arXiv subjects

Ying Zhang

Publications and source records attributed to Ying Zhang.

At least 541 records · Page 30Linked to original sources

arXiv2015

Restricted Low-Rank Approximation via ADMM

The matrix low-rank approximation problem with additional convex constraints can find many applications and has been extensively studied before. However, this problem is shown to be nonconvex and NP-hard; most of the existing solutions are heuristic and application-dependent. In this paper, we show that, other than tons of application in current literature, this problem can be used to recover a feasible solution for SDP relaxation. By some sophisticated tricks, it can be equivalently posed in an appropriate form for the Alternating Direction Method of Multipliers (ADMM) to solve. The two updates of ADMM include the basic matrix low-rank approximation and projection onto a convex set. Different from the general non-convex problems, the sub-problems in each step of ADMM can be solved exactly and efficiently in spite of their non-convexity. Moreover, the algorithm will converge exponentially under proper conditions. The simulation results confirm its superiority over existing solutions. We believe that the results in this paper provide a useful tool for this important problem and will help to extend the application of ADMM to the non-convex regime.

math.NA↗

arXiv2015

I/O Efficient Core Graph Decomposition at Web Scale

Core decomposition is a fundamental graph problem with a large number of applications. Most existing approaches for core decomposition assume that the graph is kept in memory of a machine. Nevertheless, many real-world graphs are big and may not reside in memory. In the literature, there is only one work for I/O efficient core decomposition that avoids loading the whole graph in memory. However, this approach is not scalable to handle big graphs because it cannot bound the memory size and may load most parts of the graph in memory. In addition, this approach can hardly handle graph updates. In this paper, we study I/O efficient core decomposition following a semi-external model, which only allows node information to be loaded in memory. This model works well in many web-scale graphs. We propose a semi-external algorithm and two optimized algorithms for I/O efficient core decomposition using very simple structures and data access model. To handle dynamic graph updates, we show that our algorithm can be naturally extended to handle edge deletion. We also propose an I/O efficient core maintenance algorithm to handle edge insertion, and an improved algorithm to further reduce I/O and CPU cost by investigating some new graph properties. We conduct extensive experiments on 12 real large graphs. Our optimal algorithm significantly outperform the existing I/O efficient algorithm in terms of both processing time and memory consumption. In many memory-resident graphs, our algorithms for both core decomposition and maintenance can even outperform the in-memory algorithm due to the simple structures and data access model used. Our algorithms are very scalable to handle web-scale graphs. As an example, we are the first to handle a web graph with 978.5 million nodes and 42.6 billion edges using less than 4.2 GB memory.

cs.DB↗

arXiv2015

Batch Normalized Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are powerful models for sequential data that have the potential to learn long-term dependencies. However, they are computationally expensive to train and difficult to parallelize. Recent work has shown that normalizing intermediate representations of neural networks can significantly improve convergence rates in feedforward neural networks . In particular, batch normalization, which uses mini-batch statistics to standardize features, was shown to significantly reduce training time. In this paper, we show that applying batch normalization to the hidden-to-hidden transitions of our RNNs doesn't help the training procedure. We also show that when applied to the input-to-hidden transitions, batch normalization can lead to a faster convergence of the training criterion but doesn't seem to improve the generalization performance on both our language modelling and speech recognition tasks. All in all, applying batch normalization to RNNs turns out to be more challenging than applying it to feedforward networks, but certain variants of it can still be beneficial.

stat.ML↗

arXiv2015

Peak-Aware Online Economic Dispatching for Microgrids

By employing local renewable energy sources and power generation units while connected to the central grid, microgrid can usher in great benefits in terms of cost efficiency, power reliability, and environmental awareness. Economic dispatching is a central problem in microgrid operation, which aims at effectively scheduling various energy sources to minimize the operating cost while satisfying the electricity demand. Designing intelligent economic dispatching strategies for microgrids, however, is drastically different from that for conventional central grids, due to two unique challenges. First, the erratic renewable energy emphasizes the need for online algorithms. Second, the widely-adopted peak-based pricing scheme brings out the need for new peak-aware strategy design. In this paper, we tackle these critical challenges and devise peak-aware online economic dispatching algorithms. For microgrids with fast-responding generators, we prove that our deterministic and randomized algorithms achieve the best possible competitive ratios $2-β$ and $e/(e-1+β)$, respectively, where $β\in[0,1]$ is the ratio between the minimum grid spot price and the local-generation price. Our results characterize the fundamental \emph{price of uncertainty} of the problem. For microgrids with slow-responding generators, we first show that a large competitive ratio is inevitable. Then we leverage limited prediction of electricity demand and renewable generation to improve the competitiveness of the algorithms. By extensive empirical evaluations using real-world traces, we show that our online algorithms achieve near offline-optimal performance. In a representative scenario, our algorithm achieves $17.5\%$ and $9.24\%$ cost reduction as compared to the case without local generation units and the case using peak-oblivious algorithms, respectively.

eess.SY↗

arXiv2015

Development of Yangbajing Air shower Core detector array for a new EAS hybrid Experiment

Aiming at the observation of cosmic-ray chemical composition at the "knee" energy region, we have been developinga new type air-shower core detector (YAC, Yangbajing Air shower Core detector array) to be set up at Yangbajing (90.522$^\circ$ E, 30.102$^\circ$ N, 4300 m above sea level, atmospheric depth: 606 g/m$^2$) in Tibet, China. YAC works together with the Tibet air-shower array (Tibet-III) and an underground water cherenkov muon detector array (MD) as a hybrid experiment. Each YAC detector unit consists of lead plates of 3.5 cm thick and a scintillation counter which detects the burst size induced by high energy particles in the air-shower cores. The burst size can be measured from 1 MIP (Minimum Ionization Particle) to $10^{6}$ MIPs. The first phase of this experiment, named "YAC-I", consists of 16 YAC detectors each having the size 40 cm $\times$ 50 cm and distributing in a grid with an effective area of 10 m$^{2}$. YAC-I is used to check hadronic interaction models. The second phase of the experiment, called "YAC-II", consists of 124 YAC detectors with coverage about 500 m$^2$. The inner 100 detectors of 80 cm $\times $ 50 cm each are deployed in a 10 $\times$ 10 matrix from with a 1.9 m separation and the outer 24 detectors of 100 cm $\times$ 50 cm each are distributed around them to reject non-core events whose shower cores are far from the YAC-II array. YAC-II is used to study the primary cosmic-ray composition, in particular, to obtain the energy spectra of proton, helium and iron nuclei between 5$\times$$10^{13}$ eV and $10^{16}$ eV covering the "knee" and also being connected with direct observations at energies around 100 TeV. We present the design and performance of YAC-II in this paper.

physics.ins-det↗

arXiv2015

Polynomial automorphisms of C^n preserving the Markoff-Hurwitz polynomial

We study the action of the group of polynomial automorphisms of C^n (n>2) which preserve the Markoff-Hurwitz polynomial H(x):= x_1^2 + x_2^2 + ... + x_n^2 - x_1 x_2 ... x_n. Our main results include the determination of the group, the description of a non-empty open subset of C^n on which the group acts properly discontinuously (domain of discontinuity), and identities for the orbit of points in the domain of discontinuity.

math.GT↗

arXiv2015

Statistical Constraints on the Error of the Leptonic CP Violation of Neutrinos

A constraint on the error of leptonic CP violation, which require the phase $δ_{CP}$ to be less than $π/4$ for it to be distinguishable on a $2π$ cycle, is presented. Under this constraint, the effects of neutrino detector 's distance, beam energy, and energy resolution are discussed with reference to the present values of these parameters in experiments. Although an optimized detector performances can minimize the deviation to yield a larger distinguishable range of the leptonic CP phase on a $2π$ cycle, it is not possible to determine an arbitrary leptonic CP phase in the range of $2π$ with the statistics from a single detector because of the existence of two singular points. An efficiency factor $η$ is defined to characterize the distinguishable range of $δ_{CP}$. To cover the entire possible $δ_{CP}$ range, a combined efficiency factor $η^*$ corresponding to multiple sets of detection parameters with different neutrino beam energies and distances is proposed. The combined efficiency factors $η^*$ of various major experiments are also presented.

hep-ph↗

arXiv2015

A Simple and General Problem and its Optimal Randomized Online Algorithm Design with Competitive Analysis

The online algorithm design was proposed to handle the caching problem when the future information is unknown. And currently, it draws more and more attentions from the researchers from the areas of microgrid, where the production of renewables are unpredictable. In this note, we present a framework of randomized online algorithm design for the \textit{simple and tractable} problem. This framework hopes to provide a tractable design to design a randomized online algorithm, which can be proved to achieve the best competitive ratio by \textit{Yao's Principle}.

cs.OH↗

arXiv2015

Combined Analysis of the CP Properties of The Higgs Boson in Effective Higgs Lagrangian

CP violation effects of the Higgs stem from not only CP-violation interactions but also an ambiguous defined CP state. The two CPV sources are coherently studied based on an effective Higgs Lagrangian. The constraints from unitarity limits for $WW$ and $ZZ$ scatterings are proposed to restrict Higgs couplings to weak gauge bosons. Five interesting cases are classified in terms of CPV sources to investigate the Higgs CP properties. The allowed ranges are shown from fitting results to the signal strengths of the Higgs measured by ATLAS and CMS.

hep-ph↗

arXiv2014

Virtual Machine Migration Planning in Software-Defined Networks

In this paper, we examine the problem of how to schedule the migrations and how to allocate network resources for migration when multiple VMs need to be migrated at the same time. We consider the problem in the Software-defined Network (SDN) context since it provides flexible control on routing. More specifically, we propose a method that computes the optimal migration sequence and network bandwidth used for each migration. We formulate this problem as a mixed integer programming, which is NP-hard. To make it computationally feasible for large scale data centers, we propose an approximation scheme via linear approximation plus fully polynomial time approximation, and obtain its theoretical performance bound. Through extensive simulations, we demonstrate that our fully polynomial time approximation (FPTA) algorithm has a good performance compared with the optimal solution and two state of-the-art algorithms. That is, our proposed FPTA algorithm approaches to the optimal solution with less than 10% variation and much less computation time. Meanwhile, it reduces the total migration time and the service downtime by up to 40% and 20% compared with the state-of-the-art algorithms, respectively.

cs.NI↗

arXiv2014

Symplectic Cohomology and the Stability of J-Anti-Invariant Cohomology

In this paper, we investigate the relationship between J-anti-invariant cohomology of a closed symplectic 4-manifold introduced by T.-J. Li and W. Zhang and new symplectic cohomologies introduced by L.-S. Tseng and S.-T. Yau. We also prove that the dimension of J-anti-invariant cohomology is constant for almost structures J which are compatible with a fixed symplectic form.

math.SG↗

arXiv2014

A new multivariate dependence measure based on comonotonicity

In this paper we introduce a new multivariate dependence measure based on comonotonicity by means of product moment which motivated by the recent papers of Koch and Schepper (ASTIN Bulletin 41 (2011) 191-213) and Dhaene et al. (Journal of Computational and Applied Mathematics 263 (2014) 78-87). Some differences and relations between the new dependence measure and other multivariate measures are an- alyzed. We also give several characteristics of this measure and estimations based on the definitions and its property are presented.

q-fin.RM↗

arXiv2014

Effects of carbon nanotubes and graphene oxide absorbers on the noise of mode-locked fiber lasers

Phase noise is very important for the ultrafast pulse application in telecommunication, ultrafast diagnose, material science, and biology. In this paper, two types of carbon nano-materials, single-wall carbon nanotube and graphene oxide, are investigated for noise suppression in ultrafast photonics. Various properties of the wall-paper SAs, such as saturable intensity, optical absorption and degree of purity, are found to be key factors determining the phase noise of the ultrafast pulses. A reduced-noise femtosecond fiber laser is experimentally demonstrated by optimizing the above parameters of carbon material based SAs. The phase noise reduction more than 10 dB at 10 kHz can be obtained in the experiments. To our knowledge, this is the first time that the relationship between different carbon material based SAs and the phase noise of mode-locked lasers has been investigated. This work will pave the way to get a high-quality ultrashort pulse in passively mode-locked fiber lasers.

physics.optics↗

arXiv2014

Presentations for quaternionic $S$-unit groups

The purpose of this paper is to give presentations for projective $S$-unit groups of the Hurwitz order in Hamilton's quaternions over the rational field $\mathbb{Q}$. To our knowledge, this provides the first explicit presentations of an $S$-arithmetic lattice in a semisimple Lie group with $S$ large. In particular, we give presentations for groups acting irreducibly and cocompactly on a product of Bruhat--Tits trees. We also include some discussion and experimentation related to the congruence subgroup problem, which is open when $S$ contains at least two odd primes. In the appendix, we provide code that allows the reader to compute presentations for an arbitrary finite set $S$.

math.NT↗

arXiv2014

Application of signal processing techniques in the assessment of clinical risks in preterm infants

Preterm infants with very low birth weight suffer from a high risk of intra-ventricular hemorrhage(IVH) and other serious diseases. To improve the clinical risk assessment of preterm infants and develop potential clinically makers for the adverse outcome, the first part of the paper develops the frequency spectral analysis on the non-invasively measured heart rate variability, blood pressure variability and cerebral near-infrared spectroscopy measures. Moderate and high correlations with the clinical risk index for babies were identified from various spectral measures of arterial baroreflex and cerebral autoregulation functions. It was also observed that the cross-spectral transfer function analysis of cerebral NIRS and arterial blood pressure was able to provide a number of parameters that were potentially useful for distinguishing between preterm infants with or without IVH. Furthermore, the detrended fluctuation analysis that quantifies the fractal correlation properties of physiological signals has been examined, to determine whether it could derive markers for the identification of preterm infants with IVH. Cardiac output(CO) and total peripheral resistance(TPR) are two important parameters of the cardiovascular system. Measurement of these two parameters can provide valuable information for the assessment and management of patients needing intensive care, including preterm infants in the neonatal intensive care unit. To further assess the changes in CO and TPR in the preterm infants, the multivariate regression model based on the useful features from ABP method was used to improve the accuracy and robustness of the estimation. The combination of signal analysis and multivariate regression model in estimation of CO has produced some outcomes, and in the future, more effort should be involved in this kind of research to improve the prediction of serious diseases in preterm infants.

q-bio.QM↗

arXiv2014

Higgsphobic and fermiophobic Z' as a single dark matter candidate

A spin-1 Z' particle as a single dark matter candidate is investigated by assuming that it does not directly couple to the Higgs boson and standard model fermions and does not mix with the photon and Z boson. The remaining dominant vertices are quartic Z'Z'ZZ and Z'Z'W+W-, which can induce effective Z'Z'q\bar{q} couplings through standard-model gauge-boson loops. We discuss constraints from the cosmological thermal relic density, and direct and indirect-detection experiments, and find that a dark Z' can only exist above the W boson mass threshold, and the effective quartic coupling of Z'Z'VV is bounded in the region of 10^{-3}~10^{-2}.

hep-ph↗

arXiv2014

A new identity for SL(2,C)-characters of the once punctured torus group

We obtain new variations of the original McShane identity for those SL(2,C)-representations of the once punctured torus group which satisfy the Bowditch conditions, and also for those fixed up to conjugacy by an Anosov mapping class of the torus and satisfying the relative Bowditch conditions.

math.GT↗

arXiv2013

Engineering Topological Surface States and Giant Rashba Spin Splitting in BiTeI/Bi$_2$Te$_3$ Heterostructures

The search for strongly inversion asymmetric topological insulators is an active research field because these materials possess distinct properties compared with the inversion symmetric ones. In particular, it is desirable to realize a large Rashba spin-splitting (RSS) in such materials, which combined with the topological surface states (TSS) could lead to useful spintronics applications. In this report, based on first principles calculations, we predict that the heterostructure of BiTeI/Bi$_{2}$Te$_{3}$ is a strong topological insulator with a giant RSS. The coexistence of TSS and RSS in the current system is native and stable. More importantly, we find that both the $\mathbb{Z}_{2}$ invariants and the Rashba energy can be controlled by engineering the layer geometries of the heterostructure, and the Rashba energy can be made even larger than that of bulk BiTeI. Our work opens a new route for designing topological spintronics devices based on inversion asymmetric heterostructures.

cond-mat.mtrl-sci↗