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Min Yang

Publications and source records attributed to Min Yang.

At least 343 records · Page 19Linked to original sources
arXiv2018

GPSP: Graph Partition and Space Projection based Approach for Heterogeneous Network Embedding

In this paper, we propose GPSP, a novel Graph Partition and Space Projection based approach, to learn the representation of a heterogeneous network that consists of multiple types of nodes and links. Concretely, we first partition the heterogeneous network into homogeneous and bipartite subnetworks. Then, the projective relations hidden in bipartite subnetworks are extracted by learning the projective embedding vectors. Finally, we concatenate the projective vectors from bipartite subnetworks with the ones learned from homogeneous subnetworks to form the final representation of the heterogeneous network. Extensive experiments are conducted on a real-life dataset. The results demonstrate that GPSP outperforms the state-of-the-art baselines in two key network mining tasks: node classification and clustering.

cs.SI↗
arXiv2017

Generative Adversarial Network for Abstractive Text Summarization

In this paper, we propose an adversarial process for abstractive text summarization, in which we simultaneously train a generative model G and a discriminative model D. In particular, we build the generator G as an agent of reinforcement learning, which takes the raw text as input and predicts the abstractive summarization. We also build a discriminator which attempts to distinguish the generated summary from the ground truth summary. Extensive experiments demonstrate that our model achieves competitive ROUGE scores with the state-of-the-art methods on CNN/Daily Mail dataset. Qualitatively, we show that our model is able to generate more abstractive, readable and diverse summaries.

cs.CL↗
arXiv2017

Information-Based Optimal Subdata Selection for Big Data Linear Regression

Extraordinary amounts of data are being produced in many branches of science. Proven statistical methods are no longer applicable with extraordinary large data sets due to computational limitations. A critical step in big data analysis is data reduction. Existing investigations in the context of linear regression focus on subsampling-based methods. However, not only is this approach prone to sampling errors, it also leads to a covariance matrix of the estimators that is typically bounded from below by a term that is of the order of the inverse of the subdata size. We propose a novel approach, termed information-based optimal subdata selection (IBOSS). Compared to leading existing subdata methods, the IBOSS approach has the following advantages: (i) it is significantly faster; (ii) it is suitable for distributed parallel computing; (iii) the variances of the slope parameter estimators converge to 0 as the full data size increases even if the subdata size is fixed, i.e., the convergence rate depends on the full data size; (iv) data analysis for IBOSS subdata is straightforward and the sampling distribution of an IBOSS estimator is easy to assess. Theoretical results and extensive simulations demonstrate that the IBOSS approach is superior to subsampling-based methods, sometimes by orders of magnitude. The advantages of the new approach are also illustrated through analysis of real data.

stat.ME↗
arXiv2017

Load Balancing using Hilbert Space-filling Curves for Parallel Reservoir Simulations

The goal of load balancing (grid partitioning) is to minimize overall computations and communications, and to make sure that all processors have a similar workload. Geometric methods divide a grid by using a location of a cell while topological methods work with connectivity of cells, which is generally described as a graph. This paper introduces a Hilbert space-filling curve method. A space-filling curve is a continuous curve and defines a map between a one-dimensional space and a multi-dimensional space. A Hilbert space-filling curve is one special space-filling curve discovered by Hilbert and has many useful characteristics, such as good locality, which means that two objects that are close to each other in a multi-dimensional space are also close to each other in a one dimensional space. This property can model communications in grid-based parallel applications. The idea of the Hilbert space-filling curve method is to map a computational domain into a one-dimensional space, partition the one-dimensional space to certain intervals, and assign all cells in a same interval to a MPI. To implement a load balancing method, a mapping kernel is required to convert high-dimensional coordinates to a scalar value and an efficient one-dimensional partitioning module that divides a one-dimensional space and makes sure that all intervals have a similar workload. The Hilbert space-filling curve method is compared with ParMETIS, a famous graph partitioning package. The results show that our Hilbert space-filling curve method has good partition quality. It has been applied to grids with billions of cells, and linear scalability has been obtained on IBM Blue Gene/Q.

cs.DC↗
arXiv2017

A Hybrid Data Association Framework for Robust Online Multi-Object Tracking

Global optimization algorithms have shown impressive performance in data-association based multi-object tracking, but handling online data remains a difficult hurdle to overcome. In this paper, we present a hybrid data association framework with a min-cost multi-commodity network flow for robust online multi-object tracking. We build local target-specific models interleaved with global optimization of the optimal data association over multiple video frames. More specifically, in the min-cost multi-commodity network flow, the target-specific similarities are online learned to enforce the local consistency for reducing the complexity of the global data association. Meanwhile, the global data association taking multiple video frames into account alleviates irrecoverable errors caused by the local data association between adjacent frames. To ensure the efficiency of online tracking, we give an efficient near-optimal solution to the proposed min-cost multi-commodity flow problem, and provide the empirical proof of its sub-optimality. The comprehensive experiments on real data demonstrate the superior tracking performance of our approach in various challenging situations.

cs.CV↗
arXiv2016

Context-aware System Service Call-oriented Symbolic Execution of Android Framework with Application to Exploit Generation

Android Framework is a layer of software that exists in every Android system managing resources of all Android apps. A vulnerability in Android Framework can lead to severe hacks, such as destroying user data and leaking private information. With tens of millions of Android devices unpatched due to Android fragmentation, vulnerabilities in Android Framework certainly attract attackers to exploit them. So far, enormous manual effort is needed to craft such exploits. To our knowledge, no research has been done on automatic generation of exploits that take advantage of Android Framework vulnerabilities. We make a first step towards this goal by applying symbolic execution of Android Framework to finding bugs and generating exploits. Several challenges have been raised by the task. (1) The information of an app flows to Android Framework in multiple intricate steps, making it difficult to identify symbolic inputs. (2) Android Framework has a complex initialization phase, which exacerbates the state space explosion problem. (3) A straightforward design that builds the symbolic executor as a layer inside the Android system will not work well: not only does the implementation have to ensure the compatibility with the Android system, but it needs to be maintained whenever Android gets updated. We present novel ideas and techniques to resolve the challenges, and have built the first system for symbolic execution of Android Framework. It fundamentally changes the state of the art in exploit generation on the Android system, and has been applied to constructing new techniques for finding vulnerabilities.

cs.CR↗
arXiv2016

Self-ordered Mo-oxide Nanotube Arrays as Precursor for Aligned MoOx/MoS2 Core-Shell Nanotubular Structures with a High Density of Reactive Sites

In the present work we demonstrate the self-organized formation of anodic Mo-oxide nanotube arrays grown on a Mo sheet under suitable electrochemical conditions in glycerol/NH4F electrolytes. The resulting amorphous tubes can be crystallized by annealing to MoO2 or MoO3. The tube walls then can be further sulfurized fully or partially to Mo-sulfide to form well-ordered arrays of vertically aligned MoOx/MoS2 nanotubes. Under optimized conditions, defined MoS2 sheets form on the oxide walls in a layer by layer low angle zig-zag arrangement that provide a high density of reactive stacking faults. These core-shell nanotube arrays, consisting of tubes with a conductive suboxide core and a functional high defect density MoS2 coating, are highly promising for applications such as electrocatalysis (hydrogen evolution) or ion insertion devices.

cond-mat.mtrl-sci↗
arXiv2016

Acoustic Coherent Perfect Absorbers as Sensitive Null Detectors

We report the experimental realization of acoustic coherent perfect absorption (CPA) of four symmetric scatterers of very different structures. The only conditions necessary for these scatterers to exhibit CPA are that both the reflection and transmission amplitudes of the scatterers are 0.5 under one incident wave, and there are two collinear and counter-propagating incident waves with appropriate relative amplitude and phase. Nearly 1000 times in the modulation of output power has been demonstrated by changing the relative phase of the incident waves over 180°. We further demonstrate that these scatterers are sensitive devices to detect the small differences between two nearly equal incident waves. A 27 % change in the strength of the scattering wave has been demonstrated for every degree of phase deviation from the optimum condition between the incident waves.

physics.class-ph↗
arXiv2016

Hybrid membrane resonators for multiple frequency asymmetric absorption and reflection in large waveguide

We report that Hybrid membrane resonators (HMRs) made of a decorated membrane resonator backed by a shallow cavity can function as Helmholtz resonators (HRs) when mounted on the sidewall of a clear waveguide for air ventilation. When two single-frequency HMRs are used in the same scheme as two frequency-detuned HRs, asymmetric total absorption/reflection is demonstrated at 286.7 Hz with absorption coefficient over 97 % in a waveguide 9 cm x 9 cm in cross section. When two multiple-frequency HMRs are used, absorption in the range of near 60 % to above 80 % is observed at 403 Hz, 450 Hz, 688 Hz, 863 Hz and 945 Hz. Theoretical predictions agree well with the experimental data. The HMRs may replace HRs in duct noise reduction applications in that at a single operation frequency they have stronger strength to cover a much larger cross section area than that of HRs with similar cavity volume, and they can be designed to provide multiple frequency absorption band.

physics.class-ph↗
arXiv2016

Optimal Sound Absorbing Structures

Causal nature of the acoustic response, for any materials or structures, dictates an inequality that relates the absorption spectrum of the sample to its thickness. We present a general recipe for constructing sound-absorbing structures that can attain near-equality for the causal relation with very high absorption performance; such structures are denoted optimal. Our strategy involves using carefully designed acoustic metamaterials as backing to a thin layer of conventional sound absorbing material, e.g., acoustic sponge. By using this design approach, we have realized a 12 cm-thick structure that exhibits broadband, near-perfect flat absorption spectrum starting at around 400 Hz. From the causal relation, the calculated minimum sample thickness is 11.5 cm for the observed absorption spectrum. We present the theory that underlies such absorption performance, involving the evanescent waves and their interaction with a dissipative medium, and show the excellent agreement with the experiment.

physics.class-ph↗
arXiv2016

Telepresence Interaction by Touching Live Video Images

This paper presents a telepresence interaction framework based on touchscreen and telepresence-robot technologies. The core of the framework is a new user interface, Touchable live video Image based User Interface, called TIUI. The TIUI allows a remote operator to not just drive the telepresence robot but operate and interact with real objects by touching their live video images on a pad with finger touch gestures. We implemented a telepresence interaction system which is composed of a telepresence robot and tele-interactive objects located in a local space, the TIUI of a pad located in a remote space, and the wireless networks connecting the two spaces. Our system can be a perfect embodiment of a remote operator to do most of daily living tasks, such as opening a door, drawing a curtain, pushing a wheelchair, and other like tasks. The evaluation and demonstration results show the effectiveness and promising applications of our system.

cs.HC↗
arXiv2016

Local unitary equivalence of quantum states and simultaneous orthogonal equivalence

The correspondence between local unitary equivalence of bipartite quantum states and simultaneous orthogonal equivalence is thoroughly investigated and strengthened. It is proved that local unitary equivalence can be studied through simultaneous similarity under projective orthogonal transformations, and four parametrization independent algorithms are proposed to judge when two density matrices on $\mathbb C^{d_1}\otimes \mathbb C^{d_2}$ are locally unitary equivalent in connection with trace identities, Weierstrass pencils, Albert determinants and Smith normal forms.

quant-ph↗
arXiv2015

Temporal Dynamic Appearance Modeling for Online Multi-Person Tracking

Robust online multi-person tracking requires the correct associations of online detection responses with existing trajectories. We address this problem by developing a novel appearance modeling approach to provide accurate appearance affinities to guide data association. In contrast to most existing algorithms that only consider the spatial structure of human appearances, we exploit the temporal dynamic characteristics within temporal appearance sequences to discriminate different persons. The temporal dynamic makes a sufficient complement to the spatial structure of varying appearances in the feature space, which significantly improves the affinity measurement between trajectories and detections. We propose a feature selection algorithm to describe the appearance variations with mid-level semantic features, and demonstrate its usefulness in terms of temporal dynamic appearance modeling. Moreover, the appearance model is learned incrementally by alternatively evaluating newly-observed appearances and adjusting the model parameters to be suitable for online tracking. Reliable tracking of multiple persons in complex scenes is achieved by incorporating the learned model into an online tracking-by-detection framework. Our experiments on the challenging benchmark MOTChallenge 2015 demonstrate that our method outperforms the state-of-the-art multi-person tracking algorithms.

cs.CV↗
arXiv2015

Subwavelength total acoustic absorption with degenerate resonators

We report the experimental realization of perfect sound absorption by sub-wavelength monopole and dipole resonators that exhibit degenerate resonant frequencies. This is achieved through the destructive interference of two resonators' transmission responses, while the matching of their averaged impedances to that of air implies no backscattering, thereby leading to total absorption. Two examples, both using decorated membrane resonators (DMRs) as the basic units, are presented. The first is a flat panel comprising a DMR and a pair of coupled DMRs, while the second one is a ventilated short tube containing a DMR in conjunction with a sidewall DMR backed by a cavity. In both examples, near perfect absorption, up to 99.7%, has been observed with the airborne wavelength up to 1.2 m, which is at least an order of magnitude larger than the composite absorber. Excellent agreement between theory and experiment is obtained.

cond-mat.mtrl-sci↗
arXiv2015

Sound Absorption by Subwavelength Membrane Structures: A Generalized Perspective

Decorated membrane, comprising a thin layer of elastic film with small rigid platelets fixed on top, has been found to be an efficient absorber of low frequency sound. In this work we consider the problem of sound absorption from a perspective aimed at deriving upper bounds under different scenarios, i.e., whether the sound is incident from one side only or from both sides, and whether there is a reflecting surface on the back side of the membrane. By considering the negligible thickness of the membrane, usually on the order of a fraction of one millimeter, we derive a relation showing that the sum of the incoming sound waves' (complex) pressure amplitudes, averaged over the area of the membrane, must be equal to that of the outgoing waves. By using this relation, and without going to any details of the wave solutions, it is shown that the maximum absorption achievable from one-side incident is 50%, while the maximum absorption with a back reflecting surface can reach 100%. The latter was attained by the hybridized resonances. All the results are shown to be in excellent agreement with the experiments. This generalized perspective, when used together with the Green function formalism, can be useful in gaining insights and delineating the constraints on what are achievable in scatterings and absorption by thin film structures.

cond-mat.mtrl-sci↗
arXiv2015

Ordering-sensitive and Semantic-aware Topic Modeling

Topic modeling of textual corpora is an important and challenging problem. In most previous work, the "bag-of-words" assumption is usually made which ignores the ordering of words. This assumption simplifies the computation, but it unrealistically loses the ordering information and the semantic of words in the context. In this paper, we present a Gaussian Mixture Neural Topic Model (GMNTM) which incorporates both the ordering of words and the semantic meaning of sentences into topic modeling. Specifically, we represent each topic as a cluster of multi-dimensional vectors and embed the corpus into a collection of vectors generated by the Gaussian mixture model. Each word is affected not only by its topic, but also by the embedding vector of its surrounding words and the context. The Gaussian mixture components and the topic of documents, sentences and words can be learnt jointly. Extensive experiments show that our model can learn better topics and more accurate word distributions for each topic. Quantitatively, comparing to state-of-the-art topic modeling approaches, GMNTM obtains significantly better performance in terms of perplexity, retrieval accuracy and classification accuracy.

cs.LG↗
arXiv2014

Saturated locally optimal designs under differentiable optimality criteria

We develop general theory for finding locally optimal designs in a class of single-covariate models under any differentiable optimality criterion. Yang and Stufken [Ann. Statist. 40 (2012) 1665-1681] and Dette and Schorning [Ann. Statist. 41 (2013) 1260-1267] gave complete class results for optimal designs under such models. Based on their results, saturated optimal designs exist; however, how to find such designs has not been addressed. We develop tools to find saturated optimal designs, and also prove their uniqueness under mild conditions.

math.ST↗