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Hao Chen

Publications and source records attributed to Hao Chen.

At least 1,441 records · Page 80Linked to original sources

A ternary construction of lattices

In this paper we propose a general ternary construction of lattices from three rows and ternary codes. Most laminated lattices and Kappa lattices in ${\bf R}^n$, $n\leq 24$ can be recovered from our tenary construction naturally. This ternary construction of lattices can be used to generate many new "sub-optimal" lattices of low dimensions.Based on this ternary construction new extremal even lattices of dimensions $32, 40$ and $48$ are also constructed.

math.NT↗

Computing the Mazur and Swinnerton-Dyer critical subgroup of elliptic curves

Let $E$ be an optimal elliptic curve defined over $\mathbb{Q}$. The critical subgroup of $E$ is defined by Mazur and Swinnerton-Dyer as the subgroup of $E(\mathbb{Q})$ generated by traces of branch points under a modular parametrization of $E$. We prove that for all rank two elliptic curves with conductor smaller than 1000, the critical subgroup is torsion. First, we define a family of critical polynomials attached to $E$ and describe two algorithms to compute such polynomials. We then give a sufficient condition for the critical subgroup to be torsion in terms of the factorization of critical polynomials. Finally, a table of critical polynomials is obtained for all elliptic curves of rank two and conductor smaller than 1000, from which we deduce our result.

math.NT↗

Vibration-assisted coherent excitation energy transfer in a detuning system

The roles of the vibration motions played in the excitation energy transfer process are studied. It is found that a strong coherent transfer in the hybrid system emerges when the detuning between the donor and the acceptor equals the intrinsic frequency of the vibrational mode, and as a result the energy can be transferred into the acceptor much effectively. Three cases of the donor and the acceptor coupling with vibrational modes are investigated respectively. We find that the quantum interference between the two different transfer channels via the vibrational modes can affects the dynamics of the system significantly.

physics.bio-ph↗

A First Look at Firefox OS Security

With Firefox OS, Mozilla is making a serious push for an HTML5-based mobile platform. In order to assuage security concerns over providing hardware access to web applications, Mozilla has introduced a number of mechanisms that make the security landscape of Firefox OS distinct from both the desktop web and other mobile operating systems. From an application security perspective, the two most significant of these mechanisms are the the introduction of a default Content Security Policy and code review in the market. This paper describes how lightweight static analysis can augment these mechanisms to find vulnerabilities which have otherwise been missed. We provide examples of privileged applications in the market that contain vulnerabilities that can be automatically detected. In addition to these findings, we show some of the challenges that occur when desktop software is repurposed for a mobile operating system. In particular, we argue that the caching of certificate overrides across applications--a known problem in Firefox OS--generates a counter-intuitive user experience that detracts from the security of the system.

cs.CR↗

1-HKUST: Object Detection in ILSVRC 2014

The Imagenet Large Scale Visual Recognition Challenge (ILSVRC) is the one of the most important big data challenges to date. We participated in the object detection track of ILSVRC 2014 and received the fourth place among the 38 teams. We introduce in our object detection system a number of novel techniques in localization and recognition. For localization, initial candidate proposals are generated using selective search, and a novel bounding boxes regression method is used for better object localization. For recognition, to represent a candidate proposal, we adopt three features, namely, RCNN feature, IFV feature, and DPM feature. Given these features, category-specific combination functions are learned to improve the object recognition rate. In addition, object context in the form of background priors and object interaction priors are learned and applied in our system. Our ILSVRC 2014 results are reported alongside with the results of other participating teams.

cs.CV↗

Graph-Based Change-Point Detection

We consider the testing and estimation of change-points -- locations where the distribution abruptly changes -- in a data sequence. A new approach, based on scan statistics utilizing graphs representing the similarity between observations, is proposed. The graph-based approach is non-parametric, and can be applied to any data set as long as an informative similarity measure on the sample space can be defined. Accurate analytic approximations to the significance of graph-based scan statistics for both the single change-point and the changed interval alternatives are provided. Simulations reveal that the new approach has better power than existing approaches when the dimension of the data is moderate to high. The new approach is illustrated on two applications: The determination of authorship of a classic novel, and the detection of change in a network over time.

stat.ME↗

Graph-Based Tests for Two-Sample Comparisons of Categorical Data

We study the problem of two-sample comparison with categorical data when the contingency table is sparsely populated. In modern applications, the number of categories is often comparable to the sample size, causing existing methods to have low power. When the number of categories is large, there is often underlying structure on the sample space that can be exploited. We propose a general non-parametric approach that utilizes similarity information on the space of all categories in two sample tests. Our approach extends the graph-based tests of Friedman and Rafsky (1979) and Rosenbaum (2005), which are tests base on graphs connecting observations by similarity. Both tests require uniqueness of the underlying graph and cannot be directly applied on categorical data. We explored different ways to extend graph-based tests to the categorical setting and found two types of statistics that are both powerful and fast to compute. We showed that their permutation null distributions are asymptotically normal and that their $p$-value approximations under typical settings are quite accurate, facilitating the application of the new approach. The approach is illustrated through several examples.

stat.ME↗

Limit Directions for Lorentzian Coxeter Systems

Every Coxeter group admits a geometric representation as a group generated by reflections in a real vector space. In the projective representation space, limit directions are limits of injective sequences in the orbit of some base point. Limit roots are limit directions that can be obtained starting from simple roots. In this article, we study the limit directions arising from any point when the representation space is a Lorentz space. In particular, we characterize the light-like limit directions using eigenvectors of infinite-order elements. This provides a spectral perspective on limit roots, allowing for efficient computations. Moreover, we describe the space-like limit directions in terms of the projective Coxeter arrangement.

math.GR↗

Apollonian Ball Packings and Stacked Polytopes

We investigate in this paper the relation between Apollonian $d$-ball packings and stacked $(d+1)$-polytopes for dimension $d\ge 3$. For $d=3$, the relation is fully described: we prove that the $1$-skeleton of a stacked $4$-polytope is the tangency graph of an Apollonian $3$-ball packing if and only if no six $4$-cliques share a $3$-clique. For higher dimension, we have some partial results.

math.MG↗

Dense lattices in low dimensions

The Barnes-Wall lattice ${\bf Λ}_{16}$ with the center density ${\{1}{16}}$ and the kissing number 4320 was found in 1959 and is the only known densest sphere packing in the dimension 16. J. H. Conway and N.J.A. Sloane conjectured that ${\bf Λ}_{16}$ is the densest 16 dimensional lattice. Sometimes it is conjectured that the Barnes-Wall lattice ${\bf Λ}_{16}$ is the only densest lattice and the optimal sphere packing in ${\bf R}^{16}$. In this paper two new 16 dimensional lattices with the center density $\{1}{16}$ and the kissing numbers 4224 and 4176 are constructed. This leads to several new 14 and 15 dimensional lattices which have the same center densities but different kissing numbers as the presently known densest lattices in these two dimensions. This gives a negative answer to the long time expectation that ${\bf Λ}_n$'s, $n \leq 24, n \neq 11,12,13$ are the only densest lattices in their dimensions. {abstract}

math.NT↗

Distance Geometry for Kissing Spheres

A kissing sphere is a sphere that is tangent to a fixed reference ball. We develop in this paper a distance geometry for kissing spheres, which turns out to be a generalization of the classical Euclidean distance geometry.

math.MG↗

New lattice sphere packings denser than Mordell-Weil lattices

1) We present new lattice sphere packings in Euclid spaces of many dimensions in the range 3332-4096, which are denser than known densest Mrodell-Weil lattice sphere packings in these dimensions. Moreover it is proved that if there were some nice linear binary codes we could construct lattices denser than Mordell-Weil lattices of many dimensions in the range 116-3332. 2) New lattices with densities at least 8 times of the densities of Craig lattices in the dimensions $p-1$, where $p$ is a prime satisfying $p-1 \geq 1222$, are constructed. Some of these lattices provide new record sphere packings. 3) Lattice sphere packings in many dimensions in the range 4098-8232 better than present records are presented. Some new dense lattice sphere packings in moderate dimensions $84, 85, 86, 181-189$ denser than any previously known sphere packings in these dimensions are also given. The construction is based on the analogues of Craig lattices.

math.NT↗

Spatial Whitening Framework for Distributed Estimation

Designing resource allocation strategies for power constrained sensor network in the presence of correlated data often gives rise to intractable problem formulations. In such situations, applying well-known strategies derived from conditional-independence assumption may turn out to be fairly suboptimal. In this paper, we address this issue by proposing an adjacency-based spatial whitening scheme, where each sensor exchanges its observation with their neighbors prior to encoding their own private information and transmitting it to the fusion center. We comment on the computational limitations for obtaining the optimal whitening transformation, and propose an iterative optimization scheme to achieve the same for large networks. We demonstrate the efficacy of the whitening framework by considering the example of bit-allocation for distributed estimation.

cs.IT↗

Optimal Identical Binary Quantizer Design for Distributed Estimation

We consider the design of identical one-bit probabilistic quantizers for distributed estimation in sensor networks. We assume the parameter-range to be finite and known and use the maximum Cramér-Rao Lower Bound (CRB) over the parameter-range as our performance metric. We restrict our theoretical analysis to the class of antisymmetric quantizers and determine a set of conditions for which the probabilistic quantizer function is greatly simplified. We identify a broad class of noise distributions, which includes Gaussian noise in the low-SNR regime, for which the often used threshold-quantizer is found to be minimax-optimal. Aided with theoretical results, we formulate an optimization problem to obtain the optimum minimax-CRB quantizer. For a wide range of noise distributions, we demonstrate the superior performance of the new quantizer - particularly in the moderate to high-SNR regime.

cs.IT↗

Minimum vertex covers and the spectrum of the normalized Laplacian on trees

We show that, in the graph spectrum of the normalized graph Laplacian on trees, the eigenvalue 1 and eigenvalues near 1 are strongly related to minimum vertex covers. In particular, for the eigenvalue 1, its multiplicity is related to the size of a minimum vertex cover, and zero entries of its eigenvectors correspond to vertices in minimum vertex covers; while for eigenvalues near 1, their distance to 1 can be estimated from minimum vertex covers; and for the largest eigenvalue smaller than 1, the sign graphs of its eigenvectors take vertices in a minimum vertex cover as representatives.

math.CO↗

Restricted Parameter Range Promise Set Cover Problems Are Easy

Let $({\bf U},{\bf S},d)$ be an instance of Set Cover Problem, where ${\bf U}=\{u_1,...,u_n\}$ is a $n$ element ground set, ${\bf S}=\{S_1,...,S_m\}$ is a set of $m$ subsets of ${\bf U}$ satisfying $\bigcup_{i=1}^m S_i={\bf U}$ and $d$ is a positive integer. In STOC 1993 M. Bellare, S. Goldwasser, C. Lund and A. Russell proved the NP-hardness to distinguish the following two cases of ${\bf GapSetCover_η}$ for any constant $η> 1$. The Yes case is the instance for which there is an exact cover of size $d$ and the No case is the instance for which any cover of ${\bf U}$ from ${\bf S}$ has size at least $ηd$. This was improved by R. Raz and S. Safra in STOC 1997 about the NP-hardness for ${\bf GapSetCover}_{clogm}$ for some constant $c$. In this paper we prove that restricted parameter range subproblem is easy. For any given function of $n$ satisfying $η(n) \geq 1$, we give a polynomial time algorithm not depending on $η(n)$ to distinguish between {\bf YES:} The instance $({\bf U},{\bf S}, d)$ where $d>\frac{2 |{\bf S}|}{3η(n)-1}$, for which there exists an exact cover of size at most $d$; {\bf NO:} The instance $({\bf U},{\bf S}, d)$ where $d>\frac{2 |{\bf S}|}{3η(n)-1}$, for which any cover from ${\bf S}$ has size larger than $η(n) d$. The polynomial time reduction of this restricted parameter range set cover problem is constructed by using the lattice.

cs.CC↗

Accelerating Nesterov's Method for Strongly Convex Functions with Lipschitz Gradient

We modify Nesterov's constant step gradient method for strongly convex functions with Lipschitz continuous gradient described in Nesterov's book. Nesterov shows that $f(x_k) - f^* \leq L \prod_{i=1}^k (1 - α_k) \| x_0 - x^* \|_2^2$ with $α_k = \sqrtρ$ for all $k$, where $L$ is the Lipschitz gradient constant and $ρ$ is the reciprocal condition number of $f(x)$. Hence the convergence rate is $1-\sqrtρ$. In this work, we try to accelerate Nesterov's method by adaptively searching for an $α_k > \sqrtρ$ at each iteration. The proposed method evaluates the gradient function at most twice per iteration and has some extra Level 1 BLAS operations. Theoretically, in the worst case, it takes the same number of iterations as Nesterov's method does but doubles the gradient calls. However, in practice, the proposed method effectively accelerates the speed of convergence for many problems including a smoothed basis pursuit denoising problem.

math.OC↗