@conference {13947,
	title = {Kernel partial least squares for speaker recognition},
	booktitle = {Twelfth Annual Conference of the International Speech Communication Association},
	year = {2011},
	month = {2011///},
	abstract = {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.},
	author = {Srinivasan,B.V. and Garcia-Romero,D. and Zotkin,Dmitry N and Duraiswami, Ramani}
}
@conference {13078,
	title = {Kernel PLS regression for robust monocular pose estimation},
	booktitle = {Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on},
	year = {2011},
	month = {2011/06//},
	pages = {24 - 30},
	abstract = {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.},
	keywords = {(computer, 3D, analysis;rendering, correlations;projection, detection;monocular, detection;pose, estimation;Gaussian, estimation;nonlinear, estimation;regression, GP, graphics);, images;rendering, latent, monocular, PLS, pose, process;Kernel, processes;object, regression;Gaussian, regression;human, software;robust, structures;realistic, to},
	doi = {10.1109/CVPRW.2011.5981750},
	author = {Dondera,R. and Davis, Larry S.}
}
@article {13941,
	title = {Kernelized Renyi distance for subset selection and similarity scoring},
	journal = {Technical Reports of the Computer Science Department},
	year = {2011},
	month = {2011/10/12/},
	abstract = {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.
},
	keywords = {Technical Report},
	url = {http://drum.lib.umd.edu/handle/1903/12132},
	author = {Srinivasan,Balaji Vasan and Duraiswami, Ramani}
}
@inbook {17635,
	title = {On k-Column Sparse Packing Programs},
	booktitle = {Integer Programming and Combinatorial OptimizationInteger Programming and Combinatorial Optimization},
	series = {Lecture Notes in Computer Science},
	volume = {6080},
	year = {2010},
	month = {2010///},
	pages = {369 - 382},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	abstract = {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.
},
	isbn = {978-3-642-13035-9},
	url = {http://dx.doi.org/10.1007/978-3-642-13036-6_28},
	author = {Bansal,Nikhil and Korula,Nitish and Nagarajan,Viswanath and Srinivasan, Aravind},
	editor = {Eisenbrand,Friedrich and Shepherd,F.}
}
@conference {13952,
	title = {Kernelized R{\'e}nyi distance for speaker recognition},
	booktitle = {Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on},
	year = {2010},
	month = {2010/03//},
	pages = {4506 - 4509},
	abstract = {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.},
	keywords = {$\#$x0301;nyi, approach;input, distance;reference, entropy;graphical, equipment;entropy;speaker, graphic, identification;speaker, processor;information, Re, recognition;, recognition;speaker, signals;kernelized, signals;speaker, theoretic, verification;computer},
	doi = {10.1109/ICASSP.2010.5495587},
	author = {Vasan Srinivasan,B. and Duraiswami, Ramani and Zotkin,Dmitry N}
}
@inbook {12536,
	title = {Knowledge Extraction from Surveillance Sensors},
	booktitle = {Wiley Handbook of Science and Technology for Homeland SecurityWiley Handbook of Science and Technology for Homeland Security},
	year = {2009},
	month = {2009///},
	publisher = {John Wiley \& Sons, Inc.},
	organization = {John Wiley \& Sons, Inc.},
	keywords = {multi-camera tracking, multi-modal fusion, recognition, sensor networks, Surveillance},
	isbn = {9780470087923},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/9780470087923.hhs510/abstract;jsessionid=D0D752EF5D04327BE003BDFBD2F96134.d01t03},
	author = {Chellapa, Rama and Veeraraghavan,Ashok and Sankaranarayanan,Aswin C.}
}
@conference {13122,
	title = {Kernel integral images: A framework for fast non-uniform filtering},
	booktitle = {Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on},
	year = {2008},
	month = {2008/06//},
	pages = {1 - 8},
	abstract = {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.},
	keywords = {approximated, equations;interpolation;, filtering;bilinear, filtering;kernel, Gaussian, graphics;computer, images;approximation, integral, interpolation;computer, nonuniform, processing;integral, theory;filtering, theory;image, vision;fast, weighting},
	doi = {10.1109/CVPR.2008.4587641},
	author = {Hussein,M. and Porikli, F. and Davis, Larry S.}
}
@conference {12581,
	title = {Kernel fully constrained least squares abundance estimates},
	booktitle = {Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International},
	year = {2007},
	month = {2007/07//},
	pages = {4041 - 4044},
	abstract = {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.},
	keywords = {abundance, algorithm;kernel, analysis;, AVIRIS, based, constrained, constraint;feature, constraint;spectral, estimates;linear, extraction;geophysical, feature, fully, image;hyperspectral, imagery;kernel, least, mixing, model;nonnegativity, processing;geophysical, processing;multidimensional, processing;spectral, signal, space;kernel, squares, techniques;image, unmixing;sum-to-one},
	doi = {10.1109/IGARSS.2007.4423736},
	author = {Broadwater, J. and Chellapa, Rama and Banerjee, A. and Burlina, P.}
}
@article {16858,
	title = {K-nearest neighbor finding using MaxNearestDist},
	journal = {IEEE transactions on pattern analysis and machine intelligence},
	year = {2007},
	month = {2007///},
	pages = {243 - 252},
	author = {Samet, Hanan}
}
@conference {16854,
	title = {Knowledge discovery using the sand spatial browser},
	booktitle = {Proceedings of the 8th annual international conference on Digital government research: bridging disciplines \& domains},
	series = {dg.o {\textquoteright}07},
	year = {2007},
	month = {2007///},
	pages = {284 - 285},
	publisher = {Digital Government Society of North America},
	organization = {Digital Government Society of North America},
	abstract = {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{\textquoteright}s study of the 1854 Cholera epidemic in Soho, London.},
	keywords = {distance semi-join, knowledge discovery, sand database system, snow cholera map},
	isbn = {1-59593-599-1},
	url = {http://dl.acm.org/citation.cfm?id=1248460.1248521},
	author = {Samet, Hanan and Phillippy,Adam and Sankaranarayanan,Jagan}
}
@conference {15627,
	title = {Keep Your Friends Close and Your Enemies Closer: The Art of Proximity Searching},
	booktitle = {Proceedings of the eighth Workshop on Algorithm Engineering and Experiments and the third Workshop on Analytic Algorithmics and Combinatorics},
	volume = {123},
	year = {2006},
	month = {2006///},
	pages = {65 - 65},
	author = {Mount, Dave}
}
@inbook {12639,
	title = {Key Frame-Based Activity Representation Using Antieigenvalues},
	booktitle = {Computer Vision {\textendash} ACCV 2006Computer Vision {\textendash} ACCV 2006},
	series = {Lecture Notes in Computer Science},
	volume = {3852},
	year = {2006},
	month = {2006///},
	pages = {499 - 508},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	abstract = {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 {\textendash} 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.},
	isbn = {978-3-540-31244-4},
	url = {http://dx.doi.org/10.1007/11612704_50},
	author = {Cuntoor,Naresh and Chellapa, Rama},
	editor = {Narayanan,P. and Nayar,Shree and Shum,Heung-Yeung}
}
@article {12269,
	title = {KeyChains: A Decentralized Public-Key Infrastructure},
	journal = {Technical Reports from UMIACS, UMIACS-TR-2006-12},
	year = {2006},
	month = {2006/03/02/},
	abstract = {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 {\textquoteleft}{\textquoteleft}web of trust{\textquoteright}{\textquoteright} 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.
},
	keywords = {Technical Report},
	url = {http://drum.lib.umd.edu/handle/1903/3332},
	author = {Morselli,Ruggero and Bhattacharjee, Bobby and Katz, Jonathan and Marsh,Michael A}
}
@article {17272,
	title = {Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {12},
	year = {2006},
	month = {2006/06//May},
	pages = {311 - 322},
	abstract = {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},
	keywords = {case study, Computer aided software engineering, Computer Society, Data analysis, data mining, data visualisation, Data visualization, database management systems, e-mail user survey, Genomics, Helium, Hierarchical Clustering Explorer, hierarchical clustering explorer., high-dimensional data, Histograms, Information visualization evaluation, interactive systems, interactive tool, knowledge discovery, multivariate data, Rank-by-feature framework, Scattering, Testing, user interface, User interfaces, user survey, visual analytic tools, visual analytics, visualization tools},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.50},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
@article {13446,
	title = {Knowledge transfer with a multiresolution ensemble of classifiers},
	journal = {ICML Workshop on Structural Knowledge Transfer for Machine Learning},
	year = {2006},
	month = {2006///},
	author = {Eaton,E. and desJardins, Marie}
}
@conference {13198,
	title = {Kernel-based Bayesian filtering for object tracking},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {227 - 234 vol. 1 - 227 - 234 vol. 1},
	abstract = {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.},
	keywords = {approach;, approximation;, Bayes, Bayesian, Carlo, density, detection;, filtering;, functions;, Gaussian, interpolation;, kernel-based, methods;, mixtures;, Monte, nonGaussian, nonlinear, object, particle, probability, probability;, processes;, recognition;, sampling, sampling;, sequences;, system;, tracking;, video},
	doi = {10.1109/CVPR.2005.199},
	author = {Han,Bohyung and Zhu,Ying and Comaniciu, D. and Davis, Larry S.}
}
@article {17271,
	title = {Knowledge Discovery in High Dimensional Data: Case Studies and a User Survey for an Information Visualization Tool},
	journal = {Institute for Systems Research Technical Reports},
	year = {2005},
	month = {2005///},
	abstract = {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.},
	keywords = {Information Visualization},
	url = {http://drum.lib.umd.edu/handle/1903/6566},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
@inbook {16931,
	title = {A Knowledge Integration Framework for Information Visualization},
	booktitle = {From Integrated Publication and Information Systems to Information and Knowledge EnvironmentsFrom Integrated Publication and Information Systems to Information and Knowledge Environments},
	series = {Lecture Notes in Computer Science},
	volume = {3379},
	year = {2005},
	month = {2005///},
	pages = {207 - 220},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	abstract = {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{\textquoteright} 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.},
	isbn = {978-3-540-24551-3},
	url = {http://dx.doi.org/10.1007/978-3-540-31842-2_21},
	author = {Seo,Jinwook and Shneiderman, Ben},
	editor = {Hemmje,Matthias and Nieder{\'e}e,Claudia and Risse,Thomas}
}
@article {16932,
	title = {A Knowledge Integration Framework for Information Visualization (2004)},
	journal = {Institute for Systems Research Technical Reports},
	year = {2005},
	month = {2005///},
	abstract = {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 usersdo-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.},
	keywords = {Technical Report},
	url = {http://drum.lib.umd.edu/handle/1903/6525},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
@article {12707,
	title = {Kullback-Leibler distance between two Gaussian densities in reproducing kernel Hilbert space},
	journal = {IEEE Intl. Symp. Information Theory},
	year = {2004},
	month = {2004///},
	author = {Zhou,S. K and Chellapa, Rama}
}
@conference {11896,
	title = {Kernel snakes: non-parametric active contour models},
	booktitle = {IEEE International Conference on Systems, Man and Cybernetics, 2003},
	volume = {1},
	year = {2003},
	month = {2003/10//},
	pages = {240- 244 vol.1 - 240- 244 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {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.},
	keywords = {Active contours, Artificial intelligence, Bayes methods, Bayesian decision theory, Bayesian methods, decision theory, Deformable models, Image edge detection, Image segmentation, Intelligent robots, Kernel, kernel snakes, Laboratories, multicolored target tracking, nonparametric active contour models, nonparametric generalized formulation, nonparametric model, nonparametric statistics, nonparametric techniques, real time performance, Robot vision systems, statistical pressure snakes, target tracking},
	isbn = {0-7803-7952-7},
	doi = {10.1109/ICSMC.2003.1243822},
	author = {Abd-Almageed, Wael and Smith,C.E. and Ramadan,S.}
}
@article {15094,
	title = {Key-insulated public key cryptosystems},
	journal = {Advances in Cryptology{\textemdash}Eurocrypt 2002},
	year = {2002},
	month = {2002///},
	pages = {65 - 82},
	abstract = {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 {\textquotedblleft}master key{\textquotedblright}. 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.},
	doi = {10.1007/3-540-46035-7_5},
	author = {Dodis,Y. and Katz, Jonathan and Xu,S. and Yung,M.}
}
@article {13897,
	title = {KidStory: A technology design partnership with children},
	journal = {Behaviour \& Information Technology},
	volume = {20},
	year = {2001},
	month = {2001///},
	pages = {119 - 125},
	author = {Tax{\'e}n,G. and Druin, Allison and Fast,C. and Kjellin,M.}
}
@article {16756,
	title = {K-nearest neighbor search for moving query point},
	journal = {Advances in Spatial and Temporal Databases},
	year = {2001},
	month = {2001///},
	pages = {79 - 96},
	author = {Song,Z. and Roussopoulos, Nick}
}
@article {14980,
	title = {Kronos: A software system for the processing and retrieval of large-scale AVHRR data sets},
	journal = {PE \& RS- Photogrammetric Engineering and Remote Sensing},
	volume = {66},
	year = {2000},
	month = {2000///},
	pages = {1073 - 1082},
	abstract = {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{\textquoteright} 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.
},
	author = {Zhang,Z. and JaJa, Joseph F. and Bader, D.A. and Kalluri, SNV and Song,H. and El Saleous,N. and Vermote,E. and Townshend,J.R.G.}
}
@conference {12217,
	title = {KidPad: a design collaboration between children, technologists, and educators},
	booktitle = {Proceedings of the SIGCHI conference on Human factors in computing systems},
	year = {1997},
	month = {1997///},
	pages = {463 - 470},
	author = {Druin, Allison and Stewart,J. and Proft,D. and Bederson, Benjamin B. and Hollan,J.}
}
@conference {13445,
	title = {Knowledge acquisition techniques for a military planning system},
	booktitle = {Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on},
	year = {1994},
	month = {1994/11/06/9},
	pages = {454 - 460},
	publisher = {IEEE Comput. Soc. Press},
	organization = {IEEE Comput. Soc. Press},
	abstract = {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},
	isbn = {0-8186-6785-0},
	doi = {10.1109/TAI.1994.346457},
	url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=346457\&tag=1},
	author = {desJardins, Marie}
}
@article {15702,
	title = {A Krylov multisplitting algorithm for solving linear systems of equations},
	journal = {Linear Algebra and its Applications},
	volume = {194},
	year = {1993},
	month = {1993/11/15/},
	pages = {9 - 29},
	abstract = {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.},
	isbn = {0024-3795},
	doi = {10.1016/0024-3795(93)90110-A},
	url = {http://www.sciencedirect.com/science/article/pii/002437959390110A},
	author = {Huang,Chiou-Ming and O{\textquoteright}Leary, Dianne P.}
}
@article {12023,
	title = {On the kinetic depth effect},
	journal = {Biological cybernetics},
	volume = {60},
	year = {1989},
	month = {1989///},
	pages = {445 - 455},
	author = {Aloimonos, J. and Brown, C. M.}
}
@article {16554,
	title = {KMS reference manual},
	journal = {Dep. Comput. Sci., Univ. Maryland, College Park, Tech. Rep. TR-1136},
	year = {1982},
	month = {1982///},
	author = {Reggia, James A. and Perricone,B.}
}
@conference {16618,
	title = {Knowledge-based decision support systems: Development through high-level languages},
	booktitle = {Proc. 20th Ann. Tech. Meeting of Wash. DC ACM},
	year = {1981},
	month = {1981///},
	author = {Reggia, James A. and Perricone,B. T.}
}
