Lin F. Yang - LMM

Lin F. Yang
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Lin F. Yang

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Pub Categories

Physics - Materials Science (4)
Computer Science - Computer Vision and Pattern Recognition (4)
Mathematics - Statistics (3)
Computer Science - Learning (3)
Computer Science - Data Structures and Algorithms (3)
Cosmology and Nongalactic Astrophysics (3)
Quantum Physics (3)
Statistics - Theory (3)
High Energy Astrophysical Phenomena (2)
Mathematics - Optimization and Control (2)
Physics - Strongly Correlated Electrons (2)
Quantitative Biology - Populations and Evolution (2)
Statistics - Machine Learning (2)
Physics - Other (1)
Physics - Soft Condensed Matter (1)
Quantitative Biology - Tissues and Organs (1)
Computer Science - Computer Science and Game Theory (1)
Computer Science - Information Retrieval (1)
Physics - Mesoscopic Systems and Quantum Hall Effect (1)

Publications Authored By Lin F. Yang

Finding the reduced-dimensional structure is critical to understanding complex networks. Existing approaches such as spectral clustering are applicable only when the full network is explicitly observed. In this paper, we focus on the online factorization and partition of implicit large-scale networks based on observations from an associated random walk. Read More

Tungstates $A$WO$_4$ with the wolframite structure characterized by the $A$O$_6$ octahedral zigzag chains along the $c$-axis, can be magnetic if $A$=Mn, Fe, Co, Cu, Ni. Among them, MnWO$_4$ is a unique member with a cycloid Mn$^{2+}$ spin order developed at low temperature, leading to an interesting type-II multiferroic behavior. However, so far no other multiferroic material in the tungstate family has been found. Read More

Background: Guillain-Barr\'e Syndrome (GBS) is a common type of severe acute paralytic neuropathy and associated with other virus infections such as dengue fever and Zika. This study investigate the relationship between GBS, dengue, local meteorological factors in Hong Kong and global climatic factors from January 2000 to June 2016. Methods: The correlations between GBS, dengue, Multivariate El Nino Southern Oscillation Index (MEI) and local meteorological data were explored by the Spearman Rank correlations and cross-correlations between these time series. Read More

In this paper, we propose a simple but effective method for fast image segmentation. We re-examine the locality-preserving character of spectral clustering by constructing a graph over image regions with both global and local connections. Our novel approach to build graph connections relies on two key observations: 1) local region pairs that co-occur frequently will have a high probability to reside on a common object; 2) spatially distant regions in a common object often exhibit similar visual saliency, which implies their neighborship in a manifold. Read More

We propose a robust image enhancement algorithm dedicated for muscle fiber specimen images captured by optical microscopes. Blur or out of focus problems are prevalent in muscle images during the image acquisition stage. Traditional image deconvolution methods do not work since they assume the blur kernels are known and also produce ring artifacts. Read More

We use differential equations based approaches to provide some {\it \textbf{physics}} insights into analyzing the dynamics of popular optimization algorithms in machine learning. In particular, we study gradient descent, proximal gradient descent, coordinate gradient descent, proximal coordinate gradient, and Newton's methods as well as their Nesterov's accelerated variants in a unified framework motivated by a natural connection of optimization algorithms to physical systems. Our analysis is applicable to more general algorithms and optimization problems {\it \textbf{beyond}} convexity and strong convexity, e. Read More

A promising approach to hedge against the inherent uncertainty of renewable generation is to equip the renewable plants with energy storage systems. This paper focuses on designing profit maximization offering strategies, i.e. Read More

Similarity search is a fundamental problem in social and knowledge networks like GitHub, DBLP, Wikipedia, etc. Existing network similarity measures are limited because they only consider similarity from the perspective of the query node. However, due to the complicated topology of real-world networks, ignoring the preferences of target nodes often results in odd or unintuitive performance. Read More

Purpose: Rupture of an intracranial aneurysm is the most common cause of subarachnoid haemorrhage (SAH), which is a life-threatening acute cerebrovascular event that typically affects working-age people. This study aims to investigate the aneurysmal SAH incidence rate in elderly population than in middle aged population in China. Materials and methods: Aneurysmal SAH cases were collected retrospectively from the archives of 21 hospitals in Mainland China. Read More

We design new sketching algorithms for unitarily invariant matrix norms, including the Schatten $p$-norms~$\|{\cdot}\|_{S_p}$, and obtain, as a by-product, streaming algorithms that approximate the norm of a matrix $A$ presented as a turnstile data stream. The primary advantage of our streaming algorithms is that they are simpler and faster than previous algorithms, while requiring the same or less storage. Our three main results are a faster sketch for estimating $\|{A}\|_{S_p}$, a smaller-space $O(1)$-pass sketch for $\|{A}\|_{S_p}$, and more general sketching technique that yields sublinear-space approximations for a wide class of matrix norms. Read More

Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation perfor- mance. To exploit the 3D contexts using neural networks, known DL segmentation methods, including 3D convolution, 2D convolution on planes orthogonal to 2D image slices, and LSTM in multiple directions, all suffer incompatibility with the highly anisotropic dimensions in common 3D biomedical images. Read More

Supervised contour detection methods usually require many labeled training images to obtain satisfactory performance. However, a large set of annotated data might be unavailable or extremely labor intensive. In this paper, we investigate the usage of semi-supervised learning (SSL) to obtain competitive detection accuracy with very limited training data (three labeled images). Read More

A central problem in the theory of algorithms for data streams is to determine which functions on a stream can be approximated in sublinear, and especially sub-polynomial or poly-logarithmic, space. Given a function $g$, we study the space complexity of approximating $\sum_{i=1}^n g(|f_i|)$, where $f\in\mathbb{Z}^n$ is the frequency vector of a turnstile stream. This is a generalization of the well-known frequency moments problem, and previous results apply only when $g$ is monotonic or has a special functional form. Read More

We characterize the streaming space complexity of every symmetric norm $l$ (a norm on $\mathbb{R}^n$ invariant under sign-flips and coordinate-permutations), by relating this space complexity to the measure-concentration characteristics of $l$. Specifically, we provide nearly matching upper and lower bounds on the space complexity of calculating a $(1\pm\epsilon)$-approximation to the norm of the stream, for every $0<\epsilon\leq 1/2$. (The bounds match up to $poly(\epsilon^{-1} \log n)$ factors. Read More

In this paper, we propose a new max-margin based discriminative feature learning method. Specifically, we aim at learning a low-dimensional feature representation, so as to maximize the global margin of the data and make the samples from the same class as close as possible. In order to enhance the robustness to noise, a $l_{2,1}$ norm constraint is introduced to make the transformation matrix in group sparsity. Read More

Warm dark matter (WDM) has been proposed as an alternative to cold dark matter (CDM), to resolve issues such as the apparent lack of satellites around the Milky Way. Even if WDM is not the answer to observational issues, it is essential to constrain the nature of the dark matter. The effect of WDM on haloes has been extensively studied, but the small-scale initial smoothing in WDM also affects the present-day cosmic web and voids. Read More

We study the global spatio-temporal patterns of influenza dynamics. This is achieved by analysing and modelling weekly laboratory confirmed cases of influenza A and B from 138 countries between January 2006 and May 2014. The data were obtained from FluNet, the surveillance network compiled by the the World Health Organization. Read More

Dimensional evolution between one- ($1D$) and two-dimensional ($2D$) topological phases is investigated systematically. The crossover from a $2D$ topological insulator to its $1D$ limit shows oscillating behavior between a $1D$ ordinary insulator and a $1D$ topological insulator. By constructing a $2D$ topological system from a $1D$ topological insulator, it is shown that there exist possibly weak topological phases in $2D$ time-reversal invariant band insulators, one of which can be realized in anisotropic systems. Read More

A model of Poissonian observation having a jump (change-point) in the intensity function is considered. Two cases are studied. The first one corresponds to the situation when the jump size converges to a non-zero limit, while in the second one the limit is zero. Read More

We consider the problem of hypothesis testing in the situation when the first hypothesis is simple and the second one is local one-sided composite. We describe the choice of the thresholds and the power functions of the Score Function test, of the General Likelihood Ratio test, of the Wald test and of two Bayes tests in the situation when the intensity function of the observed inhomogeneous Poisson process is smooth with respect to the parameter. It is shown that almost all these tests are asymptotically uniformly most powerful. Read More

We consider the problem of hypothesis testing in the situation where the first hypothesis is simple and the second one is local one-sided composite. We describe the choice of the thresholds and the power functions of different tests when the intensity function of the observed inhomogeneous Poisson process has two different types of singularity: cusp and discontinuity. The asymptotic results are illustrated by numerical simulations. Read More

Observations of diffuse Galactic gamma ray emission (DGE) by the Fermi Large Area Telescope (LAT) allow a detailed study of cosmic rays and the interstellar medium. However, diffuse emission models of the inner Galaxy underpredict the Fermi-LAT data at energies above a few GeV and hint at possible non-astrophysical sources including dark matter (DM) annihilations or decays. We present a study of the possible emission components from DM using the high-resolution Via Lactea II N-body simulation of a Milky Way-sized DM halo. Read More

We present an experiment in which we 'ring' a set of cosmological N-body-simulation initial conditions, placing spikes in the initial power spectrum at different wavenumber bins. We then measure where these spikes end up in the final conditions. In the usual overdensity power spectrum, most sensitive to contracting and collapsing dense regions, initial power on slightly non-linear scales (k ~ 0. Read More

We search for new fully compensated half metals, in which only one electronic spin channel is conducting and there exists no net magnetic moment. We focus on half Heusler alloys and we examine the physical consequence of different crystal structures found in the literature for these compounds, XMnZ, with a transition metal element, such as Cr, Mn, and Fe for X and a nonmetallic element, such as P, Sb and Si for Z. The structures differ in the placement of voids in the L2$_1$ structure of the full Heulser alloy. Read More

We present a proposal for realizing local decoherence-free evolution of given entangled states of two two-level (TL) ions. For two TL ions coupled to a single heavily damped cavity, we can use engineering reservoir scheme to obtain a decoherence-free subspace which can be nonadiabatically controlled by the system and reservoir parameters. Then the local decoherence-free evolution of the entangled states are achieved. Read More


We identify the optical counterpart of the ultraluminous X-ray source (ULX) NGC 1313 X-1 and discuss constraints on its physical nature from multiband optical spectra. There is a single object on Hubble Space Telescope (HST) images within the aspect-corrected Chandra X-ray error circle; a fainter, possibly extended, feature lies near the edge of the error circle. The brighter object showed prominent variation in the F555W band, but was constant in the F814W band. Read More

We describe the self-assembly of biomimetic isotropic films which display structural color amenable to potential applications in coatings. Isotropic structures can produce color if there is a pronounced characteristic length-scale comparable to the wavelength of visible light and wavelength-independent scattering is suppressed. Read More

We demonstrate the decoy-state quantum key distribution over 200 km with photon polarization through optical fiber, by using super-conducting single photon detector with a repetition rate of 320 Mega Hz and a dark count rate of lower than 1 Hz. Since we have used the polarization coding, the synchronization pulses can be run in a low frequency. The final key rate is 14. Read More

Recently, the magnetic moment/Mn, $M$, in Mn$_x$Si$_{1-x}$ was measured to be 5.0 $\mu_B$/Mn, at $x$ =0.1%. Read More

We show how to calculate the fraction of single photon counts of the 3-intensity decoy-state quantum cryptography faithfully with both statistical fluctuations and source errors. Our results only rely on the bound values of a few parameters of the states of pulses. Read More