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Results for "Liwei Wang"

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Distributed Bandit Learning: How Much Communication is Needed to Achieve (Near) Optimal RegretApr 12 2019We study the communication complexity of distributed multi-armed bandits (MAB) and distributed linear bandits for regret minimization. We propose communication protocols that achieve near-optimal regret bounds and result in optimal speed-up under mild ... More
Differentially Private Data Releasing for Smooth Queries with Synthetic Database OutputJan 06 2014We consider accurately answering smooth queries while preserving differential privacy. A query is said to be $K$-smooth if it is specified by a function defined on $[-1,1]^d$ whose partial derivatives up to order $K$ are all bounded. We develop an $\epsilon$-differentially ... More
The Expressive Power of Neural Networks: A View from the WidthSep 08 2017Nov 01 2017The expressive power of neural networks is important for understanding deep learning. Most existing works consider this problem from the view of the depth of a network. In this paper, we study how width affects the expressiveness of neural networks. Classical ... More
Learning Region Features for Object DetectionMar 19 2018While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work proposes a general viewpoint that unifies existing region feature extraction ... More
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural NetworksJun 14 2017Aug 29 2017Early detection of pulmonary cancer is the most promising way to enhance a patient's chance for survival. Accurate pulmonary nodule detection in computed tomography (CT) images is a crucial step in diagnosing pulmonary cancer. In this paper, inspired ... More
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC ClassesFeb 18 2017In this work we study the quantitative relation between the recursive teaching dimension (RTD) and the VC dimension (VCD) of concept classes of finite sizes. The RTD of a concept class $\mathcal C \subseteq \{0, 1\}^n$, introduced by Zilles et al. (2011), ... More
A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored SearchJun 03 2014Jun 04 2014Sponsored search is an important monetization channel for search engines, in which an auction mechanism is used to select the ads shown to users and determine the prices charged from advertisers. There have been several pieces of work in the literature ... More
Training Deeper Convolutional Networks with Deep SupervisionMay 11 2015One of the most promising ways of improving the performance of deep convolutional neural networks is by increasing the number of convolutional layers. However, adding layers makes training more difficult and computationally expensive. In order to train ... More
Quantum phase transitions in the spin-boson model without the counterrotating termsDec 10 2018We study the spin-boson model without the counterrotating terms by a numerically exact method based on variational matrix product states. Surprisingly, the second-order quantum phase transition (QPT) is observed for the sub-Ohmic bath in the rotating-wave ... More
Low Rank Approximation of Binary Matrices: Column Subset Selection and GeneralizationsNov 05 2015Apr 20 2017Low rank matrix approximation is an important tool in machine learning. Given a data matrix, low rank approximation helps to find factors, patterns and provides concise representations for the data. Research on low rank approximation usually focus on ... More
Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot LearningOct 19 2018Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to unseen ones so that the latter can be recognised without any training samples. This is made possible by learning a projection function between a feature space and a semantic space ... More
Zero-Shot Fine-Grained Classification by Deep Feature Learning with SemanticsJul 04 2017Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task due to two main issues: lack of sufficient training data for every class and difficulty in learning discriminative features for representation. ... More
Gradient Descent Finds Global Minima of Deep Neural NetworksNov 09 2018Feb 04 2019Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The current paper proves gradient descent achieves zero training loss in polynomial time for a deep over-parameterized neural network ... More
Pairwise Constraint Propagation on Multi-View DataJan 18 2015This paper presents a graph-based learning approach to pairwise constraint propagation on multi-view data. Although pairwise constraint propagation has been studied extensively, pairwise constraints are usually defined over pairs of data points from a ... More
CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data ModelJan 22 2019Background: Widespread adoption of electronic health records (EHRs) has enabled secondary use of EHR data for clinical research and healthcare delivery. Natural language processing (NLP) techniques have shown promise in their capability to extract the ... More
KBGAN: Adversarial Learning for Knowledge Graph EmbeddingsNov 11 2017Apr 16 2018We introduce KBGAN, an adversarial learning framework to improve the performances of a wide range of existing knowledge graph embedding models. Because knowledge graphs typically only contain positive facts, sampling useful negative training examples ... More
Broken Dynamic Symmetry and Phase Transition PrecursorFeb 22 2013Symmetry breaking is a central concept of Landau phase transition theory, which, however, only considers time-averaged static symmetry of crystal lattice while neglects dynamic symmetry of lattice vibrations thus fails to explain the ubiquitous transformation ... More
A convergent linearized Lagrange finite element method for the magneto-hydrodynamic equations in 2D nonsmooth and nonconvex domainsFeb 12 2019A new fully discrete linearized $H^1$-conforming Lagrange finite element method is proposed for solving the two-dimensional magneto-hydrodynamics equations based on a magnetic potential formulation. The proposed method yields numerical solutions that ... More
A convergent linearized Lagrange finite element method for the magneto-hydrodynamic equations in 2D nonsmooth and nonconvex domainsFeb 12 2019Mar 09 2019A new fully discrete linearized $H^1$-conforming Lagrange finite element method is proposed for solving the two-dimensional magneto-hydrodynamics equations based on a magnetic potential formulation. The proposed method yields numerical solutions that ... More
Learning Deep Structure-Preserving Image-Text EmbeddingsNov 19 2015Apr 14 2016This paper proposes a method for learning joint embeddings of images and text using a two-branch neural network with multiple layers of linear projections followed by nonlinearities. The network is trained using a large margin objective that combines ... More
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning PossibleJun 11 2017Non-interactive Local Differential Privacy (LDP) requires data analysts to collect data from users through noisy channel at once. In this paper, we extend the frontiers of Non-interactive LDP learning and estimation from several aspects. For learning ... More
Image classification by visual bag-of-words refinement and reductionJan 18 2015This paper presents a new framework for visual bag-of-words (BOW) refinement and reduction to overcome the drawbacks associated with the visual BOW model which has been widely used for image classification. Although very influential in the literature, ... More
Product domains, Multi-Cauchy transforms, and the $\bar \partial$ equationApr 20 2019Solution operators for the equation $\bar \partial u=f$ are constructed on general product domains in $\mathbb{C}^n$. When the factors are one-dimensional, the operator is a simple integral operator: it involves specific derivatives of $f$ integrated ... More
Study on Timing Performance of a Readout Circuit for SiPMJun 07 2018In recent years, SiPM photoelectric devices have drawn much attention in the domain of time-of-flight-based positron emission tomography (TOF-PET). Using them to construct PET detectors with excellent coincidence time resolution (CTR) is always one of ... More
An FPGA Based Fast Linear Discharge Method for Nuclear Pulse DigitizationJun 07 2018Inspired by Wilkinson ADC method, we implement a fast linear discharge method based on FPGA to digitize nuclear pulse signal. In this scheme, we use a constant current source to discharge the charge on capacitor which is integrated by the input current ... More
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDPJan 27 2019A fundamental question in reinforcement learning is whether model-free algorithms are sample efficient. Recently, Jin et al. \cite{jin2018q} proposed a Q-learning algorithm with UCB exploration policy, and proved it has nearly optimal regret bound for ... More
Improved Silbey-Harris polaron ansatz for the spin-boson modelMar 27 2018In this paper, the well-known Silbey-Harris (SH) polaron ansatz for the spin-boson model is improved by adding orthogonal displaced Fock states. The obtained results for the ground state in all baths converge very quickly within finite displaced Fock ... More
Quantum criticality of the sub-Ohmic spin-boson model within displaced Fock statesOct 04 2014The spin-boson model is analytically studied using displaced Fock states (DFS) without discretization of the continuum bath. In the orthogonal displaced Fock basis, the ground-state wavefunction can be systematically improved in a controllable way. Interestingly, ... More
Efficient Private ERM for Smooth ObjectivesMar 29 2017May 24 2017In this paper, we consider efficient differentially private empirical risk minimization from the viewpoint of optimization algorithms. For strongly convex and smooth objectives, we prove that gradient descent with output perturbation not only achieves ... More
Entanglement dynamics of a two-qubit system coupled individually to Ohmic bathsJun 07 2013Aug 08 2013Developed originally for the Holstein polaron, the Davydov D1 ansatz is an efficient, yet extremely accurate trial state for time-dependent variation of the spin-boson model [J. Chem. Phys. 138, 084111 (2013)]. In this work, the Dirac-Frenkel time-dependent ... More
Improving the Generalization of Adversarial Training with Domain AdaptationOct 01 2018Jan 17 2019By injecting adversarial examples into training data, adversarial training is promising for improving the robustness of deep learning models. However, most existing adversarial training approaches are based on a specific type of adversarial attack. It ... More
Quantum phase transitions of the spin-boson model within multi-coherent-statesDec 19 2014A variational approach based on the multi-coherent-state ansatz with asymmetric parameters is employed to study the ground state of the spin-boson model. Without any artificial approximations except for the finite number of the coherent states, we find ... More
A CDG-FE method for the two-dimensional Green-Naghdi model with the enhanced dispersive propertyFeb 15 2019In this work, we investigate numerical solutions of the two-dimensional shallow water wave using a fully nonlinear Green-Naghdi model with an improved dispersive effect. For the purpose of numerics, the Green-Naghdi model is rewritten into a formulation ... More
Multi-scale Orderless Pooling of Deep Convolutional Activation FeaturesMar 07 2014Sep 08 2014Deep convolutional neural networks (CNN) have shown their promise as a universal representation for recognition. However, global CNN activations lack geometric invariance, which limits their robustness for classification and matching of highly variable ... More
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical ViewpointsJul 19 2017Algorithm-dependent generalization error bounds are central to statistical learning theory. A learning algorithm may use a large hypothesis space, but the limited number of iterations controls its model capacity and generalization error. The impacts of ... More
Mimicking the In-Camera Color Pipeline for Camera-Aware Object CompositingMar 27 2019We present a method for compositing virtual objects into a photograph such that the object colors appear to have been processed by the photo's camera imaging pipeline. Compositing in such a camera-aware manner is essential for high realism, and it requires ... More
Weighted Sobolev regularity of the Bergman projection on the Hartogs triangleFeb 15 2015Oct 20 2015We prove a weighted Sobolev estimate of the Bergman projection on the Hartogs triangle, where the weight is some power of the distance to the singularity at the boundary. This method also applies to the $n$-dimensional generalization of the Hartogs triangle. ... More
A Theoretical Analysis of NDCG Type Ranking MeasuresApr 24 2013A central problem in ranking is to design a ranking measure for evaluation of ranking functions. In this paper we study, from a theoretical perspective, the widely used Normalized Discounted Cumulative Gain (NDCG)-type ranking measures. Although there ... More
Weighted Bergman Projection on the Hartogs TriangleOct 22 2014Apr 26 2015We prove the $L^p$ regularity of the weighted Bergman projection on the Hartogs triangle, where the weights are powers of the distance to the singularity at the boundary. The restricted range of $p$ is proved to be sharp. By using a two-weight inequality ... More
FPGA Based Pico-second Time Measurement System for a DIRC-like TOF DetectorJun 07 2018A prototype of DIRC-like Time-of-Flight detector (DTOF), including a pico-second time measurement electronics, is developed and tested preliminarily. The basic structure of DTOF is composed of a fused silica radiator connected to fast micro-channel plate ... More
MedSTS: A Resource for Clinical Semantic Textual SimilarityAug 28 2018The wide adoption of electronic health records (EHRs) has enabled a wide range of applications leveraging EHR data. However, the meaningful use of EHR data largely depends on our ability to efficiently extract and consolidate information embedded in clinical ... More
Learning to Navigate for Fine-grained ClassificationSep 02 2018Fine-grained classification is challenging due to the difficulty of finding discriminative features. Finding those subtle traits that fully characterize the object is not straightforward. To handle this circumstance, we propose a novel self-supervision ... More
The $L^p$ boundedness of the Bergman projection for a class of bounded Hartogs domainsApr 30 2013Jun 08 2015We generalize the Hartogs triangle to a class of bounded Hartogs domains, and we prove that the corresponding Bergman projections are bounded on $L^p$ if and only if $p$ is in the range $(\frac{2n}{n+1},\frac{2n}{n-1})$.
Solution of the two-mode quantum Rabi model using extended squeezed statesDec 30 2014Jul 29 2015The two-mode quantum Rabi model with bilinear coupling is studied using extended squeezed states. We derive $G$-functions for each Bargmann index $q$% . They share a common structure with the $G$-function of the one-photon and two-photon quantum Rabi ... More
On the Depth of Deep Neural Networks: A Theoretical ViewJun 17 2015Nov 28 2015People believe that depth plays an important role in success of deep neural networks (DNN). However, this belief lacks solid theoretical justifications as far as we know. We investigate role of depth from perspective of margin bound. In margin bound, ... More
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence ModelAug 23 2018Existing neural semantic parsers mainly utilize a sequence encoder, i.e., a sequential LSTM, to extract word order features while neglecting other valuable syntactic information such as dependency graph or constituent trees. In this paper, we first propose ... More
Dual Learning for Machine TranslationNov 01 2016While neural machine translation (NMT) is making good progress in the past two years, tens of millions of bilingual sentence pairs are needed for its training. However, human labeling is very costly. To tackle this training data bottleneck, we develop ... More
Fast, Diverse and Accurate Image Captioning Guided By Part-of-SpeechMay 31 2018Apr 11 2019Image captioning is an ambiguous problem, with many suitable captions for an image. To address ambiguity, beam search is the de facto method for sampling multiple captions. However, beam search is computationally expensive and known to produce generic ... More
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same RepresentationOct 28 2018Nov 28 2018It is widely believed that learning good representations is one of the main reasons for the success of deep neural networks. Although highly intuitive, there is a lack of theory and systematic approach quantitatively characterizing what representations ... More
On Low Rank Approximation of Binary MatricesNov 05 2015We consider the problem of low rank approximation of binary matrices. Here we are given a $d \times n$ binary matrix $A$ and a small integer $k < d$. The goal is to find two binary matrices $U$ and $V$ of sizes $d \times k$ and $k \times n$ respectively, ... More
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence ModelsMay 19 2015Sep 19 2016The Flickr30k dataset has become a standard benchmark for sentence-based image description. This paper presents Flickr30k Entities, which augments the 158k captions from Flickr30k with 244k coreference chains, linking mentions of the same entities across ... More
Towards Binary-Valued Gates for Robust LSTM TrainingJun 08 2018Long Short-Term Memory (LSTM) is one of the most widely used recurrent structures in sequence modeling. It aims to use gates to control information flow (e.g., whether to skip some information or not) in the recurrent computations, although its practical ... More
FRAGE: Frequency-Agnostic Word RepresentationSep 18 2018Continuous word representation (aka word embedding) is a basic building block in many neural network-based models used in natural language processing tasks. Although it is widely accepted that words with similar semantics should be close to each other ... More
Generalized Second Price Auction with Probabilistic Broad MatchApr 15 2014Generalized Second Price (GSP) auctions are widely used by search engines today to sell their ad slots. Most search engines have supported broad match between queries and bid keywords when executing GSP auctions, however, it has been revealed that GSP ... More
Can Image-Level Labels Replace Pixel-Level Labels for Image ParsingMar 07 2014Nov 13 2014This paper presents a weakly supervised sparse learning approach to the problem of noisily tagged image parsing, or segmenting all the objects within a noisily tagged image and identifying their categories (i.e. tags). Different from the traditional image ... More
Solutions to the quantum Rabi model with two equivalent qubitsJan 25 2014May 29 2014Using extended coherent states, an analytically exact study has been carried out for the quantum Rabi model with two equivalent qubits. Compact transcendental functions of one variable have been derived leading to exact solutions. The energy spectrum ... More
Randomness in Deconvolutional Networks for Visual RepresentationApr 02 2017Feb 20 2018Toward a deeper understanding on the inner work of deep neural networks, we investigate CNN (convolutional neural network) using DCN (deconvolutional network) and randomization technique, and gain new insights for the intrinsic property of this network ... More
A Comparison of Word Embeddings for the Biomedical Natural Language ProcessingFeb 01 2018Jul 18 2018Word embeddings have been widely used in biomedical Natural Language Processing (NLP) applications as they provide vector representations of words capturing the semantic properties of words and the linguistic relationship between words. Many biomedical ... More
A Deep Representation Empowered Distant Supervision Paradigm for Clinical Information ExtractionApr 20 2018Objective: To automatically create large labeled training datasets and reduce the efforts of feature engineering for training accurate machine learning models for clinical information extraction. Materials and Methods: We propose a distant supervision ... More
Invariant algebraic surfaces of the FitzHugh-Nagumo systemJan 04 2017In this paper, we characterize all the irreducible Darboux polynomials and polynomial first integrals of FitzHugh-Nagumo (F-N) system. The method of the weight homogeneous polynomials and the characteristic curves is widely used to give a complete classification ... More
Magnetic miniband and magnetotransport property of a graphene superlatticeMar 30 2010Apr 04 2010The eigen energy and the conductivity of a graphene sheet subject to a one-dimensional cosinusoidal potential and in the presence of a magnetic field are calculated. Such a graphene superlattice presents three distinct magnetic miniband structures as ... More
On the translates of general dyadic systems on $\R$Sep 04 2018Many techniques in harmonic analysis use the fact that a continuous object can be written as a sum (or an intersection) of dyadic counterparts, as long as those counterparts belong to a distinct dyadic system. Here we generalize the notion of distinct ... More
Improving Aviation Safety using Synthetic Vision System integrated with Eye-tracking DevicesMar 07 2018By collecting the data of eyeball movement of pilots, it is possible to monitor pilot's operation in the future flight in order to detect potential accidents. In this paper, we designed a novel SVS system that is integrated with an eye tracking device, ... More
Sub-Ohmic spin-boson model with off-diagonal coupling: Ground state propertiesOct 06 2013We have carried out analytical and numerical studies of the spin-boson model in the sub-ohmic regime with the influence of both the diagonal and off-diagonal coupling accounted for via the Davydov D1 variational ansatz. While a second-order phase transition ... More
Photoresponse in large area multi-walled carbon nanotube/polymer nanocomposite filmsDec 28 2008We present a near IR photoresponse study of large area multi-walled carbon nanotube/poly(3-hexylthiophene)-block-polystyrene polymer (MWNT/P3HT-b-PS) nanocomposite films for different loading ratio of MWNT into the polymer matrix. We show that the photocurrent ... More
Inaudible Voice CommandsAug 24 2017Voice assistants like Siri enable us to control IoT devices conveniently with voice commands, however, they also provide new attack opportunities for adversaries. Previous papers attack voice assistants with obfuscated voice commands by leveraging the ... More
On the Inequalities of Projected Volumes and the Constructible RegionOct 31 2014Dec 08 2018We study the following geometry problem: given a $2^n-1$ dimensional vector $\pi=\{\pi_S\}_{S\subseteq [n], S\ne \emptyset}$, is there an object $T\subseteq\mathbb{R}^n$ such that $\log(\mathsf{vol}(T_S))= \pi_S$, for all $S\subseteq [n]$, where $T_S$ ... More
Analysis of the Fourier series Dirichlet-to-Neumann boundary condition of the Helmholtz equation and its application to finite element methodsSep 02 2016Feb 11 2019It is well known that the Fourier series Dirichlet-to-Neumann (DtN) boundary condition can be used to solve the Helmholtz equation in unbounded domains. In this work, applying such DtN boundary condition and using the finite element method, we solve and ... More
A solution operator for $\bar\partial$ on the Hartogs triangle and $L^p$ estimatesOct 12 2017Sep 20 2018An integral solution operator for $\bar\partial$ is constructed on product domains that include the punctured bidisc. This operator is shown to satisfy $L^p$ estimates for all $1\leq p <\infty$, though with non-standard -- relative to strongly pseudoconvex ... More
A priori error estimates of the DtN-FEM: fluid-solid interaction problemsSep 02 2016We consider the finite element method solving a fluid-solid interaction (FSI) problem in two dimensions. The original problem is reduced to an equivalent nonlocal boundary value problem through an exact Dirichlet-to-Neumann (DtN) mapping defined on an ... More
The Optimal Size of Stochastic Hodgkin-Huxley Neuronal Systems for Maximal Energy Efficiency in Coding of Pulse SignalsAug 17 2013The generation and conduction of action potentials represents a fundamental means of communication in the nervous system, and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in a process of transfer ... More
Construction of Directed Strongly Regular Graphs as Generalized Cayley GraphsOct 05 2014Dec 23 2014Directed strongly regular graphs were introduced by Duval in 1998 as one of the possible generalization of classical strongly regular graphs to the directed case. Duval also provided several construction methods for directed strongly regular graphs. In ... More
A high order discontinuous Galerkin method for the coupled Maxwell and gas dynamic modelFeb 26 2019It is known that both linear and nonlinear optical phenomena can be produced as metallic nanostructures are excited by external electromagnetic waves. In this paper, we are interested in the nonlocal effects and the high order harmonic generations. To ... More
Smoothing Properties of the Friedrichs Operator on $L^p$ spacesSep 01 2017Dec 16 2017We show that the Friedrichs operator exhibits smoothing properties in the $L^p$ scale. In particular we prove that on any smoothly bounded pseudoconvex domain the Friedrichs operator maps $A^2(\Omega)$ to $A^p(\Omega)$ for some $p>2$.
Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamicsFeb 24 2018This interdisciplinary study, which combines machine learning, statistical methodologies, high-fidelity simulations, and flow physics, demonstrates a new process for building an efficient surrogate model for predicting spatiotemporally evolving flow dynamics. ... More
Data-Driven Analysis and Common Proper Orthogonal Decomposition (CPOD)-Based Spatio-Temporal Emulator for Design ExplorationJul 26 2017The present study proposes a data-driven framework trained with high-fidelity simulation results to facilitate decision making for combustor designs. At its core is a surrogate model employing a machine-learning technique called kriging, which is combined ... More
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four MinutesJul 30 2018Synchronized stochastic gradient descent (SGD) optimizers with data parallelism are widely used in training large-scale deep neural networks. Although using larger mini-batch sizes can improve the system scalability by reducing the communication-to-computation ... More
Weighted Bergman Projections on the Hartogs Triangle: Exponential DecayOct 27 2016We study weighted Bergman projections on the Hartogs triangle in $\mathbb{C}^2$. We show that projections corresponding to exponentially vanishing weights have degenerate $L^p$ mapping properties.
Solutions to the anisotropic quantum Rabi modelFeb 02 2015In this work, the anisotropic quantum Rabi model with different coupling strengths of the rotating-wave and counter-rotating wave terms is studied by using two kinds of extended coherent states (ECS). By the first kind of ECS, we can derive a so-called ... More
Boundary integral equation methods for the elastic and thermoelastic waves in three dimensionsFeb 11 2019In this paper, we consider the boundary integral equation (BIE) method for solving the exterior Neumann boundary value problems of elastic and thermoelastic waves in three dimensions based on the Fredholm integral equations of the first kind. The innovative ... More
The Rate of Convergence of the Augmented Lagrangian Method for a Nonlinear Semidefinite Nuclear Norm Composite Optimization ProblemSep 02 2017We propose two basic assumptions, under which the rate of convergence of the augmented Lagrange method for a class of composite optimization problems is estimated. We analyze the rate of local convergence of the augmented Lagrangian method for a nonlinear ... More
A Linearly Convergent Majorized ADMM with Indefinite Proximal Terms for Convex Composite Programming and Its ApplicationsJun 06 2017Feb 07 2018This paper aims to study a majorized alternating direction method of multipliers with indefinite proximal terms (iPADMM) for convex composite optimization problems. We show that the majorized iPADMM for 2-block convex optimization problems converges globally ... More
Regrets of an Online Alternating Direction Method of Multipliers for Online Composite OptimizationApr 05 2019In this paper, we investigate regrets of an online semi-proximal alternating direction method of multiplier (Online-spADMM) for solving online linearly constrained convex composite optimization problems. Under mild conditions, we establish ${\rm O}(\sqrt{N})$ ... More
An accurate boundary element method for the exterior elastic scattering problem in two dimensionsAug 31 2016This paper is concerned with a Galerkin boundary element method solving the two dimensional exterior elastic wave scattering problem. The original problem is first reduced to the so-called Burton-Miller (\cite{BM71}) boundary integral formulation, and ... More
Continuous Behavioural Function Equilibria and Approximation Schemes in Bayesian Games with Non-Finite Type and Action SpacesOct 13 2017Meirowitz [17] showed existence of continuous behavioural function equilibria for Bayesian games with non-finite type and action spaces. A key condition for the proof of the existence result is equi-continuity of behavioural functions which, according ... More
A Bounded Formulation for The School Bus Scheduling ProblemMar 24 2018This paper proposes a new formulation for the school bus scheduling problem (SBSP) which optimizes starting times for schools and associated bus routes to minimize transportation cost. Specifically, the problem determines the minimum number of buses required ... More
An effect of large permanent charge: Decreasing flux to zero with increasing transmembrane potential to infinityDec 12 2017In this work, we examine effects of large permanent charges on ionic flow through ion channels based on a quasi-one dimensional Poisson-Nernst-Planck model. It turns out large positive permanent charges inhibit the flux of cation as expected, but strikingly, ... More
$L^p$ regularity of the Bergman Projection on domains covered by the polydiskMar 25 2019If a bounded domain can be covered by the polydisk through a rational proper holomorphic map, then the Bergman projection is $L^p$-bounded for $p$ in a certain range depending on the ramified rational covering. This result can be applied to the symmetrized ... More
An accurate boundary element method for the exterior elastic scattering problem in two dimensionsAug 31 2016Aug 14 2017This paper is concerned with a Galerkin boundary element method solving the two dimensional exterior elastic wave scattering problem. The original problem is first reduced to the so-called Burton-Miller (\cite{BM71}) boundary integral formulation, and ... More
Smoothing SQP methods for solving degenerate nonsmooth constrained optimization problems with applications to bilevel programsMar 07 2014Jun 03 2014We consider a degenerate nonsmooth and nonconvex optimization problem for which the standard constraint qualification such as the generalized Mangasarian Fromovitz constraint qualification (GMFCQ) may not hold. We use smoothing functions with the gradient ... More
On the Inequalities of Projected Volumes and the Constructible RegionOct 31 2014We study the following geometry problem: given a $2^n-1$ dimensional vector $\pi=\{\pi_S\}_{S\subseteq [n], S\ne \emptyset}$, is there an object $T\subseteq\mathbb{R}^n$ such that $\log(\mathsf{vol}(T_S))= \pi_S$, for all $S\subseteq [n]$, where $T_S$ ... More
SQL-Rank: A Listwise Approach to Collaborative RankingFeb 28 2018Feb 06 2019In this paper, we propose a listwise approach for constructing user-specific rankings in recommendation systems in a collaborative fashion. We contrast the listwise approach to previous pointwise and pairwise approaches, which are based on treating either ... More
Linear Rate Convergence of the Alternating Direction Method of Multipliers for Convex Composite Quadratic and Semi-Definite ProgrammingAug 10 2015In this paper, we aim to provide a comprehensive analysis on the linear rate convergence of the alternating direction method of multipliers (ADMM) for solving linearly constrained convex composite optimization problems. Under a certain error bound condition, ... More
Weighted integral solvers for elastic scattering by open arcs in two dimensionsFeb 22 2019We present a novel approach for the numerical solution of problems of elastic scattering by open arcs in two dimensions. Our methodology relies on the composition of weighted versions of the classical operators associated with Dirichlet and Neumann boundary ... More
Concise analytic solutions to the quantum Rabi model with two arbitrary qubitsMay 03 2014Mar 14 2015Using extended coherent states, an analytical exact study has been carried out for the quantum Rabi model (QRM) with two arbitrary qubits in a very concise way. The $G$-functions with $2 \times 2$ determinants are generally derived. For the same coupling ... More
Characterization of the Robust Isolated Calmness for a Class of Conic Programming ProblemsJan 27 2016Oct 01 2016This paper is devoted to studying the robust isolated calmness of the Karush-Kuhn-Tucker (KKT) solution mapping for a large class of interesting conic programming problems (including most commonly known ones arising from applications) at a locally optimal ... More
Let the Cloud Watch Over Your IoT File SystemsFeb 17 2019Smart devices produce security-sensitive data and keep them in on-device storage for persistence. The current storage stack on smart devices, however, offers weak security guarantees: not only because the stack depends on a vulnerable commodity OS, but ... More
A hybridizable discontinuous Galerkin method for the quad-curl problemFeb 22 2019The quad-curl problem arises in magnetohydrodynamics, inverse electromagnetic scattering and transform eigenvalue problems. In this paper we investigate a hybridizable discontinuous Galerkin method to solve the quad-curl problem based on a mixed formulation. ... More
Analysis of a hybridizable discontinuous Galerkin method for the Maxwell operatorMay 23 2018Mar 10 2019In this paper, we study a hybridizable discontinuous Galerkin (HDG) method for the Maxwell operator. The only global unknowns are defined on the inter-element boundaries, and the numerical solutions are obtained by using discontinuous polynomial approximations. ... More
Boundary integral equation methods for the two dimensional fluid-solid interaction problemDec 22 2015Aug 31 2016This paper is concerned with boundary integral equation methods for solving the two-dimensional fluid-solid interaction problem. We reduce the problem to three differential systems of boundary integral equations via direct and indirect approaches. Existence ... More