作者:
S. MoazeniApplied Math
Department of Mathematics and Computer Science Tehran Polytechnic Amirkabir University of Technology슠 Tehran Iran
We discuss the problem of finding the shortest paths from a fixed origin to all nodes on a network not necessarily acyclic, with each arc length represented as positive fuzzy quantity with finite support. At first, we...
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We discuss the problem of finding the shortest paths from a fixed origin to all nodes on a network not necessarily acyclic, with each arc length represented as positive fuzzy quantity with finite support. At first, we show that the only existing paper on this problem, Klein's algorithm, in some cases lead to a dominated path in the sense of extension principle and then we introduce a new algorithm for the problem. The proposed algorithm is on the basis of the multiple labeling methods of Hansen and Dijkstra's shortest path algorithm.
XP/Agile education and training remains a challenge from the perspective of determining relevant content;identifying effective methods for delivery;and maintaining the focus and motivation of students. This panel brin...
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We define nowhere dense and somewhere dense classes by means of counting of homomorphisms from test graphs. This seems to be bridging the gap between existential and counting theorems (for graph homomorphisms) and it ...
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In this work, a reservoir simulation approximation model (proxy) based on recurrent artificial neural networks is proposed. This model is intended to obtain rates of oil, gas and water production at time t+1 from the ...
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We give a development of universal lossy data compression based on a lossy version of the Kraft inequality. As an application, we evaluate the performance of universal mixture codebooks.
We give a development of universal lossy data compression based on a lossy version of the Kraft inequality. As an application, we evaluate the performance of universal mixture codebooks.
A method is presented to correct an approximate polygonal sketch of an image object boundary by adjusting the location of each corner point in the sketch. The method is suitable for the segmentation of unknown images ...
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A method is presented to correct an approximate polygonal sketch of an image object boundary by adjusting the location of each corner point in the sketch. The method is suitable for the segmentation of unknown images using interactive techniques, and for locating object boundaries in model-based segmentation. For each point, p, at which two lines meet in an open or closed polygonal sketch, a corner segmentation model is derived based on the angle, orientation and scale of the corner defined, and the image function f(x, y) in the immediate region about p. A corner template is then constructed and matched in a small neighborhood about p, thereby providing a corrected polygonal sketch. The segmentation model is correct in 95% of the cases, and the corner is accurately located.< >
Presents a method for the localization and interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expre...
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Presents a method for the localization and interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation during the interpretation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.< >
In many large economic markets, goods are sold through sequential auctions. Examples include eBay, online ad auctions, wireless spectrum auctions, and the Dutch flower auctions. In this paper, we combine methods from ...
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ISBN:
(纸本)9781627480031
In many large economic markets, goods are sold through sequential auctions. Examples include eBay, online ad auctions, wireless spectrum auctions, and the Dutch flower auctions. In this paper, we combine methods from game theory and decision theory to search for approximate equilibria in sequential auction domains, in which bidders do not know their opponents' values for goods, bidders only partially observe the actions of their opponents', and bidders demand multiple goods. We restrict attention to two-phased strategies: first predict (i.e., learn); second, optimize. We use best-reply dynamics [4] for prediction (i.e., to predict other bidders' strategies), and then assuming fixed other-bidder strategies, we estimate and solve the ensuing Markov decision processes (MDP) [18] for optimization. We exploit auction properties to represent the MDP in a more compact state space, and we use Monte Carlo simulation to make estimating the MDP tractable. We show how equilibria found using our search procedure compare to known equilibria for simpler auction domains, and we approximate an equilibrium for a more complex auction domain where analytical solutions are unknown.
We study a semi-random graph model for finding independent sets. For /spl alpha/>0, an n-vertex graph with an independent set S of site /spl alpha/n is constructed by blending random and adversarial decisions. Rand...
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We study a semi-random graph model for finding independent sets. For /spl alpha/>0, an n-vertex graph with an independent set S of site /spl alpha/n is constructed by blending random and adversarial decisions. Randomly and independently with probability p, each pair of vertices, such that one is in S and the other is not, is connected by an edge. An adversary can then add edges arbitrarily (provided that S remains an independent set). The smaller p is, the larger the control the adversary has over the semi-random graph. We design heuristics that with high probability recover S when p>(1+/spl epsiv/)ln n/|S|, for any constant /spl epsiv/>0. We show that when p
We propose an approach to distinguish between correct and incorrect image classifications. Our approach can detect misclassifications which either occur unintentionally ("natural errors"), or due to intentio...
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