arXiv subjects

Yun Li

Publications and source records attributed to Yun Li.

At least 181 records · Page 10Linked to original sources

arXiv2020

Matching methods for obtaining survival functions to estimate the effect of a time-dependent treatment

In observational studies of survival time featuring a binary time-dependent treatment, the hazard ratio (an instantaneous measure) is often used to represent the treatment effect. However, investigators are often more interested in the difference in survival functions. We propose semiparametric methods to estimate the causal effect of treatment among the treated with respect to survival probability. The objective is to compare post-treatment survival with the survival function that would have been observed in the absence of treatment. For each patient, we compute a prognostic score (based on the pre-treatment death hazard) and a propensity score (based on the treatment hazard). Each treated patient is then matched with an alive, uncensored and not-yet-treated patient with similar prognostic and/or propensity scores. The experience of each treated and matched patient is weighted using a variant of Inverse Probability of Censoring Weighting to account for the impact of censoring. We propose estimators of the treatment-specific survival functions (and their difference), computed through weighted Nelson-Aalen estimators. Closed-form variance estimators are proposed which take into consideration the potential replication of subjects across matched sets. The proposed methods are evaluated through simulation, then applied to estimate the effect of kidney transplantation on survival among end-stage renal disease patients using data from a national organ failure registry.

stat.ME↗

arXiv2020

The Impact of Unmeasured Within- and Between-Cluster Confounding on the Bias of Effect Estimators from Fixed Effect, Mixed effect and Instrumental Variable Models

Instrumental variable methods are popular choices in combating unmeasured confounding to obtain less biased effect estimates. However, we demonstrate that alternative methods may give less biased estimates depending on the nature of unmeasured confounding. Treatment preferences of clusters (e.g., physician practices) are the most f6requently used instruments in instrumental variable analyses (IVA). These preference-based IVAs are usually conducted on data clustered by region, hospital/facility, or physician, where unmeasured confounding often occurs within or between clusters. We aim to quantify the impact of unmeasured confounding on the bias of effect estimators in IVA, as well as alternative methods including ordinary least squares regression, linear mixed models (LMM) and fixed effect models (FE) to study the effect of a continuous exposure (e.g., treatment dose). We derive bias formulae of estimators from these four methods in the presence of unmeasured within- and/or between-cluster confounders. We show that IVAs can provide consistent estimates when unmeasured within-cluster confounding exists, but not when between-cluster confounding exists. On the other hand, FEs and LMMs can provide consistent estimates when unmeasured between-cluster confounding exits, but not for within-cluster confounding. Whether IVAs are advantageous in reducing bias over FEs and LMMs depends on the extent of unmeasured within-cluster confounding relative to between-cluster confounding. Furthermore, the impact of unmeasured between-cluster confounding on IVA estimates is larger than the impact of unmeasured within-cluster confounding on FE and LMM estimates. We illustrate these methods through data applications. Our findings provide guidance for choosing appropriate methods to combat the dominant types of unmeasured confounders and help interpret statistical results in the context of unmeasured confounding

stat.ME↗

arXiv2020

Agglomerative Neural Networks for Multi-view Clustering

Conventional multi-view clustering methods seek for a view consensus through minimizing the pairwise discrepancy between the consensus and subviews. However, the pairwise comparison cannot portray the inter-view relationship precisely if some of the subviews can be further agglomerated. To address the above challenge, we propose the agglomerative analysis to approximate the optimal consensus view, thereby describing the subview relationship within a view structure. We present Agglomerative Neural Network (ANN) based on Constrained Laplacian Rank to cluster multi-view data directly while avoiding a dedicated postprocessing step (e.g., using K-means). We further extend ANN with learnable data space to handle data of complex scenarios. Our evaluations against several state-of-the-art multi-view clustering approaches on four popular datasets show the promising view-consensus analysis ability of ANN. We further demonstrate ANN's capability in analyzing complex view structures and extensibility in our case study and explain its robustness and effectiveness of data-driven modifications.

cs.LG↗

arXiv2020

Taking the pulse of COVID-19: A spatiotemporal perspective

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.

physics.soc-ph↗

arXiv2020

Conductive Domain Walls in Non-Oxide Ferroelectrics Sn2P2S6

The conductive domain wall (CDW) is extensively investigated in ferroelectrics, which can be considered as a quasi-two-dimensional reconfigurable conducting channel embedded into an insulating material. Therefore, it is highly important for the application of ferroelectric nanoelectronics. Hitherto, most CDW investigations are restricted in oxides, and limited work has been reported in non-oxides to the contrary. Here, by successfully synthesizing the non-oxide ferroelectric Sn2P2S6 single crystal, we observed and confirmed the domain wall conductivity by using different scanning probe techniques which origins from the nature of inclined domain walls. Moreover, the domains separated by CDW also exhibit distinguishable electrical conductivity due to the interfacial polarization charge with opposite signs. The result provides a novel platform for understanding electrical conductivity behavior of the domains and domain walls in non-oxide ferroelectrics.

cond-mat.mtrl-sci↗

arXiv2020

Operator level hard-to-soft transition for $β$-ensembles

The soft and hard edge scaling limits of $β$-ensembles can be characterized as the spectra of certain random Sturm-Liouville operators. It has been shown that by tuning the parameter of the hard edge process one can obtain the soft edge process as a scaling limit. We prove that this limit can be realized on the level of the corresponding random operators. More precisely, the random operators can be coupled in a way so that the scaled versions of the hard edge operators converge to the soft edge operator a.s. in the norm resolvent sense.

math.PR↗

arXiv2019

Bound state and non-Markovian dynamics of a quantum emitter around a surface plasmonic nanostructure

A bound state between a quantum emitter (QE) and surface plasmon polaritons (SPPs) can be formed, where the QE is partially stabilized in its excited state. We put forward a general approach for calculating the energy level shift at a negative frequency $ω$, which is just the negative of the nonresonant part for the energy level shift at positive frequency $-ω$. We also propose an efficient formalism for obtaining the long-time value of the excited-state population without calculating the eigenfrequency of the bound state or performing a time evolution of the system, in which the probability amplitude for the excited state in the steady limit is equal to one minus the integral of the evolution spectrum over the positive frequency range. With the above two quantities obtained, we show that the non-Markovian decay dynamics in the presence of a bound state can be obtained by the method based on the Green's function expression for the evolution operator. A general criterion for identifying the existence of a bound state is presented. These are numerically demonstrated for a QE located around a nanosphere and in a gap plasmonic nanocavity. These findings are instructive in the fields of coherent light-matter interactions.

cond-mat.mes-hall↗

arXiv2019

A simple and effective postprocessing method for image classification

Whether it is computer vision, natural language processing or speech recognition, the essence of these applications is to obtain powerful feature representations that make downstream applications completion more efficient. Taking image recognition as an example, whether it is hand-crafted low-level feature representation or feature representation extracted by a convolutional neural networks(CNNs), the goal is to extract features that better represent image features, thereby improving classification accuracy. However, we observed that image feature representations share a large common vector and a few top dominating directions. To address this problems, we propose a simple but effective postprocessing method to render off-the-shelf feature representations even stronger by eliminating the common mean vector from off-the-shelf feature representations. The postprocessing is empirically validated on a variety of datasets and feature extraction methods.such as VGG, LBP, and HOG. Some experiments show that the features that have been post-processed by postprocessing algorithm can get better results than original ones.

cs.CV↗

arXiv2019

On the Capacity Region of Broadcast Packet Erasure Relay Networks With Feedback

We derive a new outer bound on the capacity region of broadcast traffic in multiple input broadcast packet erasure channels with feedback, and extend this outer bound to packet erasure relay networks with feedback. We show the tightness of the outer bound for various classes of networks. An important engineering implication of this work is that for network coding schemes for parallel broadcast channels, the `xor' packets should be sent over correlated broadcast subchannels.

cs.IT↗

arXiv2019

Exploring Communities in Large Profiled Graphs

Given a graph $G$ and a vertex $q\in G$, the community search (CS) problem aims to efficiently find a subgraph of $G$ whose vertices are closely related to $q$. Communities are prevalent in social and biological networks, and can be used in product advertisement and social event recommendation. In this paper, we study profiled community search (PCS), where CS is performed on a profiled graph. This is a graph in which each vertex has labels arranged in a hierarchical manner. Extensive experiments show that PCS can identify communities with themes that are common to their vertices, and is more effective than existing CS approaches. As a naive solution for PCS is highly expensive, we have also developed a tree index, which facilitate efficient and online solutions for PCS.

cs.DB↗

arXiv2018

Chirality-dependent electromagnetically induced transparency based on a double semi-periodic helix metastructure

A chiral metastructure composed of spatially separated double semi-periodic helices is proposed and investigated theoretically and experimentally in this Letter. Chirality-dependent electromagnetically induced transparency (EIT) and a slow light effect in the microwave region are observed from a numerical parameter study, while experimental results from the 3D printing sample yield good agreement with the theoretical findings. The studied EIT phenomenon arises as a result of destructive interference by coupled resonances, and the proposed chiral metastructure can be applied in areas such as polarization communication, pump-probe characterization, and quantum computing areas.

physics.class-ph↗

arXiv2018

STTM: A Tool for Short Text Topic Modeling

Along with the emergence and popularity of social communications on the Internet, topic discovery from short texts becomes fundamental to many applications that require semantic understanding of textual content. As a rising research field, short text topic modeling presents a new and complementary algorithmic methodology to supplement regular text topic modeling, especially targets to limited word co-occurrence information in short texts. This paper presents the first comprehensive open-source package, called STTM, for use in Java that integrates the state-of-the-art models of short text topic modeling algorithms, benchmark datasets, and abundant functions for model inference and evaluation. The package is designed to facilitate the expansion of new methods in this research field and make evaluations between the new approaches and existing ones accessible. STTM is open-sourced at https://github.com/qiang2100/STTM.

cs.IR↗

arXiv2018

Quantum depletion and superfluid density of a supersolid in Raman spin-orbit coupled Bose gases

We theoretically investigate a three-dimensional weakly interacting Bose gas with one-dimensional Raman-type spin-orbit coupling at zero temperature. By employing an improved ansatz, including high-order harmonics in the stripe phase, we show that the critical transition from the stripe to the plane-wave phases is shifted to a relatively larger Rabi frequency compared to the prediction by previous work [Li $\textit{et al.}$, Phys. Rev. Lett. $\textbf{108}$, 225301 (2012)] using a first-order stripe ansatz. We also determine the quantum depletion and superfluid density over a large range of Rabi frequency in different phases. The depletion exhibits an intriguing behavior with a discontinuous jump at the transition between the stripe and plane-wave phases, and a maximum at the transition between the plane-wave and zero-momentum phases. The superfluid density is derived through a phase-twist method. In the plane-wave and zero-momentum phases, it is significantly suppressed along the spin-orbit-coupling direction and vanishes at the transition, consistent with a recent work [Zhang $\textit{et al.}$, Phys. Rev. A $\textbf{94}$, 033635 (2016)], while in the stripe phase, it smoothly decreases with increasing Rabi frequency. Our predictions would be useful for further theoretical and experimental studies of the exotic supersolid stripe phase.

cond-mat.quant-gas↗

arXiv2018

Constructions of Augmented Orthogonal Arrays

Augmented orthogonal arrays (AOAs) were introduced by Stinson, who showed the equivalence between ideal ramp schemes and augmented orthogonal arrays (Discrete Math. 341 (2018), 299-307). In this paper, we show that there is an AOA$(s,t,k,v)$ if and only if there is an OA$(t,k,v)$ which can be partitioned into $v^{t-s}$ subarrays, each being an OA$(s,k,v)$, and that there is a linear AOA$(s,t,k,q)$ if and only if there is a linear maximum distance separable (MDS) code of length $k$ and dimension $t$ over $\mathbb{F}_q$ which contains a linear MDS subcode of length $k$ and dimension $s$ over $\mathbb{F}_q$. Some constructions for AOAs and some new infinite classes of AOAs are also given.

math.CO↗

arXiv2018

Simplex Search Based Brain Storm Optimization

Through modeling human's brainstorming process, the brain storm optimization (BSO) algorithm has become a promising population-based evolutionary algorithm. However, BSO is pointed out that it possesses a degenerated L-curve phenomenon, i.e., it often gets near optimum quickly but needs much more cost to improve the accuracy. To overcome this question in this paper, an excellent direct search based local solver, the Nelder-Mead Simplex (NMS) method is adopted in BSO. Through combining BSO's exploration ability and NMS's exploitation ability together, a simplex search based BSO (Simplex-BSO) is developed via a better balance between global exploration and local exploitation. Simplex-BSO is shown to be able to eliminate the degenerated L-curve phenomenon on unimodal functions, and alleviate significantly this phenomenon on multimodal functions. Large number of experimental results show that Simplex-BSO is a promising algorithm for global optimization problems.

cs.NE↗

arXiv2018

Controlled Tracking in Urban Terrain: Closing the Loop

We investigate the challenging problem of integrating detection, signal processing, target tracking, and adaptive waveform scheduling with lookahead in urban terrain. We propose a closed-loop active sensing system to address this problem by exploiting three distinct levels of diversity: (1) spatial diversity through the use of coordinated multistatic radars; (2) waveform diversity by adaptively scheduling the transmitted waveform; and (3) motion model diversity by using a bank of parallel filters matched to different motion models. Specifically, at every radar scan, the waveform that yields the minimum trace of the one-step-ahead error covariance matrix is transmitted; the received signal goes through a matched-filter, and curve fitting is used to extract range and range-rate measurements that feed the LMIPDA-VSIMM algorithm for data association and filtering. Monte Carlo simulations demonstrate the effectiveness of the proposed system in an urban scenario contaminated by dense and uneven clutter, strong multipath, and limited line-of-sight.

eess.SP↗

arXiv2018

Inevitable high density of oxygen vacancies on the surface of LaAlO3/SrTiO3 heterostructures

Using density-functional-theory (DFT) calculations with the HSE06 hybrid functional, we accurately evaluate the critical thickness of LaAlO3 film for the intrinsic doping in LaAlO3/SrTiO3 (LAO/STO) heterstructures. The calculated critical thickness of 6 unit-cell (uc) layers suggests to rule out the intrinsic doping mechanism. We also calculate the density of oxygen vacancies on the LAO surface at varying LAO thicknesses, preparation oxygen pressures and temperatures by using the condition of chemical equilibrium and DFT calculations. We find that once LAO thickness >=3 uc high-density (~ 10^14 cm^-2 ) oxygen vacancies will inevitably exist on the LAO surface of the LAO/STO heterstructures even though the samples are grown under high oxygen pressure. The oxygen vacancies are stabilized by releasing the electrostatic energy in the LAO film.

cond-mat.mtrl-sci↗

arXiv2017

Chern insulators without band inversion in MoS2 monolayers with 3d adatoms

Electronic and topological properties of MoS2 monolayers endowed with 3d transition metal (TM) adatoms (V-Fe) are explored by using ab initio methods and k.p models. Without the consideration of the Hubbard U interaction, the V, Cr, and Fe adatoms tend to locate on the top of the Mo atoms, while the most stable site for the Mn atom is at the hollow position of the Mo-S hexagon. After the Hubbard U is applied, the most stable sites of all the systems become the top of the Mo atoms. Chern insulators without band inversion are achieved in these systems. The V and Fe adsorption systems are the best candidates to produce the topological states. The k.p model calculations indicate that these topological states are determined by the TM magnetism, the C3v crystal field from the MoS2 substrate, and the TM atomic spin-orbit coupling (SOC). The special two-meron pseudospin texture is found to contribute to the topology. The apparent difference between the Berry curvatures for the V and Fe adsorption systems are also explored. Our results widen the understanding to the Chern insulators and are helpful for the applications of the MoS2 monolayers in the future electronics and spintronics.

cond-mat.mtrl-sci↗