%0 Conference Paper
%B Twelfth Annual Conference of the International Speech Communication Association
%D 2011
%T Kernel partial least squares for speaker recognition
%A Srinivasan,B.V.
%A Garcia-Romero,D.
%A Zotkin,Dmitry N
%A Duraiswami, Ramani
%X I-vectors are a concise representation of speaker characteristics. Recent advances in speaker recognition have utilized their ability to capture speaker and channel variability to develop efficient recognition engines. Inter-speaker relationships in the i-vector space are non-linear. Accomplishing effective speaker recognition requires a good modeling of these non-linearities and can be cast as a machine learning problem. In this paper, we propose a kernel partial least squares (kernel PLS, or KPLS) framework for modeling speakers in the i-vectors space. The resulting recognition system is tested across several conditions of the NIST SRE 2010 extended core data set and compared against state-of-the-art systems: Joint Factor Analysis (JFA), Probabilistic Linear Discriminant Analysis (PLDA), and Cosine Distance Scoring (CDS) classifiers. Improvements are shown.
%B Twelfth Annual Conference of the International Speech Communication Association
%8 2011///
%G eng
%0 Conference Paper
%B Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on
%D 2011
%T Kernel PLS regression for robust monocular pose estimation
%A Dondera,R.
%A Davis, Larry S.
%K (computer
%K 3D
%K analysis;rendering
%K correlations;projection
%K detection;monocular
%K detection;pose
%K estimation;Gaussian
%K estimation;nonlinear
%K estimation;regression
%K GP
%K graphics);
%K images;rendering
%K latent
%K monocular
%K PLS
%K pose
%K process;Kernel
%K processes;object
%K regression;Gaussian
%K regression;human
%K software;robust
%K structures;realistic
%K to
%X We evaluate the robustness of five regression techniques for monocular 3D pose estimation. While most of the discriminative pose estimation methods focus on overcoming the fundamental problem of insufficient training data, we are interested in characterizing performance improvement for increasingly large training sets. Commercially available rendering software allows us to efficiently generate large numbers of realistic images of poses from diverse actions. Inspired by recent work in human detection, we apply PLS and kPLS regression to pose estimation. We observe that kPLS regression incrementally approximates GP regression using the strongest nonlinear correlations between image features and pose. This provides robustness, and our experiments show kPLS regression is more robust than two GP-based state-of-the-art methods for pose estimation.
%B Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on
%P 24 - 30
%8 2011/06//
%G eng
%R 10.1109/CVPRW.2011.5981750
%0 Journal Article
%J Technical Reports of the Computer Science Department
%D 2011
%T Kernelized Renyi distance for subset selection and similarity scoring
%A Srinivasan,Balaji Vasan
%A Duraiswami, Ramani
%K Technical Report
%X Renyi entropy refers to a generalized class of entropies that have beenused in several applications. In this work, we derive a non-parametric distance between distributions based on the quadratic Renyi entropy. The distributions are estimated via Parzen density estimates. The quadratic complexity of the distance evaluation is mitigated with GPU-based parallelization. This results in an efficiently evaluated non-parametric entropic distance - the kernelized Renyi distance or the KRD. We adapt the KRD into a similarity measure and show its application to speaker recognition. We further extend KRD to measure dissimilarities between distributions and illustrate its applications to statistical subset selection and dictionary learning for object recognition and pose estimation.
%B Technical Reports of the Computer Science Department
%8 2011/10/12/
%G eng
%U http://drum.lib.umd.edu/handle/1903/12132
%0 Book Section
%B Integer Programming and Combinatorial OptimizationInteger Programming and Combinatorial Optimization
%D 2010
%T On k-Column Sparse Packing Programs
%A Bansal,Nikhil
%A Korula,Nitish
%A Nagarajan,Viswanath
%A Srinivasan, Aravind
%E Eisenbrand,Friedrich
%E Shepherd,F.
%X We consider the class of packing integer programs (PIPs) that are column sparse, where there is a specified upper bound k on the number of constraints that each variable appears in. We give an improved (ek + o(k))-approximation algorithm for k-column sparse PIPs. Our algorithm is based on a linear programming relaxation, and involves randomized rounding combined with alteration. We also show that the integrality gap of our LP relaxation is at least 2k − 1; it is known that even special cases of k-column sparse PIPs are (klogk)-hard to approximate.We generalize our result to the case of maximizing monotone submodular functions over k-column sparse packing constraints, and obtain an e2ke−1+o(k) -approximation algorithm. In obtaining this result, we prove a new property of submodular functions that generalizes the fractionally subadditive property, which might be of independent interest.
%B Integer Programming and Combinatorial OptimizationInteger Programming and Combinatorial Optimization
%S Lecture Notes in Computer Science
%I Springer Berlin / Heidelberg
%V 6080
%P 369 - 382
%8 2010///
%@ 978-3-642-13035-9
%G eng
%U http://dx.doi.org/10.1007/978-3-642-13036-6_28
%0 Conference Paper
%B Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
%D 2010
%T Kernelized Rényi distance for speaker recognition
%A Vasan Srinivasan,B.
%A Duraiswami, Ramani
%A Zotkin,Dmitry N
%K #x0301;nyi
%K approach;input
%K distance;reference
%K entropy;graphical
%K equipment;entropy;speaker
%K graphic
%K identification;speaker
%K processor;information
%K Re
%K recognition;
%K recognition;speaker
%K signals;kernelized
%K signals;speaker
%K theoretic
%K verification;computer
%X Speaker recognition systems classify a test signal as a speaker or an imposter by evaluating a matching score between input and reference signals. We propose a new information theoretic approach for computation of the matching score using the Re #x0301;nyi entropy. The proposed entropic distance, the Kernelized Re #x0301;nyi distance (KRD), is formulated in a non-parametric way and the resulting measure is efficiently evaluated in a parallelized fashion on a graphical processor. The distance is then adapted as a scoring function and its performance compared with other popular scoring approaches in a speaker identification and speaker verification framework.
%B Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
%P 4506 - 4509
%8 2010/03//
%G eng
%R 10.1109/ICASSP.2010.5495587
%0 Book Section
%B Wiley Handbook of Science and Technology for Homeland SecurityWiley Handbook of Science and Technology for Homeland Security
%D 2009
%T Knowledge Extraction from Surveillance Sensors
%A Chellapa, Rama
%A Veeraraghavan,Ashok
%A Sankaranarayanan,Aswin C.
%K multi‐camera tracking
%K multi‐modal fusion
%K recognition
%K sensor networks
%K Surveillance
%B Wiley Handbook of Science and Technology for Homeland SecurityWiley Handbook of Science and Technology for Homeland Security
%I John Wiley & Sons, Inc.
%8 2009///
%@ 9780470087923
%G eng
%U http://onlinelibrary.wiley.com/doi/10.1002/9780470087923.hhs510/abstract;jsessionid=D0D752EF5D04327BE003BDFBD2F96134.d01t03
%0 Conference Paper
%B Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
%D 2008
%T Kernel integral images: A framework for fast non-uniform filtering
%A Hussein,M.
%A Porikli, F.
%A Davis, Larry S.
%K approximated
%K equations;interpolation;
%K filtering;bilinear
%K filtering;kernel
%K Gaussian
%K graphics;computer
%K images;approximation
%K integral
%K interpolation;computer
%K nonuniform
%K processing;integral
%K theory;filtering
%K theory;image
%K vision;fast
%K weighting
%X Integral images are commonly used in computer vision and computer graphics applications. Evaluation of box filters via integral images can be performed in constant time, regardless of the filter size. Although Heckbert (1986) extended the integral image approach for more complex filters, its usage has been very limited, in practice. In this paper, we present an extension to integral images that allows for application of a wide class of non-uniform filters. Our approach is superior to Heckbertpsilas in terms of precision requirements and suitability for parallelization. We explain the theoretical basis of the approach and instantiate two concrete examples: filtering with bilinear interpolation, and filtering with approximated Gaussian weighting. Our experiments show the significant speedups we achieve, and the higher accuracy of our approach compared to Heckbertpsilas.
%B Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
%P 1 - 8
%8 2008/06//
%G eng
%R 10.1109/CVPR.2008.4587641
%0 Conference Paper
%B Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
%D 2007
%T Kernel fully constrained least squares abundance estimates
%A Broadwater, J.
%A Chellapa, Rama
%A Banerjee, A.
%A Burlina, P.
%K abundance
%K algorithm;kernel
%K analysis;
%K AVIRIS
%K based
%K constrained
%K constraint;feature
%K constraint;spectral
%K estimates;linear
%K extraction;geophysical
%K feature
%K fully
%K image;hyperspectral
%K imagery;kernel
%K least
%K mixing
%K model;nonnegativity
%K processing;geophysical
%K processing;multidimensional
%K processing;spectral
%K signal
%K space;kernel
%K squares
%K techniques;image
%K unmixing;sum-to-one
%X A critical step for fitting a linear mixing model to hyperspectral imagery is the estimation of the abundances. The abundances are the percentage of each end member within a given pixel; therefore, they should be non-negative and sum to one. With the advent of kernel based algorithms for hyperspectral imagery, kernel based abundance estimates have become necessary. This paper presents such an algorithm that estimates the abundances in the kernel feature space while maintaining the non-negativity and sum-to-one constraints. The usefulness of the algorithm is shown using the AVIRIS Cuprite, Nevada image.
%B Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
%P 4041 - 4044
%8 2007/07//
%G eng
%R 10.1109/IGARSS.2007.4423736
%0 Journal Article
%J IEEE transactions on pattern analysis and machine intelligence
%D 2007
%T K-nearest neighbor finding using MaxNearestDist
%A Samet, Hanan
%B IEEE transactions on pattern analysis and machine intelligence
%P 243 - 252
%8 2007///
%G eng
%0 Conference Paper
%B Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
%D 2007
%T Knowledge discovery using the sand spatial browser
%A Samet, Hanan
%A Phillippy,Adam
%A Sankaranarayanan,Jagan
%K distance semi-join
%K knowledge discovery
%K sand database system
%K snow cholera map
%X The use of the SAND Internet Browser as a knowledge discovery tool for epidemiological cartography is highlighted by recreating the results of Dr. John Snow's study of the 1854 Cholera epidemic in Soho, London.
%B Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
%S dg.o '07
%I Digital Government Society of North America
%P 284 - 285
%8 2007///
%@ 1-59593-599-1
%G eng
%U http://dl.acm.org/citation.cfm?id=1248460.1248521
%0 Conference Paper
%B Proceedings of the eighth Workshop on Algorithm Engineering and Experiments and the third Workshop on Analytic Algorithmics and Combinatorics
%D 2006
%T Keep Your Friends Close and Your Enemies Closer: The Art of Proximity Searching
%A Mount, Dave
%B Proceedings of the eighth Workshop on Algorithm Engineering and Experiments and the third Workshop on Analytic Algorithmics and Combinatorics
%V 123
%P 65 - 65
%8 2006///
%G eng
%0 Book Section
%B Computer Vision – ACCV 2006Computer Vision – ACCV 2006
%D 2006
%T Key Frame-Based Activity Representation Using Antieigenvalues
%A Cuntoor,Naresh
%A Chellapa, Rama
%E Narayanan,P.
%E Nayar,Shree
%E Shum,Heung-Yeung
%X Many activities may be characterized by a sequence of key frames that are related to important changes in motion rather than dominant characteristics that persist over a long sequence of frames. To detect such changes, we define a transformation operator at every time instant, which relates the past to the future states. One of the useful quantities associated with numerical range of an operator is the eigenvalue. In the literature, eigenvalue-based approaches have been studied extensively for many modeling tasks. These rely on gross properties of the data and are not suitable to detect subtle changes. We propose an antieigenvalue – based measure to detect key frames. Antieigenvalues depend critically on the turning of the operator, whereas eigenvalues represent the amount of dilation along the eigenvector directions aligned with the direction of maximum variance. We demonstrate its application to activity modeling and recognition using two datasets: a motion capture dataset and the UCF human action dataset.
%B Computer Vision – ACCV 2006Computer Vision – ACCV 2006
%S Lecture Notes in Computer Science
%I Springer Berlin / Heidelberg
%V 3852
%P 499 - 508
%8 2006///
%@ 978-3-540-31244-4
%G eng
%U http://dx.doi.org/10.1007/11612704_50
%0 Journal Article
%J Technical Reports from UMIACS, UMIACS-TR-2006-12
%D 2006
%T KeyChains: A Decentralized Public-Key Infrastructure
%A Morselli,Ruggero
%A Bhattacharjee, Bobby
%A Katz, Jonathan
%A Marsh,Michael A
%K Technical Report
%X A Certification Authority (CA) can be used to certify keys and build apublic-key infrastructure (PKI) when all users trust the same CA. A decentralized PKI trades off absolute assurance on keys for independence from central control and improved scalability and robustness. The PGP ``web of trust'' model has been suggested as a decentralized certification system, and has been used with great success for secure email. Although the PGP web of trust model allows anyone to issue certificates which can be used to form certificate chains, the discovery and construction of certificate chains relies on centralized keyservers to store certificates and respond to queries. In this paper, we design and implement KeyChains, a peer-to-peer system which incorporates a novel lookup mechanism specifically tailored to the task of generating and retrieving certificate chains in completely unstructured networks. By layering our system on top of the web of trust model, we thus obtain the first PKI which is truly decentralized in all respects. Our analysis and simulations show that the resulting system is both efficient and secure.
%B Technical Reports from UMIACS, UMIACS-TR-2006-12
%8 2006/03/02/
%G eng
%U http://drum.lib.umd.edu/handle/1903/3332
%0 Journal Article
%J IEEE Transactions on Visualization and Computer Graphics
%D 2006
%T Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework
%A Seo,Jinwook
%A Shneiderman, Ben
%K case study
%K Computer aided software engineering
%K Computer Society
%K Data analysis
%K data mining
%K data visualisation
%K Data visualization
%K database management systems
%K e-mail user survey
%K Genomics
%K Helium
%K Hierarchical Clustering Explorer
%K hierarchical clustering explorer.
%K high-dimensional data
%K Histograms
%K Information visualization evaluation
%K interactive systems
%K interactive tool
%K knowledge discovery
%K multivariate data
%K Rank-by-feature framework
%K Scattering
%K Testing
%K user interface
%K User interfaces
%K user survey
%K visual analytic tools
%K visual analytics
%K visualization tools
%X Knowledge discovery in high-dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our three-year effort to develop versions of the hierarchical clustering explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the hierarchical clustering explorer (HCE) using three case studies and an e-mail user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods
%B IEEE Transactions on Visualization and Computer Graphics
%V 12
%P 311 - 322
%8 2006/06//May
%@ 1077-2626
%G eng
%N 3
%R 10.1109/TVCG.2006.50
%0 Journal Article
%J ICML Workshop on Structural Knowledge Transfer for Machine Learning
%D 2006
%T Knowledge transfer with a multiresolution ensemble of classifiers
%A Eaton,E.
%A desJardins, Marie
%B ICML Workshop on Structural Knowledge Transfer for Machine Learning
%8 2006///
%G eng
%0 Conference Paper
%B Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
%D 2005
%T Kernel-based Bayesian filtering for object tracking
%A Han,Bohyung
%A Zhu,Ying
%A Comaniciu, D.
%A Davis, Larry S.
%K approach;
%K approximation;
%K Bayes
%K Bayesian
%K Carlo
%K density
%K detection;
%K filtering;
%K functions;
%K Gaussian
%K interpolation;
%K kernel-based
%K methods;
%K mixtures;
%K Monte
%K nonGaussian
%K nonlinear
%K object
%K particle
%K probability
%K probability;
%K processes;
%K recognition;
%K sampling
%K sampling;
%K sequences;
%K system;
%K tracking;
%K video
%X Particle filtering provides a general framework for propagating probability density functions in nonlinear and non-Gaussian systems. However, the algorithm is based on a Monte Carlo approach and sampling is a problematic issue, especially for high dimensional problems. This paper presents a new kernel-based Bayesian filtering framework, which adopts an analytic approach to better approximate and propagate density functions. In this framework, the techniques of density interpolation and density approximation are introduced to represent the likelihood and the posterior densities by Gaussian mixtures, where all parameters such as the number of mixands, their weight, mean, and covariance are automatically determined. The proposed analytic approach is shown to perform sampling more efficiently in high dimensional space. We apply our algorithm to real-time tracking problems, and demonstrate its performance on real video sequences as well as synthetic examples.
%B Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on
%V 1
%P 227 - 234 vol. 1 - 227 - 234 vol. 1
%8 2005/06//
%G eng
%R 10.1109/CVPR.2005.199
%0 Journal Article
%J Institute for Systems Research Technical Reports
%D 2005
%T Knowledge Discovery in High Dimensional Data: Case Studies and a User Survey for an Information Visualization Tool
%A Seo,Jinwook
%A Shneiderman, Ben
%K Information Visualization
%X Knowledge discovery in high dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our 3-year effort to develop versions of the Hierarchical Clustering Explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the Hierarchical Clustering Explorer (HCE) using three case studies and an email user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods.
%B Institute for Systems Research Technical Reports
%8 2005///
%G eng
%U http://drum.lib.umd.edu/handle/1903/6566
%0 Book Section
%B From Integrated Publication and Information Systems to Information and Knowledge EnvironmentsFrom Integrated Publication and Information Systems to Information and Knowledge Environments
%D 2005
%T A Knowledge Integration Framework for Information Visualization
%A Seo,Jinwook
%A Shneiderman, Ben
%E Hemmje,Matthias
%E Niederée,Claudia
%E Risse,Thomas
%X Users can better understand complex data sets by combining insights from multiple coordinated visual displays that include relevant domain knowledge. When dealing with multidimensional data and clustering results, the most familiar displays and comprehensible are 1- and 2-dimensional projections (histograms, and scatterplots). Other easily understood displays of domain knowledge are tabular and hierarchical information for the same or related data sets. The novel parallel coordinates view [6] powered by a direct-manipulation search, offers strong advantages, but requires some training for most users. We provide a review of related work in the area of information visualization, and introduce new tools and interaction examples on how to incorporate users’ domain knowledge for understanding clustering results. Our examples present hierarchical clustering of gene expression data, coordinated with a parallel coordinates view and with the gene annotation and gene ontology.
%B From Integrated Publication and Information Systems to Information and Knowledge EnvironmentsFrom Integrated Publication and Information Systems to Information and Knowledge Environments
%S Lecture Notes in Computer Science
%I Springer Berlin / Heidelberg
%V 3379
%P 207 - 220
%8 2005///
%@ 978-3-540-24551-3
%G eng
%U http://dx.doi.org/10.1007/978-3-540-31842-2_21
%0 Journal Article
%J Institute for Systems Research Technical Reports
%D 2005
%T A Knowledge Integration Framework for Information Visualization (2004)
%A Seo,Jinwook
%A Shneiderman, Ben
%K Technical Report
%X Users can better understand complex data sets by combining insights from multiple coordinated visual displays that include relevant domain knowl-edge. When dealing with multidimensional data and clustering results, the most familiar displays and comprehensible are 1- and 2-dimensional projections (his-tograms, and scatterplots). Other easily understood displays of domain knowl-edge are tabular and hierarchical information for the same or related data sets. The novel parallel coordinates view [6] powered by a direct-manipulation search, offers strong advantages, but requires some training for most users. We provide a review of related work in the area of information visualization, and introduce new tools and interaction examples on how to incorporate usersdo-main knowledge for understanding clustering results. Our examples present hi-erarchical clustering of gene expression data, coordinated with a parallel coor-dinates view and with the gene annotation and gene ontology.
%B Institute for Systems Research Technical Reports
%8 2005///
%G eng
%U http://drum.lib.umd.edu/handle/1903/6525
%0 Journal Article
%J IEEE Intl. Symp. Information Theory
%D 2004
%T Kullback-Leibler distance between two Gaussian densities in reproducing kernel Hilbert space
%A Zhou,S. K
%A Chellapa, Rama
%B IEEE Intl. Symp. Information Theory
%8 2004///
%G eng
%0 Conference Paper
%B IEEE International Conference on Systems, Man and Cybernetics, 2003
%D 2003
%T Kernel snakes: non-parametric active contour models
%A Abd-Almageed, Wael
%A Smith,C.E.
%A Ramadan,S.
%K Active contours
%K Artificial intelligence
%K Bayes methods
%K Bayesian decision theory
%K Bayesian methods
%K decision theory
%K Deformable models
%K Image edge detection
%K Image segmentation
%K Intelligent robots
%K Kernel
%K kernel snakes
%K Laboratories
%K multicolored target tracking
%K nonparametric active contour models
%K nonparametric generalized formulation
%K nonparametric model
%K nonparametric statistics
%K nonparametric techniques
%K real time performance
%K Robot vision systems
%K statistical pressure snakes
%K target tracking
%X In this paper, a new non-parametric generalized formulation to statistical pressure snakes is presented. We discuss the shortcomings of the traditional pressure snakes. We then introduce a new generic pressure model that alleviates these shortcomings, based on the Bayesian decision theory. Non-parametric techniques are used to obtain the statistical models that drive the snake. We discuss the advantages of using the proposed non-parametric model compared to other parametric techniques. Multi-colored-target tracking is used to demonstrate the performance of the proposed approach. Experimental results show enhanced, real-time performance.
%B IEEE International Conference on Systems, Man and Cybernetics, 2003
%I IEEE
%V 1
%P 240- 244 vol.1 - 240- 244 vol.1
%8 2003/10//
%@ 0-7803-7952-7
%G eng
%R 10.1109/ICSMC.2003.1243822
%0 Journal Article
%J Advances in Cryptology—Eurocrypt 2002
%D 2002
%T Key-insulated public key cryptosystems
%A Dodis,Y.
%A Katz, Jonathan
%A Xu,S.
%A Yung,M.
%X Cryptographic computations (decryption, signature generation, etc.) are often performed on a relatively insecure device (e.g., a mobile device or an Internet-connected host) which cannot be trusted to maintain secrecy of the private key. We propose and investigate the notion of key-insulated security whose goal is to minimize the damage caused by secret-key exposures. In our model, the secret key(s) stored on the insecure device are refreshed at discrete time periods via inter-action with a physically-secure - but computationally-limited - device which stores a “master key”. All cryptographic computations are still done on the insecure device, and the public key remains unchanged. In a (t, N)-key-insulated scheme, an adversary who compromises the insecure device and obtains secret keys for up to t periods of his choice is unable to violate the security of the cryptosystem for any of the remaining N - t periods. Furthermore, the scheme remains secure (for all time periods) against an adversary who compromises only the physically-secure device. We focus primarily on key-insulated public-key encryption. We construct a (t, N)-key-insulated encryption scheme based on any (standard) public-key encryption scheme, and give a more efficient construction based on the DDH assumption. The latter construction is then extended to achieve chosen-ciphertext security.
%B Advances in Cryptology—Eurocrypt 2002
%P 65 - 82
%8 2002///
%G eng
%R 10.1007/3-540-46035-7_5
%0 Journal Article
%J Behaviour & Information Technology
%D 2001
%T KidStory: A technology design partnership with children
%A Taxén,G.
%A Druin, Allison
%A Fast,C.
%A Kjellin,M.
%B Behaviour & Information Technology
%V 20
%P 119 - 125
%8 2001///
%G eng
%N 2
%0 Journal Article
%J Advances in Spatial and Temporal Databases
%D 2001
%T K-nearest neighbor search for moving query point
%A Song,Z.
%A Roussopoulos, Nick
%B Advances in Spatial and Temporal Databases
%P 79 - 96
%8 2001///
%G eng
%0 Journal Article
%J PE & RS- Photogrammetric Engineering and Remote Sensing
%D 2000
%T Kronos: A software system for the processing and retrieval of large-scale AVHRR data sets
%A Zhang,Z.
%A JaJa, Joseph F.
%A Bader, D.A.
%A Kalluri, SNV
%A Song,H.
%A El Saleous,N.
%A Vermote,E.
%A Townshend,J.R.G.
%X Raw remotely sensed satellite data have to be processed andmapped into a standard projection in order to produce a multi- temporal data set which can then be used for regional or global Earth science studies. However, traditional methods of processing remotely sensed satellite data have inherent limitations because they are based on a fixed processing chain. Different users may need the data in different forms with possibly different processing steps; hence, additional transformations may have to be applied to the processed data, resulting in potentially significant errors. In this paper, we describe a software system, Kronos, for the generation of custom-tailored products from the Advanced Very High Resolution Radiometer (AVHRR) sensor. It allows the generation of a rich set of products that can be easily specified through a simple interface by scientists wishing to carry out Earth system modeling or analysis. Kronos is based on a flexible methodology and consists of four major components: ingest and preprocessing, indexing and storage, a search and processing engine, and a Java interface. After geo-location and calibration, every pixel is indexed and stored using a combination of data structures. Following the users' queries, data are selectively retrieved and secondary processing such as atmospheric correction, compositing, and projection are performed as specified. The processing is divided into two stages, the first of which involves the geo-location and calibration of the remotely sensed data and, hence, results in no loss of information. The second stage involves the retrieval of the appropriate data subsets and the application of the secondary processing specified by the user. This scheme allows the indexing and the storage of data from different sensors without any loss of information and, therefore, allows assimilation of data from multiple sensors. User specified processing can be applied later as needed.
%B PE & RS- Photogrammetric Engineering and Remote Sensing
%V 66
%P 1073 - 1082
%8 2000///
%G eng
%N 9
%0 Conference Paper
%B Proceedings of the SIGCHI conference on Human factors in computing systems
%D 1997
%T KidPad: a design collaboration between children, technologists, and educators
%A Druin, Allison
%A Stewart,J.
%A Proft,D.
%A Bederson, Benjamin B.
%A Hollan,J.
%B Proceedings of the SIGCHI conference on Human factors in computing systems
%P 463 - 470
%8 1997///
%G eng
%0 Conference Paper
%B Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
%D 1994
%T Knowledge acquisition techniques for a military planning system
%A desJardins, Marie
%X In order to build realistic AI planning systems, it is necessary to develop sophisticated tools for knowledge acquisition. This paper describes two knowledge acquisition tools for a crisis action planning system. The first is a graphical operator editor that enables users to develop new planning operators and revise existing operators. The second is an inductive learning system, based on the PAGODA learning model, that learns from simulator feedback and from choices made by the user during planning. This paper describes the work done so far, and proposed for the future, on these tools
%B Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
%I IEEE Comput. Soc. Press
%P 454 - 460
%8 1994/11/06/9
%@ 0-8186-6785-0
%G eng
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=346457&tag=1
%R 10.1109/TAI.1994.346457
%0 Journal Article
%J Linear Algebra and its Applications
%D 1993
%T A Krylov multisplitting algorithm for solving linear systems of equations
%A Huang,Chiou-Ming
%A O'Leary, Dianne P.
%X We consider the practical implementation of Krylov subspace methods (conjugate gradients, Gmres, etc.) for parallel computers in the case where the preconditioning matrix arises from a multisplitting. We show that the algorithm can be efficiently implemented by dividing the work into tasks that generate search directions and a single task that minimizes over the resulting subspace. Each task is assigned to a subset of processors. It is not necessary for the minimization task to send frequent information to the direction generating tasks, and this leads to high utilization with a minimum of synchronization. We study the convergence properties of various forms of the algorithm and present results of numerical examples on a sequential computer.
%B Linear Algebra and its Applications
%V 194
%P 9 - 29
%8 1993/11/15/
%@ 0024-3795
%G eng
%U http://www.sciencedirect.com/science/article/pii/002437959390110A
%R 10.1016/0024-3795(93)90110-A
%0 Journal Article
%J Biological cybernetics
%D 1989
%T On the kinetic depth effect
%A Aloimonos, J.
%A Brown, C. M.
%B Biological cybernetics
%V 60
%P 445 - 455
%8 1989///
%G eng
%N 6
%0 Journal Article
%J Dep. Comput. Sci., Univ. Maryland, College Park, Tech. Rep. TR-1136
%D 1982
%T KMS reference manual
%A Reggia, James A.
%A Perricone,B.
%B Dep. Comput. Sci., Univ. Maryland, College Park, Tech. Rep. TR-1136
%8 1982///
%G eng
%0 Conference Paper
%B Proc. 20th Ann. Tech. Meeting of Wash. DC ACM
%D 1981
%T Knowledge-based decision support systems: Development through high-level languages
%A Reggia, James A.
%A Perricone,B. T.
%B Proc. 20th Ann. Tech. Meeting of Wash. DC ACM
%8 1981///
%G eng