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Statistical analysis of motion contrast in optical coherence tomography angiographySep 24 2015Nov 03 2015Optical coherence tomography angiography (Angio-OCT), mainly based on the temporal dynamics of OCT scattering signals, has found a range of potential applications in clinical and scientific research. Based on the model of random phasor sums, temporal ... More

GRP Model for Sensorimotor LearningMar 01 2019Learning from complex demonstrations is challenging, especially when the demonstration consists of different strategies. A popular approach is to use a deep neural network to perform imitation learning. However, the structure of that deep neural network ... More

Improved Selective Refinement Network for Face DetectionJan 20 2019Jan 30 2019As a long-standing problem in computer vision, face detection has attracted much attention in recent decades for its practical applications. With the availability of face detection benchmark WIDER FACE dataset, much of the progresses have been made by ... More

Effective Incorporation of Speaker Information in Utterance Encoding in DialogJul 12 2019In dialog studies, we often encode a dialog using a hierarchical encoder where each utterance is converted into an utterance vector, and then a sequence of utterance vectors is converted into a dialog vector. Since knowing who produced which utterance ... More

Connecting Weighted Automata and Recurrent Neural Networks through Spectral LearningJul 04 2018In this paper, we unravel a fundamental connection between weighted finite automata~(WFAs) and second-order recurrent neural networks~(2-RNNs): in the case of sequences of discrete symbols, WFAs and 2-RNNs with linear activation functions are expressively ... More

Neural Network Based Nonlinear Weighted Finite AutomataSep 13 2017Dec 21 2017Weighted finite automata (WFA) can expressively model functions defined over strings but are inherently linear models. Given the recent successes of nonlinear models in machine learning, it is natural to wonder whether ex-tending WFA to the nonlinear ... More

Connecting Weighted Automata and Recurrent Neural Networks through Spectral LearningJul 04 2018Apr 08 2019In this paper, we unravel a fundamental connection between weighted finite automata~(WFAs) and second-order recurrent neural networks~(2-RNNs): in the case of sequences of discrete symbols, WFAs and 2-RNNs with linear activation functions are expressively ... More

Electric Field Effect in Multilayer Cr2Ge2Te6: a Ferromagnetic Two-Dimensional MaterialApr 28 2017The emergence of two-dimensional (2D) materials has attracted a great deal of attention due to their fascinating physical properties and potential applications for future nanoelectronic devices. Since the first isolation of graphene, a Dirac material, ... More

Experimental Adiabatic Quantum Factorization under Ambient Conditions Based on a Solid-State Single Spin SystemNov 10 2016The adiabatic quantum computation is a universal and robust method of quantum computing. In this architecture, the problem can be solved by adiabatically evolving the quantum processor from the ground state of a simple initial Hamiltonian to that of a ... More

Visual Tracking via Dynamic Memory NetworksJul 12 2019Template-matching methods for visual tracking have gained popularity recently due to their good performance and fast speed. However, they lack effective ways to adapt to changes in the target object's appearance, making their tracking accuracy still far ... More

TextBugger: Generating Adversarial Text Against Real-world ApplicationsDec 13 2018Deep Learning-based Text Understanding (DLTU) is the backbone technique behind various applications, including question answering, machine translation, and text classification. Despite its tremendous popularity, the security vulnerabilities of DLTU are ... More

Synergistic Drug Combination Prediction by Integrating Multi-omics Data in Deep Learning ModelsNov 16 2018Drug resistance is still a major challenge in cancer therapy. Drug combination is expected to overcome drug resistance. However, the number of possible drug combinations is enormous, and thus it is infeasible to experimentally screen all effective drug ... More

The energy transfer and its effects on the secondaries in W Ursae Majoris-type contact binariesApr 03 2009The energy transfer of W UMa contact binaries and its effects on the secondary in W UMa contact binaries are investigated. Relations are given between the mass ratio (q) and the relative energy transfer rates, i.e. U1, the ratio of the transferred luminosity ... More

Using Deep Reinforcement Learning to Learn High-Level Policies on the ATRIAS BipedSep 28 2018Learning controllers for bipedal robots is a challenging problem, often requiring expert knowledge and extensive tuning of parameters that vary in different situations. Recently, deep reinforcement learning has shown promise at automatically learning ... More

Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View SynthesisApr 13 2017Aug 04 2017Photorealistic frontal view synthesis from a single face image has a wide range of applications in the field of face recognition. Although data-driven deep learning methods have been proposed to address this problem by seeking solutions from ample face ... More

The evolutionary status of W Ursae Majoris-type systemsMay 27 2008Well-determined physical parameters of 130 W UMa systems have been collected from the literature. Based on these data, the evolutionary status and dynamical evolution of W UMa systems are investigated. It is found that there is no evolutionary difference ... More

Coalitional Graph Games for Popular Content Distribution in Cognitive Radio VANETsAug 14 2014Popular content distribution is one of the key services provided by vehicular ad hoc networks (VANETs), in which a popular file is broadcasted by roadside units (RSUs) to the on-board units (OBUs) driving through a particular area. Due to fast speed and ... More

Bayesian Optimization in Variational Latent Spaces with Dynamic CompressionJul 10 2019Data-efficiency is crucial for autonomous robots to adapt to new tasks and environments. In this work we focus on robotics problems with a budget of only 10-20 trials. This is a very challenging setting even for data-efficient approaches like Bayesian ... More

Distributed Cooperative Sensing in Cognitive Radio Networks: An Overlapping Coalition Formation ApproachAug 14 2014Cooperative spectrum sensing has been shown to yield a significant performance improvement in cognitive radio networks. In this paper, we consider distributed cooperative sensing (DCS) in which secondary users (SUs) exchange data with one another instead ... More

Transaction Fraud Detection Using GRU-centered Sandwich-structured ModelNov 04 2017Mar 19 2018Rapid growth of modern technologies such as internet and mobile computing are bringing dramatically increased e-commerce payments, as well as the explosion in transaction fraud. Meanwhile, fraudsters are continually refining their tricks, making rule-based ... More

Sentiment-Based Prediction of Alternative Cryptocurrency Price Fluctuations Using Gradient Boosting Tree ModelMay 01 2018In this paper, we analyze Twitter signals as a medium for user sentiment to predict the price fluctuations of a small-cap alternative cryptocurrency called \emph{ZClassic}. We extracted tweets on an hourly basis for a period of 3.5 weeks, classifying ... More

Geodesic rigidity of Levi-Civita connections admitting essential projective vector fieldsMay 01 2017Dec 03 2018In this paper, it is proved that a connected 3-dimensional Riemannian manifold or a closed connected semi-Riemannian manifold $M^n$($n>1$) admitting a projective vector field with a non-linearizable singularity is projectively flat.

Unique equilibrium states, large deviations and Lyapunov spectra for the Katok MapMar 07 2019Apr 03 2019We study the thermodynamical formalism of a $C^{\infty}$ non-uniformly hyperbolic diffeomorphism on 2-torus, known as the Katok map. We prove for H\"older continuous potential with one additional condition and geometric t-potential $\varphi_t$ with $t<1$, ... More

Learning to Transfer: Unsupervised Meta Domain TranslationJun 01 2019Jul 05 2019Unsupervised domain translation has recently achieved impressive performance with rapidly developed generative adversarial network (GAN) and availability of sufficient training data. However, existing domain translation frameworks form in a disposable ... More

Unique equilibrium states, large deviations and Lyapunov spectra for the Katok MapMar 07 2019We study the thermodynamical formalism of a $C^{\infty}$ non-uniformly hyperbolic diffeomorphism on 2-torus, known as the Katok map. We prove for H\"older continuous potential with one additional condition and geometric t-potential $\varphi_t$ with $t<1$, ... More

Optimal portfolio model based on WVARNov 24 2012This article is focused on using a new measurement of risk-- Weighted Value at Risk to develop a new method of constructing initiate from the TVAR solving problem, based on MATLAB software, using the historical simulation method (avoiding income distribution ... More

Expander Graph and Communication-Efficient Decentralized OptimizationDec 03 2016In this paper, we discuss how to design the graph topology to reduce the communication complexity of certain algorithms for decentralized optimization. Our goal is to minimize the total communication needed to achieve a prescribed accuracy. We discover ... More

Fast Skill Learning for Variable Compliance Robotic AssemblyMay 11 2019The robotic assembly represents a group of benchmark problems for reinforcement learning and variable compliance control that features sophisticated contact manipulation. One of the key challenges in applying reinforcement learning to physical robot is ... More

Depict noise-driven nonlinear dynamic networks from output data by using high-order correlationsMay 18 2016Aug 17 2016Many practical systems can be described by dynamic networks, for which modern technique can measure their output signals, and accumulate extremely rich data. Nevertheless, the network structures producing these data are often deeply hidden in these data. ... More

Chebyshev Interpolation for Function in 1DSep 24 2018This research is concerned with finding the roots of a function in an interval using Chebyshev Interpolation. Numerical results of Chebyshev Interpolation are presented to show that this is a powerful way to simultaneously calculate all the roots in an ... More

Listen-and-Talk: Full-duplex Cognitive Radio NetworksJul 13 2014In traditional cognitive radio networks, secondary users (SUs) typically access the spectrum of primary users (PUs) by a two-stage "listen-before-talk" (LBT) protocol, i.e., SUs sense the spectrum holes in the first stage before transmit in the second ... More

Deep Heterogeneous Autoencoders for Collaborative FilteringDec 17 2018This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from heterogeneous data, such as item descriptions, product tags and online purchase ... More

Boosting Adversarial Attacks with MomentumOct 17 2017Mar 22 2018Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences. Adversarial attacks serve as an important surrogate to evaluate the robustness of deep learning ... More

SirenAttack: Generating Adversarial Audio for End-to-End Acoustic SystemsJan 23 2019Despite their immense popularity, deep learning-based acoustic systems are inherently vulnerable to adversarial attacks, wherein maliciously crafted audios trigger target systems to misbehave. In this paper, we present SirenAttack, a new class of attacks ... More

Order-Planning Neural Text Generation From Structured DataSep 01 2017Generating texts from structured data (e.g., a table) is important for various natural language processing tasks such as question answering and dialog systems. In recent studies, researchers use neural language models and encoder-decoder frameworks for ... More

Electronic structure of topological superconductors in the presence of a vortex latticeJun 16 2015Oct 09 2015Certain types of topological superconductors and superfluids are known to host protected Majorana zero modes in cores of Abrikosov vortices. When such vortices are arranged in a dense periodic lattice one expects zero modes from neighboring vortices to ... More

Shortest Paths in HSI Space for Color Texture ClassificationApr 16 2019Color texture representation is an important step in the task of texture classification. Shortest paths was used to extract color texture features from RGB and HSV color spaces. In this paper, we propose to use shortest paths in the HSI space to build ... More

PCA-based lung motion modelJan 30 2010Organ motion induced by respiration may cause clinically significant targeting errors and greatly degrade the effectiveness of conformal radiotherapy. It is therefore crucial to be able to model respiratory motion accurately. A recently proposed lung ... More

Research on Control Method and Evaluation System of Ground Unmanned Vehicle Formation TransformAug 05 2018In this paper,we design a formation control systrm for multi-unmanned ground vehicles(UGV) from the prospective of path planning and path tracking.The master-slave control is adopted by electing out a main vehicle to address the problem of possible accumulation,tranmission ... More

Research on Control Method and Evaluation System of Ground Unmanned Vehicle Formation TransformAug 05 2018Apr 27 2019In this paper,we design a formation control systrm for multi-unmanned ground vehicles(UGV) from the prospective of path planning and path tracking.The master-slave control is adopted by electing out a main vehicle to address the problem of possible accumulation,tranmission ... More

Research on Control Method and Evaluation System of Ground Unmanned Vehicle Formation TransformAug 05 2018Jul 04 2019In this paper,we design a formation control systrm for multi-unmanned ground vehicles(UGV) from the prospective of path planning and path tracking.The master-slave control is adopted by electing out a main vehicle to address the problem of possible accumulation,tranmission ... More

Bifurcation to coherent structures in nonlocally coupled systemsApr 28 2017We show bifurcation of localized spike solutions from spatially constant states in systems of nonlocally coupled equations in the whole space. The main assumptions are a generic bifurcation of saddle-node or transcritical type for spatially constant profiles, ... More

Magnon quantum anomalies in Weyl ferromagnetsMar 08 2019When subjected to parallel electric field $\mathbf E$ and magnetic field $\mathbf B$, Weyl semimetals exhibit the exotic transport property known as the chiral anomaly due to the pumping of electrons between Weyl cones of opposite chiralities. When one ... More

Formalization of the Axiom of Choice and its Equivalent TheoremsJun 10 2019In this paper, we describe the formalization of the axiom of choice and several of its famous equivalent theorems in Morse-Kelley set theory. These theorems include Tukey's lemma, the Hausdorff maximal principle, the maximal principle, Zermelo's postulate, ... More

Unit-free and robust detection of differential expression from RNA-Seq dataMay 18 2014Aug 26 2016Ultra high-throughput sequencing of transcriptomes (RNA-Seq) is a widely used method for quantifying gene expression levels due to its low cost, high accuracy and wide dynamic range for detection. However, the nature of RNA-Seq makes it nearly impossible ... More

Learning based Facial Image Compression with Semantic Fidelity MetricDec 25 2018Surveillance and security scenarios usually require high efficient facial image compression scheme for face recognition and identification. While either traditional general image codecs or special facial image compression schemes only heuristically refine ... More

Content Word-based Sentence Decoding and Evaluating for Open-domain Neural Response GenerationMay 31 2019Various encoder-decoder models have been applied to response generation in open-domain dialogs, but a majority of conventional models directly learn a mapping from lexical input to lexical output without explicitly modeling intermediate representations. ... More

Learning based Facial Image Compression with Semantic Fidelity MetricDec 25 2018Mar 07 2019Surveillance and security scenarios usually require high efficient facial image compression scheme for face recognition and identification. While either traditional general image codecs or special facial image compression schemes only heuristically refine ... More

Electric Control of Spin Currents and Spin-Wave LogicApr 04 2011May 30 2011Spin waves in insulating magnets are ideal carriers for spin currents with low energy dissipation. An electric field can modify the dispersion of spin waves, by directly affecting, via spin-orbit coupling, the electrons that mediate the interaction between ... More

Generative adversarial network based on chaotic time seriesMay 24 2019Generative adversarial network (GAN) is gaining increased importance in artificially constructing natural images and related functionalities wherein two networks called generator and discriminator are evolving through adversarial mechanisms. Using deep ... More

Defense against Adversarial Attacks Using High-Level Representation Guided DenoiserDec 08 2017May 08 2018Neural networks are vulnerable to adversarial examples, which poses a threat to their application in security sensitive systems. We propose high-level representation guided denoiser (HGD) as a defense for image classification. Standard denoiser suffers ... More

Background Radiation Cancellation for Free-Space Optical Communications with IM/DDAug 29 2015Besides atmospheric turbulence and pointing errors which cause the signal intensity fluctuation, background radiation also impairs the free-space optical intensity-modulation / direct-detection link performance by introducing a noisy photocurrent component ... More

Dirac-Point Solitons in Nonlinear Optical LatticesNov 24 2015The discovery of a new type of solitons occuring in periodic systems without photonic bandgaps is reported. Solitons are nonlinear self-trapped wave packets. They have been extensively studied in many branches of physics. Solitons in periodic systems, ... More

Column size effects of DER fluidsFeb 01 2001Mar 27 2001The static yield stress of dielectric electrorheological(DER) fluids of infinite column state and chain state are calculated from the first principle method. The results indicate that the column surface contributions to ER effects is very small and both ... More

The Costabel-Stephan system of Boundary Integral Equations in the Time DomainAug 12 2014In this paper we formulate a transmission problem for the transient acoustic wave equation as a system of retarded boundary integral equations. We then analyse a fully discrete method using a general Galerkin semidiscretization-in-space and Convolution ... More

A Robust and Efficient Detection Algorithm for The Photon-Counting Free-Space Optical SystemNov 13 2014We propose a Viterbi-type trellis-search algorithm to implement the FSO photon-counting sequence receiver proposed in [1] more efficiently and a selective-store strategy to overcome the error floor problem observed therein.

New mapping properties of the Time Domain Electric Field Integral EquationSep 03 2015We show some improved mapping properties of the Time Domain Electric Field Integral Equation and of its Galerkin semidiscretization in space. We relate the weak distributional framework with a stronger class of solutions using a group of strongly continuous ... More

Efficient Symbol Detection for the FSO IM/DD System with Automatic and Adaptive Threshold Adjustment: The Multi-level PAM CaseMay 11 2015To detect M-ary pulse amplitude modulation signals reliably in an FSO communication system, the receiver requires accurate knowledge about the instantaneous channel attenuation on the signal. We derive here an optimum, symbol-by-symbol receiver that jointly ... More

Undersampled Phase Retrieval via Majorization-MinimizationSep 09 2016In the undersampled phase retrieval problem, the goal is to recover an $N$-dimensional complex signal $\mathbf{x}$ from only $M<N$ noisy intensity measurements without phase information. This problem has drawn a lot of attention to reduce the number of ... More

Robust Data Detection for the Photon-Counting Free-Space Optical System with Implicit CSI Acquisition and Background Radiation CompensationMay 11 2015Since atmospheric turbulence and pointing errors cause signal intensity fluctuations and the background radiation surrounding the free-space optical (FSO) receiver contributes an undesired noisy component, the receiver requires accurate channel state ... More

Efficient Direct Detection of M-PAM Sequences with Implicit CSI Acquisition for The FSO SystemNov 07 2014Compared to on-off keying (OOK), M-ary pulse amplitude modulation (M-PAM, M>2) is more spectrally efficient. However, to detect M-PAM signals reliably, the requirement of accurate channel state information is more stringent. Previously, for OOK systems, ... More

Learning Dynamic Memory Networks for Object TrackingMar 20 2018Sep 02 2018Template-matching methods for visual tracking have gained popularity recently due to their comparable performance and fast speed. However, they lack effective ways to adapt to changes in the target object's appearance, making their tracking accuracy still ... More

Recurrent Filter Learning for Visual TrackingAug 13 2017Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images. Recent methods perform online tracking by fine-tuning a pre-trained CNN model to the specific target object ... More

Background Radiation Cancellation for Free-Space Optical Communications with IM/DDAug 29 2015Jun 19 2017Besides atmospheric turbulence and pointing errors which cause the signal intensity fluctuation, background radiation also impairs the free-space optical intensity-modulation / direct-detection link performance by introducing a noisy photocurrent component ... More

Counting perfect matchings and the eight-vertex modelApr 23 2019We study the approximation complexity of the partition function of the eight-vertex model on general 4-regular graphs. For the first time, we relate the approximability of the eight-vertex model to the complexity of approximately counting perfect matchings, ... More

Multitasking with Alexa Multitasking with Alexa: How Using Intelligent Personal Assistants Impacts Language-based Primary Task PerformanceJul 03 2019Intelligent personal assistants (IPAs) are supposed to help us multitask. Yet the impact of IPA use on multitasking is not clearly quantified, particularly in situations where primary tasks are also language based. Using a dual task paradigm, our study ... More

BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply ChainAug 22 2017Deep learning-based techniques have achieved state-of-the-art performance on a wide variety of recognition and classification tasks. However, these networks are typically computationally expensive to train, requiring weeks of computation on many GPUs; ... More

Modeling and Analysis for Cache-Enabled Networks with Dynamic TrafficSep 19 2016Instead of assuming fully loaded cells in the analysis on cache-enabled networks with tools of stochastic geometry, we focus on the dynamic traffic in this letter. With modeling traffic dynamics of request arrivals and departures, probabilities of full-, ... More

Modeling and Simulation of UAV Carrier LandingsJan 23 2019With UAVs promising capabilities to increase operation flexibility and reduce mission cost, we are exploiting the automated carrier-landing performance advancement that can be achieved by fixed-wing UAVs. To demonstrate such potentials, in this paper, ... More

BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply ChainAug 22 2017Mar 11 2019Deep learning-based techniques have achieved state-of-the-art performance on a wide variety of recognition and classification tasks. However, these networks are typically computationally expensive to train, requiring weeks of computation on many GPUs; ... More

Estimating Historical Functional Linear Models with a Nested Group Bridge ApproachSep 13 2018We study a scalar-on-function historical linear regression model which assumes that the functional predictor does not influence the response when the time passes a certain cutoff point. We approach this problem from the perspective of locally sparse modeling, ... More

Cyclic Coordinate Update Algorithms for Fixed-Point Problems: Analysis and ApplicationsNov 08 2016Mar 02 2017Many problems reduce to the fixed-point problem of solving $x=T(x)$. To this problem, we apply the coordinate-update algorithms, which update only one or a few components of $x$ at each step. When each update is cheap, these algorithms are faster than ... More

Recovering Pairwise Interactions Using Neural NetworksJan 24 2019Recovering pairwise interactions, i.e. pairs of input features whose joint effect on an output is different from the sum of their marginal effects, is central in many scientific applications. We conceptualize a solution to this problem as a two-stage ... More

A Practical Bandit Method with Advantages in Neural Network TuningJan 26 2019Feb 21 2019Stochastic bandit algorithms can be used for challenging non-convex optimization problems. Hyperparameter tuning of neural networks is particularly challenging, necessitating new approaches. To this end, we present a method that adaptively partitions ... More

Remotely sensed transport in microwave photoexcited GaAs/AlGaAs two-dimensional electron systemNov 13 2013We demonstrate a strong correlation between the magnetoresistive and the concurrent microwave reflection from the microwave photo-excited GaAs/AlGaAs two-dimensional electron system (2DES). These correlations are followed as a function of the microwave ... More

Evolution of the linear-polarization-angle-dependence of the radiation-induced magnetoresistance-oscillations with microwave powerNov 19 2014We examine the role of the microwave power in the linear polarization angle dependence of the microwave radiation induced magnetoresistance oscillations observed in the high mobility GaAs/AlGaAs two dimensional electron system. Diagonal resistance $R_{xx}$ ... More

Remote sensor response study in the regime of the microwave radiation-induced magnetoresistance oscillationsNov 13 2013A concurrent remote sensing and magneto-transport study of the microwave excited two dimensional electron system (2DES) at liquid Helium temperatures has been carried out using a carbon detector to remotely sense the microwave activity of the 2D electron ... More

DeepOPF: Deep Neural Network for DC Optimal Power FlowMay 11 2019May 17 2019We develop DeepOPF as a Deep Neural Network (DNN) approach for solving direct current optimal power flow (DC-OPF) problems. DeepOPF is inspired by the observation that solving DC-OPF for a given power network is equivalent to characterizing a high-dimensional ... More

Cyclic Coordinate Update Algorithms for Fixed-Point Problems: Analysis and ApplicationsNov 08 2016Many problems reduce to the fixed-point problem of solving $x=T(x)$. To this problem, we apply the coordinate-update algorithms, which update only one or a few components of $x$ at each step. When each update is cheap, these algorithms are faster than ... More

Quantum oscillations without magnetic fieldAug 16 2016When magnetic field $B$ is applied to a metal, nearly all observable quantities exhibit oscillations periodic in $1/B$. Such quantum oscillations reflect the fundamental reorganization of electron states into Landau levels as a canonical response of the ... More

Sum Secrecy Rate Maximization in a Multi-Carrier MIMO Wiretap Channel with Full-Duplex JammingFeb 14 2018Feb 16 2018In this paper we address a sum secrecy rate maximization problem for a multi-carrier and MIMO communication system. We consider the case that the receiver is capable of full-duplex (FD) operation and simultaneously sends jamming signal to a potential ... More

A Data Driven Approach for Motion Planning of Autonomous Driving Under Complex ScenarioApr 18 2019To guarantee the safe and efficient motion planning of autonomous driving under dynamic traffic environment, the autonomous vehicle should be equipped with not only the optimal but also a long term efficient policy to deal with complex scenarios. The ... More

Design and Analysis of Multi-User SDMA Systems with Noisy Limited CSIT FeedbackJan 18 2010Jan 21 2010In this paper, we consider spatial-division multiple-access (SDMA) systems with one base station with multiple antennae and a number of single antenna mobiles under noisy limited CSIT feedback. We propose a robust noisy limited feedback design for SDMA ... More

DeepOPF: Deep Neural Network for DC Optimal Power FlowMay 11 2019We develop DeepOPF as a Deep Neural Network (DNN) approach for solving discrete circuit optimal power flow (DC-OPF) problems. DeepOPF is inspired by the observation that solving DC-OPF for a given power network is equivalent to characterizing a high-dimensional ... More

Approximability of the Six-vertex ModelDec 16 2017In this paper we take the first step toward a classification of the approximation complexity of the six-vertex model, an object of extensive research in statistical physics. Our complexity results conform to the phase transition phenomenon from physics. ... More

Max-Mahalanobis Linear Discriminant Analysis NetworksFeb 26 2018Jun 19 2018A deep neural network (DNN) consists of a nonlinear transformation from an input to a feature representation, followed by a common softmax linear classifier. Though many efforts have been devoted to designing a proper architecture for nonlinear transformation, ... More

Predict genome-scale fluxes based solely on enzyme abundance by a novel Hyper-Cube Shrink AlgorithmOct 04 2016One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the flux distribution. Both ordinary differential equation (ODE) models and the constraint-based models, like Flux balance analysis ... More

Nonlocal Drag of Magnons in a Ferromagnetic BilayerMay 13 2016Quantized spin waves, or magnons, in a magnetic insulator are assumed to interact weakly with the surroundings, and to flow with little dissipation or drag, producing exceptionally long diffusion lengths and relaxation times. In analogy to Coulomb drag ... More

PRIME: Phase Retrieval via Majorization-MinimizationNov 05 2015Nov 13 2015This paper considers the phase retrieval problem in which measurements consist of only the magnitude of several linear measurements of the unknown, e.g., spectral components of a time sequence. We develop low-complexity algorithms with superior performance ... More

Quantum oscillations and Dirac-Landau levels in Weyl superconductorsOct 16 2017Jan 09 2018When magnetic field is applied to metals and semimetals quantum oscillations appear as individual Landau levels cross the Fermi level. Quantum oscillations generally do not occur in superconductors (SC) because magnetic field is either expelled from the ... More

Superconducting-contact-induced resistance-anomalies in the 3D topological insulator Bi2Te3Feb 13 2016This study examines the magnetotransport response observed in flakes of the 3D topological insulator (TI) Bi2Te3, including indium superconducting electrodes, and demonstrates two critical transitions in the magnetoresistive response with decreasing temperatures ... More

Transition fronts for inhomogeneous monostable reaction-diffusion equations via linearization at zeroNov 28 2013We prove existence of transition fronts for a large class of reaction-diffusion equations in one dimension, with inhomogeneous monostable reactions. We construct these as perturbations of corresponding front-like solutions to the linearization of the ... More

Learning Pairwise Interactions with Bayesian Neural NetworksJan 24 2019May 23 2019Estimating pairwise interaction effects, i.e., the difference between the joint effect and the sum of marginal effects of two input features, with uncertainty properly quantified, is centrally important in science applications. We propose a non-parametric ... More

SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted CloudJun 30 2017Inference using deep neural networks is often outsourced to the cloud since it is a computationally demanding task. However, this raises a fundamental issue of trust. How can a client be sure that the cloud has performed inference correctly? A lazy cloud ... More

Crystal Structure Manipulation of the Exchange Bias in an Antiferromagnetic FilmJun 03 2016Exchange bias is one of the most extensively studied phenomena in magnetism, since it exerts a unidirectional anisotropy to a ferromagnet (FM) when coupled to an antiferromagnet (AFM) and the control of the exchange bias is therefore very important for ... More

VLBI ecliptic plane survey: VEPS-1Jan 25 2017Jun 09 2017We present here the results of the first part of the VLBI Ecliptic Plane Survey (VEPS) program. The goal of the program is to find all compact sources within $7.5^\circ$ of the ecliptic plane which are suitable as calibrators for anticipated phase referencing ... More

Hyperscaling Violating Solutions in Generalised EMD TheoryAug 10 2016Sep 01 2016This short note is devoted to deriving scaling but hyperscaling violating solutions in a generalised Einstein-Maxwell-Dilaton theory with an arbitrary number of scalars and vectors. We obtain analytic solutions in some special case and discuss the physical ... More

Phase transition for accessibility percolation on hypercubesFeb 26 2015Jun 02 2017In this paper, we consider accessibility percolation on hypercubes, i.e., we place i.i.d. uniform [0,1] random variables on vertices of a hypercube, and study whether there is a path connecting two vertices such that the values of these random variables ... More

Phase transition for accessibility percolation on hypercubesFeb 26 2015In this paper, we consider accessibility percolation on hypercubes, i.e., we place i.i.d.\ uniform random variables on vertices of a hypercube, and study whether there is a path (possibly with back steps) connecting two vertices such that the values of ... More

Wonderful compactification of an arrangement of subvarietiesNov 14 2006Jan 01 2009We define the wonderful compactification of an arrangement of subvarieties. Given a complex nonsingular algebraic variety $Y$ and certain collection $\mathcal{G}$ of subvarieties of $Y$, the wonderful compactification $Y_\mathcal{G}$ can be constructed ... More