Showing papers on "Bounding overwatch published in 2003"

A bounding chain for Swendsen-Wang

Abstract: The greatest drawback of Monte Carlo Markov chain methods is lack of knowledge of the mixing time of the chain. The use of bounding chains solves this difficulty for some chains by giving theoretical and experimental upper bounds on the mixing time. Moreover, when used with methodologies such as coupling from the past, bounding chains allow the user to take samples drawn exactly from the stationary distribution without knowledge of the mixing time. Here we present a bounding chain for the Swendsen-Wang process. The Swendsen-Wang bounding chain allow us to efficiently obtain exact samples from the ferromagnetic Q-state Potts model for certain classes of graphs. Also, by analyzing this bounding chain, we will show that Swendsen-Wang is rapidly mixing over a slightly larger range of parameters than was known previously.

Efficient Collision Detection for Models Deformed by Morphing

Abstract: We describe a fast and accurate collision-detection algorithm specialised for models deformed by morphing. The models considered are meshes where the vertex positions are convex combinations of sets of reference meshes. This new method is based on bounding-volume trees that are extended to support efficient tree-node updates by blending associated sets of reference bounding volumes. With our approach, it is possible to use either axis-aligned bounding boxes, discrete-orientation polytopes, or spheres as bounding volumes. The expected performance of our algorithm is of the same order as for rigid hierarchical collision detection. In our tested scenarios, the speed-up we achieved ranged from 1.5 to 58, compared to another more general algorithm for deforming bodies.

New Interval Analysis Support Functions Using Gradient Information in a Global Minimization Algorithm

Abstract: The performance of interval analysis branch-and-bound global optimization algorithms strongly depends on the efficiency of selection, bounding, elimination, division, and termination rules used in their implementation. All the information obtained during the search process has to be taken into account in order to increase algorithm efficiency, mainly when this information can be obtained and elaborated without additional cost (in comparison with traditional approaches). In this paper a new way to calculate interval analysis support functions for multiextremal univariate functions is presented. The new support functions are based on obtaining the same kind of information used in interval analysis global optimization algorithms. The new support functions enable us to develop more powerful bounding, selection, and rejection criteria and, as a consequence, to significantly accelerate the search. Numerical comparisons made on a wide set of multiextremal test functions have shown that on average the new algorithm works almost two times faster than a traditional interval analysis global optimization method.

Bounding the generalization error of convex combinations of classifiers: balancing the dimensionality and the margins

Abstract: A problem of bounding the generalization error of a classifier %\break $f\in \conv(\mathcal{H})$, where $\mathcal{H}$ is a "base" class of functions (classifiers), is considered. This problem frequently occurs in computer learning, where efficient algorithms that combine simple classifiers into a complex one (such as boosting and bagging) have attracted a lot of attention. Using Talagrand's concentration inequalities for empirical processes, we obtain new sharper bounds on the generalization error of combined classifiers that take into account both the empirical distribution of "classification margins" and an "approximate dimension" of the classifiers, and study the performance of these bounds in several experiments with learning algorithms.

Strategies for Bounding Volume Hierarchy Updates for Ray Tracing of Deformable Models

Abstract: In this paper, we describe strategies for bounding volume hierarchy updates for ray tracing of deformable models. By using pre-built hierarchy structures and a lazy evaluation technique for updating the bounding volumes, the hierarchy reconstruction can be made very ecien tly. Experiments show that for deforming triangle meshes the reconstruction time of the bounding volume hierarchies per frame can be reduced by an order of magnitude compared to previous approaches, which also results in a signican t speed-up in the total rendering time for many types of dynamically changing scenes. We believe our approach is a step towards interactive ray tracing of scenes where moving objects can be dynamically changed in non-deterministic ways.

Easy realignment of k-dop bounding volumes

Abstract: In this paper we reconsider pairwise collision detection for rigid motions using a k-DOP bounding volume hierarchy. This data structure is particularly attractive because it is equally efficient for rigid motions as for arbitrary point motions (deformations). We propose a new efficient realignment algorithm, which produces tighter results compared to all known algorithms. It can be implemented easily in software and in hardware. Using this approach we try to show, that k-DOP bounding volumes can keep up with the theoretically more efficient oriented bounding boxes (OBBs) in parallel-close-proximity situations.

Bounding recursive procedural models using convex optimization

Abstract: We present an algorithm to construct a tight bounding polyhedron for a recursive procedural model. We first use an iterated function system (IFS) to represent the extent of the procedural model. Then we present an algorithm that expresses the IFS-bounding problem as a set of linear convex optimization. As such, our algorithm is guaranteed to find the recursively optimal bounding polyhedron, if it exists. Finally, we demonstrate examples of this algorithm on two and three dimensional recursive procedural models.

Faster clears for three-dimensional modeling applications

Abstract: A graphics processing subsystem defines a bounding area as the portion of the display buffer and other memory buffers occupied by one or more rendered objects. When clearing the memory buffers, only the portions of the buffers corresponding to the bounding area need to be cleared. A graphics pipeline includes a bounding area memory to store bounding area values. The bounding area values are modified during rendering so that each rendered primitive falls within the bounding area values. The graphics processing subsystem clears a portion of the memory buffer in response to a clear command specifying a bounding area. The clear command may include a set of bounding area values defining the bounding area, or alternatively a reference to the bounding area memory. For applications that draw objects in isolation, the bounding area will be smaller than the window, resulting in a decreased time requirement for clearing the memory buffer.

Set simulations for quadratic systems

Abstract: In this paper, we study the problem of propagating in time a bounding set for the state of a class of nonlinear quadratic systems. The sequence of bounding sets is called the set simulation of the system, and conveys useful information about the stability and qualitative behavior of the possible time responses of the system. Numerically, efficient recursive algorithms are presented for the specific cases when the bounding sets are orthotopes or ellipsoids.

Discrepancy-based additive bounding for the AllDifferent constraint

Abstract: In this paper we show how to exploit in Constraint Programming (CP) a well-known integer programming technique, the additive bounding procedure, when using Limited Discrepancy Search (LDS). LDS is an effective search strategy based on the concept of discrepancy, i.e., a branching decision which does not follow the suggestion of a given heuristic. The property of a node to have an associated discrepancy k can be modeled (and enforced) through a constraint, called k-discrepancy constraint. Our key result is the exploitation of the k-discrepancy constraint to improve the bound given by any relaxation of a combinatorial optimization problem by using the additive bounding idea. We believe that this simple idea can be effectively exploited to tighten relaxations in CP solvers and speed up the proof of optimality. The general use of additive bounding in conjunction with LDS has been presented in [14]. Here we focus on a particular case where the AllDifferent constraint is part of the CP model. In this case, the integration of additive bound in CP is particularly effective.

Bounding the cardinality of aggregate views through domain-derived constraints

Abstract: Accurately estimating the cardinality of aggregate views is crucial for logical and physical design of data warehouses. This paper proposes an approach based on cardinality constraints, derived a-priori from the application domain, which may bound either the cardinality of a view or the ratio between the cardinalities of two views. We face the problem by first computing satisfactory bounds for the cardinality, then by capitalizing on these bounds to determine a good probabilistic estimate for it. In particular, we propose a bounding strategy which achieves an effective trade-off between the tightness of the bounds produced and the computational complexity.

Transmission line bounding models

Abstract: A method, apparatus, system, and signal-bearing medium that in an embodiment select a subset of transmission line models based on bounding electrical criteria. The bounding electrical criteria may include combinations of maximum and minimum values and in an embodiment may also include nominal values. Models that meet the bounding electrical criteria may be used in modeling the transmission line while models that do not meet the bounding electrical criteria are not used.

Sparse data and rule base completion

Abstract: Several techniques have been proposed for making inferences using the information contained in an incomplete rule base. These fall into three major categories; interpolative reasoning, analogical inference, and rule base completion. Interpolation uses the relative locations and shapes of the fuzzy sets in a pair of bounding rules to construct an output when an input occurs between the antecedents of the bounding rules. Analogical inference employs similarity to a single proximate example to produce the output. Completion generates a set of rules whose antecedents link the antecedents of the bounding rules. In this paper we compare the underlying principles of interpolation, analogical inference, and rule base completion. In addition, we propose a completion technique that partitions the domain between the antecedents of the bounding rules. The size of the partition is determined by the variation between fuzzy regions specified by the bounding rules.

An optimal algorithm for the parameter identification of MIMO linear systems using bounding ellipsoids

Abstract: This contribution proposes a recursive and easily implementable online algorithm for the parameters estimation of linear multi-output systems using ellipsoidal bounds on the unknown observation noises. A simple approach based on parameters bounding techniques is presented. A particular /spl omega/-parameterization of the algorithm is used, first to characterize, at each step, the set containing all possible values of the true parameters consistent with input/output data and the noises' bounds and also to guaranty the convergence of the estimated parameters to some neighborhood of their true values. A rigorous convergence analysis is performed and a number of algorithm's properties are highlighted such as the decrease of the normed estimation error, the shrinkage of the parameters outer-bounding set and the acceptability of the output error. Finally, the theoretical results are illustrated by a numerical simulation on a simple example.

Validating complex agent behavior

Abstract: Developing software agents that replicate human behavior, even within a narrow domain, is a time consuming and error prone process. The most widely used methodology for designing these agents is based on the complementary processes of knowledge acquisition and validation, both of which have been cited as significant bottlenecks. In this thesis, we identify two methods for comparing actors' behavior that have the potential to decrease the cost of validation. The first is a simple sequence-based approach that can be used to compare many different aspects of two actors' behavior. Although initially promising, our empirical and analytical analysis exposes significant limitations with this general class of approaches, especially as the complexity of the domain increases. As a result, we turn to a novel comparison approach that we call behavior bounding. Unlike the sequential approaches, behavior bounding uses a concise representation of an actor's aggregate behavior as a basis for performing its comparison. We show that behavior bounding requires minimal human effort to use and that its representation of behavior is efficient to construct and maintain even as the complexity of the environment increases. Furthermore, we show that behavior bounding outperforms the sequential comparison approach in two domains of distinct complexity. Finally, we provide empirical evidence that behavior bounding's summary of the differences in two actors' behavior can be used to significantly speed up the knowledge validation process.

Adaptive Set-Membership State Estimation with Optimal Bounding Ellipsoid

Abstract: The problem for recursive estimation of state bounding of a discrete time linear dynamic system in ellipsoidal sets is addressed. A novel method based on optimal bounding ellipsoid (OBE) algorithmic procedure at each stage of updating is presented to improve computational efficiency and practicability. Simulation results and performance comparisons with ROBP algorithm and Kalman filter are also given.

New algorithm for parallelotope updating in output error bounding

Abstract: This paper proposes a new algorithm for updating an outer bounding parallelotope of the exact feasible parameter set when the model output error is unknown but bounded. The proposed method consists of a reformulation of the method proposed by A. Vicino and G. Zappa (IEEE Trans. Automatic Control, vol. 41, no. 6, pp. 774-784, 1996) for parallelotope updating when the model equation error is bounded, taking into account the constraints resulting from model output error bounding.

Semi-independent partitioning: a method for bounding the solution to COP's

Abstract: In this paper we introduce a new method for bounding the solution to constraint optimization problems called semi-independent partitioning We show that our method is a strict generalization of the mini buckets algorithm [1] We demonstrate empirically that another specialization of SIP, called greedy SIP, generally produces a better answer than mini buckets in much less time

보존 경계 사각형을 이용한 이동객체의 현재와 미래 위치 색인

Abstract: Nowadays, with numerous emerging applications (e.g., traffic control, meteorology monitoring, mobile computing, etc.), access methods to process current and future queries for moving objects are becoming increasingly important. Among these methods, the time-parameterized R-tree (TPR-tree) seems likely the most flexible method in one, two, or three-dimensional space. A key point of TPR-tree is that the (conservative) bounding rectangles are expressed by functions of time. In this paper, we propose a new method, which takes into account positions of its moving objects against the rectangle's bounds. In proposed method, the size of bounding rectangle is significantly smaller than the traditional bounding rectangle in many cases. By this approach, we believe that the TPR-tree can improve query performance considerably.

Orthotopic and ellipsoidal simulations for a class of non-linear systems

Abstract: In this paper, we address the problem of propagating in time an orthotopic or ellipsoidal bounding set for the state of discrete-time quadratic systems The sequence of bounding sets is called the set simulation of the system, and conveys useful information about the stability and other qualitative behaviors of the possible trajectories of the system The bounding sets are computed recursively via numerically efficient algorithms