@article {17930,
	title = {Parallel, stochastic measurement of molecular surface area},
	journal = {Journal of Molecular Graphics and Modelling},
	volume = {27},
	year = {2008},
	month = {2008/08//},
	pages = {82 - 87},
	abstract = {Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited.We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering.
We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.
},
	keywords = {gpu, Molecular surface, Parallel, Progressive, Quasi-random, Stochastic},
	isbn = {1093-3263},
	doi = {10.1016/j.jmgm.2008.03.001},
	url = {http://www.sciencedirect.com/science/article/pii/S1093326308000387},
	author = {Juba,Derek and Varshney, Amitabh}
}
@article {12242,
	title = {A Unified Framework for Multipath Routing for Unicast and Multicast Traffic},
	journal = {Networking, IEEE/ACM Transactions on},
	volume = {16},
	year = {2008},
	month = {2008/10//},
	pages = {1038 - 1051},
	abstract = {We study the problem of load balancing the traffic from a set of unicast and multicast sessions. The problem is formulated as an optimization problem. However, we assume that the gradient of the network cost function is not available and needs to be estimated. Multiple paths are provided between a source and a destination using application-layer overlay. We propose a novel algorithm that is based on what is known as simultaneous perturbation stochastic approximation and utilizes only noisy measurements collected and reported to the sources, using an overlay architecture. We consider three network models that reflect different sets of assumptions regarding multicast capabilities of the network. Using an analytical model we first prove the almost sure convergence of the algorithm to a corresponding optimal solution under each network model considered in this paper with decreasing step sizes. Then, we establish the weak convergence (or convergence in distribution) with a fixed step size. In addition, we investigate the benefits acquired from implementing additional multicast capabilities by studying the relative performance of our algorithm under the three network models.},
	keywords = {application-layer, approximation;unicast, balancing;multicast, channels;stochastic, communication;multipath, cost, function;optimization, network, overlay;load, perturbation, problem;simultaneous, processes;telecommunication, routing;network, routing;telecommunication, Stochastic, traffic;, traffic;multicast, traffic;multipath},
	isbn = {1063-6692},
	doi = {10.1109/TNET.2007.909686},
	author = {Guven,T. and La,R.J. and Shayman,M.A. and Bhattacharjee, Bobby}
}
@article {15745,
	title = {Efficient iterative algorithms for the stochastic finite element method with application to acoustic scattering},
	journal = {Computer Methods in Applied Mechanics and Engineering},
	volume = {194},
	year = {2005},
	month = {2005/03/18/},
	pages = {1037 - 1055},
	abstract = {In this study, we describe the algebraic computations required to implement the stochastic finite element method for solving problems in which uncertainty is restricted to right-hand side data coming from forcing functions or boundary conditions. We show that the solution can be represented in a compact outer product form which leads to efficiencies in both work and storage, and we demonstrate that block iterative methods for algebraic systems with multiple right-hand sides can be used to advantage to compute this solution. We also show how to generate a variety of statistical quantities from the computed solution. Finally, we examine the behavior of these statistical quantities in one setting derived from a model of acoustic scattering.},
	keywords = {01, 28, 60, finite element, multigrid, Multiple right-hand side, Scattering, Stochastic},
	isbn = {0045-7825},
	doi = {10.1016/j.cma.2004.06.028},
	url = {http://www.sciencedirect.com/science/article/pii/S0045782504003123},
	author = {Elman, Howard and Ernst, Oliver G. and O{\textquoteright}Leary,Dianne P. and Stewart, Michael}
}
@conference {12280,
	title = {Measurement-based multipath multicast},
	booktitle = {INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE},
	volume = {4},
	year = {2005},
	month = {2005/03//},
	pages = {2803 - 2808 vol. 4 - 2803 - 2808 vol. 4},
	abstract = {We propose a measurement-based routing algorithm to load balance intradomain traffic along multiple paths for multiple multicast sources. Multiple paths are established using application-layer overlaying. The proposed algorithm is able to converge under different network models, where each model reflects a different set of assumptions about the multicasting capabilities of the network. The algorithm is derived from simultaneous perturbation stochastic approximation and relies only on noisy estimates from measurements. Simulation results are presented to demonstrate the additional benefits obtained by incrementally increasing the multicasting capabilities.},
	keywords = {algorithm;, allocation;, application-layer, approximation, approximation;, balance, communication;, Convergence, convergence;, intradomain, load, measurement-based, methods;, Multicast, multipath, network, numerical, of, overlaying;, perturbation, processes;, resource, Routing, routing;, source;, Stochastic, techniques;, Telecommunication, theory;, traffic;},
	doi = {10.1109/INFCOM.2005.1498566},
	author = {Guven,T. and La,R.J. and Shayman,M.A. and Bhattacharjee, Bobby}
}
@conference {12291,
	title = {Measurement based optimal multi-path routing},
	booktitle = {INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies},
	volume = {1},
	year = {2004},
	month = {2004/03//},
	pages = {187 - 196},
	abstract = {We propose a new architecture for efficient network monitoring and measurements in a traditional IP network. This new architecture enables establishment of multiple paths (tunnels) between source-destination pairs without having to modify the underlying routing protocol(s). Based on the proposed architecture we propose a measurement-based multipath routing algorithm derived from simultaneous perturbation stochastic approximation. The proposed algorithm does not assume that the gradient of analytical cost function is known to the algorithm, but rather relies on noisy estimates from measurements. Using the analytical model presented in the paper we prove the convergence of the algorithm to the optimal solution. Simulation results are presented to demonstrate the advantages of the proposed algorithm under a variety of network scenarios. A comparative study with an existing optimal routing algorithm, MATE, is also provided},
	keywords = {algorithm;network, approximation;routing, IP, measurement;network, monitoring;optimization;perturbation, multipath, network;measurement-based, networks;Internet;optimisation;routing, processes;, protocol;IP, protocols;stochastic, Routing, Stochastic},
	doi = {10.1109/INFCOM.2004.1354493},
	author = {Guven,T. and Kommareddy,C. and La,R.J. and Shayman,M.A. and Bhattacharjee, Bobby}
}
@conference {12684,
	title = {Simultaneous background and foreground modeling for tracking in surveillance video},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1053 - 1056 Vol.2 - 1053 - 1056 Vol.2},
	abstract = {We present a stochastic tracking algorithm for surveillance video where targets are dim and at low resolution. The algorithm builds motion models for both background and foreground by integrating motion and intensity information. Some other merits of the algorithm include adaptive selection of feature points for scene description and defining proper cost functions for displacement estimation. The experimental results show tracking robustness and precision in a challenging video sequences.},
	keywords = {algorithm;, analysis;, background-foreground, displacement, estimation;, image, information;, INTENSITY, modeling;, MOTION, processes;, processing;, resolution;, sequences;, signal, Stochastic, Surveillance, surveillance;, tracking, tracking;, video},
	doi = {10.1109/ICIP.2004.1419483},
	author = {Shao, J. and Zhou,S. K and Chellapa, Rama}
}
@article {12699,
	title = {Wide baseline image registration with application to 3-D face modeling},
	journal = {Multimedia, IEEE Transactions on},
	volume = {6},
	year = {2004},
	month = {2004/06//},
	pages = {423 - 434},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles is a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, three-dimensional (3-D) model alignment, creation of panoramic views, etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching two-dimensional (2-D) shapes of the different features of the face (e.g., eyes, nose etc.). A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellation of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3-D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, baseline, biometrics;, Computer, configuration;, correspondence, doubly, error, extraction;, Face, feature, holistic, image, matching;, matrix;, minimization;, modeling;, models;, normalization, probability, probability;, procedure;, processes;, processing;, recognition;, registration;, representation;, sequences;, shapes;, Sinkhorn, spatial, statistics;, Stochastic, video, vision;, wide},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2004.827511},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama and Keaton, T.}
}
@conference {12747,
	title = {Wide baseline image registration using prior information},
	booktitle = {Multimedia Signal Processing, 2002 IEEE Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {37 - 40},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles in a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, 3D model alignment, creation of panoramic views etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching 2D shapes of the different features of the face. A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellations of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, alignment;, angles;, baseline, Computer, configuration;, constellation;, correspondence, creation;, doubly, error, extraction;, Face, feature, global, holistic, image, images;, matching;, matrix;, model, models;, normalization, panoramic, probability;, procedure;, processes;, processing;, registration;, robust, sequences;, SHAPE, signal, Sinkhorn, spatial, statistics;, stereo;, Stochastic, video, view, viewing, vision;, wide},
	doi = {10.1109/MMSP.2002.1203242},
	author = {Chowdhury, AM and Chellapa, Rama and Keaton, T.}
}
@conference {14855,
	title = {Stochastic completion fields: a neural model of illusory contour shape and salience},
	booktitle = {Computer Vision, 1995. Proceedings., Fifth International Conference on},
	year = {1995},
	month = {1995/06//},
	pages = {408 - 415},
	abstract = {We describe an algorithm and representation level theory of illusory contour shape and salience. Unlike previous theories, our model is derived from a single assumption-namely, that the prior probability distribution of boundary completion shape can be modeled by a random walk in a lattice whose points are positions and orientations in the image plane (i.e. the space which one can reasonably assume is represented by neurons of the mammalian visual cortex). Our model does not employ numerical relaxation or other explicit minimization, but instead relies on the fact that the probability that a particle following a random walk will pass through a given position and orientation on a path joining two boundary fragments can be computed directly as the product of two vector-field convolutions. We show that for the random walk we define, the maximum likelihood paths are curves of least energy, that is, on average, random walks follow paths commonly assumed to model the shape of illusory contours. A computer model is demonstrated on numerous illusory contour stimuli from the literature},
	keywords = {boundary, completion, computational, Computer, contour, contours;, convolutions;, cortex;, curves, detection;, distribution;, edge, energy;, estimation;, fields;, fragments;, geometry;, illusory, image, lattice;, least, likelihood, mammalian, maximum, model;, nets;, neural, of, paths;, plane;, probability, probability;, random, recognition;, shape;, stimuli;, Stochastic, vector-field, visual, walk;},
	doi = {10.1109/ICCV.1995.466910},
	author = {Williams,L. R and Jacobs, David W.}
}
