Fast matching of large point sets under occlusions

The problem of isometric point-pattern matching can be modeled as inference in small tree-width graphical models whose embeddings in the plane are said to be ‘globally rigid’. Although such graphical models lead to efficient and exact solutions, they cannot generally handle occlusions, as even a single missing point may ‘break’ the rigidity of the graph in question. In addition, such models can efficiently handle point sets of only moderate size. In this paper, we propose a new graphical model that is not only adapted to handle occlusions but is much faster than previous approaches for solving the isometric point-pattern matching problem. We can match point-patterns with thousands of points in a few seconds.     

Graphical models and point pattern matching

This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We present a noniterative, polynomial time algorithm that is guaranteed to find an optimal solution for the noiseless case. First, we model point pattern matching as a weighted graph matching problem, where weights correspond to Euclidean distances between nodes. We then formulate graph matching as a problem of finding a maximum probability configuration in a graphical model. By using graph rigidity arguments, we prove that a sparse graphical model yields equivalent results to the fully connected model in the noiseless case. This allows us to obtain an algorithm that runs in polynomial time and is provably optimal for exact matching between noiseless point sets. For inexact matching, we can still apply the same algorithm to find approximately optimal solutions. Experimental results obtained by our approach show improvements in accuracy over current methods, particularly when matching patterns of different sizes.     

基于概率图模型的点集匹配方法研究

在概率图模型框架下提出了一种将回归分析和聚类分析相结合的贝叶斯点集匹配方法,其中,回归分析用来估计两个点集之间的映射函数,而聚类分析用来建立两个点集中点与点之间的对应关系.本文将点集匹配问题表示为一种多层的概率有向图,并提出了一种由粗到精的变分逼近算法来估计点集匹配的不确定性;此外,还利用高斯混合模型估计映射函数回归中的异方差噪声和场景点密度估计中离群点的分布;同时,引入转移变量建立起模型点集与场景点集之间的关系,并与离群点混合模型共同对场景点的分布进行估计.实验结果表明,该方法与其他点集匹配算法相比,在鲁棒性和匹配精度方面均达到了较好的效果.     

On-line graph coloring of {\mathbb{P}_5}-free graphs

Kierstead et al. (SIAM J Discret Math 8:485–498, 1995) have shown 1 that the competitive function of on-line coloring for -free graphs (i.e., graphs without induced path on 5 vertices) is bounded from above by the exponential function . No nontrivial lower bound was known. In this paper we show the quadratic lower bound . More precisely, we prove that is the exact competitive function for ()-free graphs. In this paper we also prove that 2 - 1 is the competitive function of the best clique covering on-line algorithm for ()-free graphs.     

Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm–Volterra integrodifferential equations

In this article, we propose the reproducing kernel Hilbert space method to obtain the exact and the numerical solutions of fuzzy Fredholm–Volterra integrodifferential equations. The solution methodology is based on generating the orthogonal basis from the obtained kernel functions in which the constraint initial condition is satisfied, while the orthonormal basis is constructing in order to formulate and utilize the solutions with series form in terms of their r-cut representation form in the Hilbert space \( W_{2}^{2} \left( \varOmega \right) \oplus W_{2}^{2} \left( \varOmega \right) \). Several computational experiments are given to show the good performance and potentiality of the proposed procedure. Finally, the utilized results show that the present method and simulated annealing provide a good scheduling methodology to solve such fuzzy equations.

     

Topology-Preserving Conditions for 2D Digital Images Under Rigid Transformations

In the continuous domain $\mathbb{R}^{n}$ , rigid transformations are topology-preserving operations. Due to digitization, this is not the case when considering digital images, i.e., images defined on $\mathbb{Z}^{n}$ . In this article, we begin to investigate this problem by studying conditions for digital images to preserve their topological properties under all rigid transformations on $\mathbb{Z}^{2}$ . Based on (i) the recently introduced notion of DRT graph, and (ii) the notion of simple point, we propose an algorithm for evaluating digital images topological invariance.     

Error quantification of the normalised right graph symbol for an errors-in-variables system

This paper proposes a novel method to quantify the error of a nominal normalized right graph symbol (NRGS) for an errors-in-variables (EIV) system corrupted with bounded noise. Following an identification framework for estimation of a perturbation model set, a worst-case v-gap error bound for the estimated nominal NRGS can be first determined from \textit{a priori} and \textit{a posteriori} information on the underlying EIV system. Then, an NRGS perturbation model set can be derived from a close relation between the v-gap metric of two models and ${\rm H}_\infty$-norm of their NRGSs' difference. The obtained NRGS perturbation model set paves the way for robust controller design using an ${\rm H}_\infty$ loop-shaping method because it is a standard form of the well-known NCF (normalized coprime factor) perturbation model set. Finally, a numerical simulation is used to demonstrate the effectiveness of the proposed identification method.     

Matching Polyhedral Terrains Using Overlays of Envelopes

For a collection $\F$ of $d$-variate piecewise linear functions of overall combinatorial complexity $n$, the lower envelope $\E(\F)$ of $\F$ is the pointwise minimum of these functions. The minimization diagram $\M(\F)$ is the subdivision of $\reals^d$ obtained by vertically (i.e., in direction $x_{d+1}$) projecting $\E(\F)$. The overlay $\O(\F,\G)$ of two such subdivisions $\M(\F)$ and $\M(\G)$ is their superposition. We extend and improve the analysis of de Berg et al. \cite{bgh-vdt3s-96} by showing that the combinatorial complexity of $\O(\F,\G)$ is $\Omega(n^d \alpha^{2}(n))$ and $O(n^{d+\eps})$ for any $\eps>0$ when $d \ge 2$, and $O(n^2 \alpha(n) \log n)$ when $d=2$. We also describe an algorithm that constructs $\O(\F,\G)$ in this time. We apply these results to obtain efficient general solutions to the problem of matching two polyhedral terrains in higher dimensions under translation. That is, given two piecewise linear terrains of combinatorial complexity $n$ in $\reals^{d+1}$, we wish to find a translation of the first terrain that minimizes its distance to the second, according to some distance measure. For the perpendicular distance measure, which we adopt from functional analysis since it is natural for measuring the similarity of terrains, we present a matching algorithm that runs in time $O(n^{2d+\eps})$ for any $\eps>0$. Sharper running time bounds are shown for $d \le 2$. For the directed and undirected \Hd\ distance measures, we present a matching algorithm that runs in time $O(n^{d^2+d+\eps})$ for any $\eps>0$.     

An extended nonsymmetric block Lanczos method for model reduction in large scale dynamical systems

In this paper, we propose an extended block Krylov process to construct two biorthogonal bases for the extended Krylov subspaces \(\mathbb {K}_{m}^e(A,V)\) and \(\mathbb {K}_{m}^e(A^{T},W)\), where \(A \in \mathbb {R}^{n \times n}\) and \(V,~W \in \mathbb {R}^{n \times p}\). After deriving some new theoretical results and algebraic properties, we apply the proposed algorithm with moment matching techniques for model reduction in large scale dynamical systems. Numerical experiments for large and sparse problems are given to show the efficiency of the proposed method.     

Weighted Matching in the Semi-Streaming Model

We present an approximation algorithm to find a weighted matching of a graph in the one-pass semi-streaming model. The semi-streaming model forbids random access to the input graph and restricts the memory to ${\mathcal{O}}(n\cdot\operatorname{polylog}n)$ bits where n denotes the number of the vertices of the input graph. We obtain an approximation ratio of 5.58 while the previously best algorithm achieves a ratio of 5.82.     

Globally optimal quadratic Lyapunov functions for robust stability of systems with structured uncertainty

The robust stability problem for a nominally linear system with nonlinear, time-varying structured perturbations is considered. The system is of the form $$\dot x = A_N x + \sum\limits_{j = 1}^q { p_j A_j x} $$ The Lyapunov direct method has been often utilized to determine the bounds for nonlinear, time-dependent functions p_j which can be tolerated by a stable nominal system. In most cases quadratic forms are used either as components of vector Lyapunov function or as a function itself. The resulting estimates are usually conservative. Optimizing the Lyapunov function reduces the conservatism of the bounds. The main result of this article is a theorem formulating the necessary and sufficient conditions for a quadratic Lyapunov function to be globally optimal. The theorem is constructive and makes it possible to propose a recursive procedure of a design of optimal Lyapunov function. Examples demonstrate application of the proposed method.     

Convergence to Suitable Weak Solutions for a Finite Element Approximation of the Navier–Stokes Equations with Numerical Subgrid Scale Modeling

In this article, a Galerkin finite element approximation for a class of time–space fractional differential equation is studied, under the assumption that \(u_{tt}, u_{ttt}, u_{2\alpha ,tt}\) are continuous for \(\varOmega \times (0,T]\), but discontinuous at time \(t=0\). In spatial direction, the Galerkin finite element method is presented. And in time direction, a Crank–Nicolson time-stepping is used to approximate the fractional differential term, and the product trapezoidal method is employed to treat the temporal fractional integral term. By using the properties of the fractional Ritz projection and the fractional Ritz–Volterra projection, the convergence analyses of semi-discretization scheme and full discretization scheme are derived separately. Due to the lack of smoothness of the exact solution, the numerical accuracy does not achieve second order convergence in time, which is \(O(k^{3-\beta }+k^{3}t_{n+1}^{-\beta }+k^{3}t_{n+1}^{-\beta -1})\), \(n=0,1,\ldots ,N-1\). But the convergence order in time is shown to be greater than one. Numerical examples are also included to demonstrate the effectiveness of the proposed method.     

New directions in distributed Nash equilibrium seeking based on monotone operator theory

There has been an increasing research interest in modeling, optimization and control of various multi-agent networks that have wide applications in industry, defense, security, and social areas, such as computing clusters, interconnected micro-grid systems, unmanned vessel swarms \cite{ChenJie}, power systems\cite{MeiS}, multiple UAV systems\cite{KolaricP} and sensor networks\cite{LiuR}. For non-cooperative agents that only concern selfish profit-maximizing, the decision making problem can be modelled and solved with the help of game theory, while Nash equilibrium (NE) seeking is at the core to solve the non-cooperative multi-agent games \cite{HenrikSandberg, IsraelAlvarez, Jong-ShiPang}. Distributed NE seeking methods are appealing compared with the center-based methods in large-scale networks due to its scalability, privacy protection, and adaptability. Recently, monotone operator theory is explored for distributed NE seeking, which is shown to provide an uniform framework for various algorithms in different scenarios. It has been gradually developing into a cutting-edge research field, with the prospect and necessity of future in-depth research. In non-cooperative multi-agent games, each agent has different characteristics and pursues maximizing its own benefit. Hence, there is no centralized manager that can force all agents to adopt specified strategies to optimize the overall benefits. Under the NE, no player can decrease its cost by unilaterally changing its local decision to another feasible one. To seek an NE, the agent is required to optimize its own objective function given the opponent''s countermeasures. Therefore, various optimization-based methods have been investigated for distributed NE seeking, such as the gradient flow method and the best response method....     

The Gaussian Surface Area and Noise Sensitivity of Degree-d Polynomial Threshold Functions

We prove asymptotically optimal bounds on the Gaussian noise sensitivity and Gaussian surface area of degree-d polynomial threshold functions. In particular, we show that for f a degree-d polynomial threshold function that the Gaussian noise sensitivity of f with parameter e{\epsilon} is at most \fracdarcsin(?{2e-e²})p{\frac{d\arcsin\left(\sqrt{2\epsilon-\epsilon^2}\right)}{\pi}} . This bound translates into an optimal bound on the Gaussian surface area of such functions, namely that the Gaussian surface area is at most \fracd?{2p}{\frac{d}{\sqrt{2\pi}}} . Finally, we note that the later result implies bounds on the runtime of agnostic learning algorithms for polynomial threshold functions.     

Collapse of the Hierarchy of Constant-Depth Exact Quantum Circuits

We study the quantum complexity class \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) of quantum operations implementable exactly by constant-depth polynomial-size quantum circuits with unbounded fan-out gates. Our main result is that the quantum OR operation is in \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\), which is an affirmative answer to the question posed by Høyer and ?palek. In sharp contrast to the strict hierarchy of the classical complexity classes: \({\mathsf{NC}^{0} \subsetneq \mathsf{AC}^{0} \subsetneq \mathsf{TC}^{0}}\), our result with Høyer and ?palek’s one implies the collapse of the hierarchy of the corresponding quantum ones: \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}=\mathsf{QAC}^\mathsf{0}_\mathsf{f}=\mathsf{QTC}^\mathsf{0}_\mathsf{f}}\). Then, we show that there exists a constant-depth subquadratic-size quantum circuit for the quantum threshold operation. This allows us to obtain a better bound on the size difference between the \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) and \({\mathsf{QTC}^\mathsf{0}_\mathsf{f}}\) circuits for implementing the same operation. Lastly, we show that, if the quantum Fourier transform modulo a prime is in \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\), there exists a polynomial-time exact classical algorithm for a discrete logarithm problem using a \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) oracle. This implies that, under a plausible assumption, there exists a classically hard problem that is solvable exactly by a \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) circuit with gates for the quantum Fourier transform.     

Data Parallel Implementation of Belief Propagation in Factor Graphs on Multi-core Platforms

We investigate data parallel techniques for belief propagation in acyclic factor graphs on multi-core systems. Belief propagation is a key inference algorithm in factor graph, a probabilistic graphical model that has found applications in many domains. In this paper, we explore data parallelism for basic operations over the potential tables in belief propagation. Data parallel techniques for these table operations are developed for shared memory platforms. We then propose a complete belief propagation algorithm using these table operations to perform exact inference in factor graphs. The proposed algorithms are implemented on state-of-the-art multi-socket multi-core systems with additional NUMA-aware optimizations. Our proposed algorithms exhibit good scalability using a representative set of factor graphs. On a four-socket Intel Westmere-EX system with 40 cores, we achieve 39.5 $\times $ speedup for the table operations and 39 $\times $ speedup for the complete algorithm using factor graphs with large potential tables.     

Parallel exact inference on the Cell Broadband Engine processor

We present the design and implementation of a parallel exact inference algorithm on the Cell Broadband Engine (Cell BE) processor, a heterogeneous multicore architecture. Exact inference is a key problem in exploring probabilistic graphical models, where the computation complexity increases dramatically with the network structure and clique size. In this paper, we exploit parallelism in exact inference at multiple levels. We propose a rerooting method to minimize the critical path for exact inference, and an efficient scheduler to dynamically allocate SPEs. In addition, we explore potential table representation and layout to optimize DMA transfer between local store and main memory. We implemented the proposed method and conducted experiments on the Cell BE processor in the IBM QS20 Blade. We achieved speedup up to 10 × on the Cell, compared to state-of-the-art processors. The methodology proposed in this paper can be used for online scheduling of directed acyclic graph (DAG) structured computations.     

Branching Time Logics \mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha } with Operations Until and Since Based on Bundles of Integer Numbers, Logical Consecutions, Deciding Algorithms

This paper is intended as an attempt to describe logical consequence in branching time logics. We study temporal branching time logics $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ which use the standard operations Until and Next and dual operations Since and Previous (LTL, as standard, uses only Until and Next). Temporal logics $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ are generated by semantics based on Kripke/Hinttikka structures with linear frames of integer numbers $\mathcal {Z}$ with a single node (glued zeros). For $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ , the permissible branching of the node is limited by α (where 1≤α≤ω). We prove that any logic $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ is decidable w.r.t. admissible consecutions (inference rules), i.e. we find an algorithm recognizing consecutions admissible in $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ . As a consequence, it implies that $\mathcal {BTL}^{\mathrm {U,S}}_{\mathrm {N},\mathrm {N}^{-1}}(\mathcal {Z})_{\alpha }$ itself is decidable and solves the satisfiability problem.