRU). For autonomous vehicles, road segmentation is a fundamental task that can provide the drivable area for ... More

A High Fraction of Double-peaked Narrow Emission Lines in Powerful Active Galactic NucleiJun 21 2016Aug 09 2016One percent of redshift z~0.1 Active Galactic Nuclei (AGNs) show velocity splitting of a few hundred km/s in the narrow emission lines in spatially integrated spectra. Such line profiles have been found to arise from the bulk motion of ionized gas clouds ... More

How to Generate a Good Word Embedding?Jul 20 2015We analyze three critical components of word embedding training: the model, the corpus, and the training parameters. We systematize existing neural-network-based word embedding algorithms and compare them using the same corpus. We evaluate each word embedding ... More

Further results on differentially 4-uniform permutations over $\F_{2^{2m}}$Feb 13 2015In this paper, we present several new constructions of differentially 4-uniform permutations over $\F_{2^{2m}}$ by modifying the values of the inverse function on some subsets of $\F_{2^{2m}}$. The resulted differentially 4-uniform permutations have high ... More

Constructing Locally Dense Point Clouds Using OpenSfM and ORB-SLAM2Apr 23 2018This paper aims at finding a method to register two different point clouds constructed by ORB-SLAM2 and OpenSfM. To do this, we post some tags with unique textures in the scene and take videos and photos of that area. Then we take short videos of only ... More

Optimal Stochastic Package Delivery Planning with Deadline: A Cardinality Minimization in RoutingFeb 28 2018Vehicle Routing Problem with Private fleet and common Carrier (VRPPC) has been proposed to help a supplier manage package delivery services from a single depot to multiple customers. Most of the existing VRPPC works consider deterministic parameters which ... More

StrongChain: Transparent and Collaborative Proof-of-Work ConsensusMay 23 2019Bitcoin is the most successful cryptocurrency so far. This is mainly due to its novel consensus algorithm, which is based on proof-of-work combined with a cryptographically-protected data structure and a rewarding scheme that incentivizes nodes to participate. ... More

The coherent structure of the energy cascade in shear turbulenceApr 04 2019Apr 25 2019The cascade of energy in turbulent flows, i.e., the transfer of kinetic energy from large to small flow motions (forward cascade) or vice versa (backward cascade), is the cornerstone of most theories and models of turbulence since the 1940s. Yet, understanding ... More

A brief introduction to giant magnetoresistanceDec 21 2014Giant magnetoresistance (GMR) is a quantum mechanical magnetoresistance effect observed in thin film structures composed of alternating ferromagnetic and nonmagnetic layers. The effect manifests itself as a significant decrease (typically 10-80%) in electrical ... More

On high order accurate schemes for space fractional diffusion equations with variable coefficientsAug 29 2016Sep 29 2016We study high order schemes for spatial fractional differential equations with variable coefficients. Approximations of fractional derivatives basing on the weighted and shifted Gr\"unwald-Letnikov formulas and weighted and shifted Lubich formulas are ... More

The phase structure of asymmetric ballistic annihilationNov 20 2018Feb 03 2019In ballistic annihilation, particles are placed throughout the real line with independent spacings and each is assigned a velocity. The particles then move at their assigned velocity and annihilate upon colliding. We develop a framework based on a mass ... More

TTR-Based Rewards for Reinforcement Learning with Implicit Model PriorsMar 23 2019Model-free reinforcement learning (RL) provides an attractive approach for learning control policies directly in high dimensional state spaces. However, many goal-oriented tasks involving sparse rewards remain difficult to solve with state-of-the-art ... More

Remarks on Automorphism and Cohomology of Cyclic CoveringsMay 18 2017Aug 20 2019For a smooth finite cyclic covering over a projective space of dimension great than one, we show that its automorphism group faithfully acts on its cohomology except for a few cases. In characteristic zero, we study the equivariant deformation theory ... More

Harnack and Shift Harnack Inequalities for Degenerate (Functional) SPDEs with Singular DriftsApr 06 2019The existence and uniqueness of the mild solutions for a class of degenerate functional SPDEs are obtained, where the drift is assumed to be H\"{o}lder-Dini continuous. Moreover, the non-explosion of the solution is proved under some reasonable conditions. ... More

Ferromagnetism in diluted magnetic semiconductor quantum dot arrays embedded in semiconductorsOct 29 2002We present an Anderson-type model Hamiltonian with exchange coupling between the localized spins and the confined holes in the quantum dots to study the ferromagnetism in diluted magnetic semiconductor (DMS) quantum dot arrays embedded in semiconductors. ... More

Gradient Descent Maximizes the Margin of Homogeneous Neural NetworksJun 13 2019Recent works on implicit regularization have shown that gradient descent converges to the max-margin direction for logistic regression with one-layer or multi-layer linear networks. In this paper, we generalize this result to homogeneous neural networks, ... More

Network-Connected UAV: 3D System Modeling and Coverage Performance AnalysisJan 19 2019Apr 25 2019With growing popularity, unmanned aerial vehicles (UAVs) are pivotally extending conventional terrestrial Internet of Things (IoT) into the sky. To enable high-performance two-way communications of UAVs with their ground pilots/users, cellular network-connected ... More

Dynamical Quantum Phase Transitions in Interacting Atomic InterferometersJul 09 2018Particle-wave duality has allowed physicists to establish atomic interferometers as celebrated complements to their optical counterparts in a broad range of quantum devices. However, interactions naturally lead to decoherence and have been considered ... More

Persistence of sums of correlated increments and clustering in cellular automataJun 25 2017Sep 01 2017We consider sums of increments given by a functional of a stationary Markov chain. Letting $T$ be the first return time of the partial sums process to $(-\infty,0]$, under general assumptions, we determine the asymptotic behavior of the survival probability, ... More

Residual Attention based Network for Hand Bone Age AssessmentDec 21 2018Computerized automatic methods have been employed to boost the productivity as well as objectiveness of hand bone age assessment. These approaches make predictions according to the whole X-ray images, which include other objects that may introduce distractions. ... More

A parallel sweeping preconditioner for heterogeneous 3D Helmholtz equationsMar 31 2012Feb 05 2013A parallelization of a sweeping preconditioner for 3D Helmholtz equations without large cavities is introduced and benchmarked for several challenging velocity models. The setup and application costs of the sequential preconditioner are shown to be O({\gamma}^2 ... More

The coherent structure of the energy cascade in shear turbulenceApr 04 2019Apr 08 2019The cascade of energy in turbulent flows, i.e., the transfer of kinetic energy from large to small flow motions (forward cascade) or vice versa (backward cascade), is the cornerstone of most theories and models of turbulence since the 1940s. Yet, understanding ... More

Application of gold in the field of heterogeneous catalysisNov 09 2014Gold has been long thought as an inert metal which finds most of its use in jewelry and monetary exchange. However, catalysis by gold has rapidly become a hot topic in chemistry ever since Haruta and Hutchings found gold to be an extraordinary good heterogeneous ... More

Challenge AI Mind: A Crowd System for Proactive AI TestingOct 21 2018Artificial Intelligence (AI) has burrowed into our lives in various aspects; however, without appropriate testing, deployed AI systems are often being criticized to fail in critical and embarrassing cases. Existing testing approaches mainly depend on ... More

On high order accurate schemes for space fractional diffusion equations with variable coefficientsAug 29 2016Oct 14 2016We study high order schemes for spatial fractional differential equations with variable coefficients. Approximations of fractional derivatives basing on the weighted and shifted Gr\"unwald-Letnikov formulas and weighted and shifted Lubich formulas are ... More

AMR Parsing as Graph Prediction with Latent AlignmentMay 14 2018Abstract meaning representations (AMRs) are broad-coverage sentence-level semantic representations. AMRs represent sentences as rooted labeled directed acyclic graphs. AMR parsing is challenging partly due to the lack of annotated alignments between nodes ... More

0-1 matrices with zero trace whose squares are 0-1 matricesMar 04 2018In this paper, we determine the maximum number of nonzero entries in 0-1 matrices of order $n$ with zero trace whose squares are 0-1 matrices when $n\ge 8$. The extremal matrices attaining this maximum number are also characterized.

Experimental validation of the hybrid scattering model of installed jet noiseJul 31 2018Jet installation causes jet noise to be amplified significantly at low frequencies and its physical mechanism must be understood to develop effective aircraft noise reduction strategies. A hybrid semi-empirical prediction model has recently been developed ... More

Extremal digraphs avoiding an orientation of $C_4$Feb 09 2018Let $P_{2,2}$ be the orientation of $C_4$ which consists of two 2-paths with the same initial and terminal vertices. In this paper, we determine the maximum size of $P_{2,2}$-free digraphs of order $n$ as well as the extremal digraphs attaining the maximum ... More

A Fast 2-Approximation Algorithm for Guarding Orthogonal TerrainsMay 11 2016May 17 2016Terrain Guarding Problem(TGP), which is known to be NP-complete, asks to find a smallest set of guard locations on a terrain $T$ such that every point on $T$ is visible by a guard. Here, we study this problem on 1.5D orthogonal terrains where the edges ... More

Core-compactness of Smyth powerspacesJul 10 2019We prove that the Smyth powerspace Q(X) of a topological space X is core-compact if and only if X is locally compact. As a straightforward consequence we obtain that the Smyth powerspace construction does not preserve core-compactness generally.

Weak contraction map and topological non-convex optimizationJul 08 2018Nov 11 2018The definition of weak contraction map and the existence and uniqueness of the fixed-point of weak contraction map is discussed. A stochastic contour-based optimization method based on weak contraction map is proposed to achieve global minimum convergence. ... More

Semi-Supervised Endmember Identification In Nonlinear Spectral Mixtures Via Semantic RepresentationJan 03 2017This paper proposes a new hyperspectral unmixing method for nonlinearly mixed hyperspectral data using a semantic representation in a semi-supervised fashion, assuming the availability of a spectral reference library. Existing semi-supervised unmixing ... More