• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 67,970
Next 10 →

Potential games

by Dov Monderer, Lloyd S. Shapley , 1996
"... We define and discuss several notions of potential functions for games in strategic form. We characterize games that have a potential function, and we present a variety of applications. ..."
Abstract - Cited by 589 (4 self) - Add to MetaCart
We define and discuss several notions of potential functions for games in strategic form. We characterize games that have a potential function, and we present a variety of applications.

Inducing Features of Random Fields

by Stephen Della Pietra, Vincent Della Pietra, John Lafferty - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1997
"... We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the ..."
Abstract - Cited by 670 (10 self) - Add to MetaCart
We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing

The transcriptional program of sporulation in budding yeast

by S. Chu, J. DeRisi, M. Eisen, J. Mulholland, D. Botstein, P. O. Brown, I. Herskowitz - SCIENCE , 1998
"... Diploid cells of budding yeast produce haploid cells through the develop-mental program of sporulation, which consists of meiosis and spore morphogenesis. DNA microarrays containing nearly every yeast gene were used to assay changes in gene expression during sporulation. At least seven distinct temp ..."
Abstract - Cited by 497 (8 self) - Add to MetaCart
of coordinately expressed genes. The temporal expression pattern provided clues to potential functions of hundreds of previously uncharacterized genes, some of which have vertebrate homologs that may function during gametogenesis.

Snakes, Shapes, and Gradient Vector Flow

by Chenyang Xu, Jerry L. Prince - IEEE TRANSACTIONS ON IMAGE PROCESSING , 1998
"... Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new extern ..."
Abstract - Cited by 755 (16 self) - Add to MetaCart
in that it cannot be written as the negative gradient of a potential function, and the corresponding snake is formulated directly from a force balance condition rather than a variational formulation. Using several two-dimensional (2-D) examples and one three-dimensional (3-D) example, we show that GVF has a large

Scalable molecular dynamics with NAMD.

by James C Phillips , Rosemary Braun , Wei Wang , James Gumbart , Emad Tajkhorshid , Elizabeth Villa , Christophe Chipot , Robert D Skeel , Laxmikant Kalé , Klaus Schulten - J Comput Chem , 2005
"... Abstract: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and la ..."
Abstract - Cited by 849 (63 self) - Add to MetaCart
and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion

Bundle Adjustment -- A Modern Synthesis

by Bill Triggs, Philip McLauchlan, Richard Hartley, Andrew Fitzgibbon - VISION ALGORITHMS: THEORY AND PRACTICE, LNCS , 2000
"... This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics c ..."
Abstract - Cited by 562 (13 self) - Add to MetaCart
This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics

Sparse coding with an overcomplete basis set: a strategy employed by V1

by Bruno A. Olshausen, David J. Fieldt - Vision Research , 1997
"... The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive f ..."
Abstract - Cited by 958 (9 self) - Add to MetaCart
for representing a given input, and so the input-output function will deviate from being purely linear. These deviations from linearity provide a potential explanation for the weak forms of non-linearity observed in the response properties of cortical simple cells, and they further make predictions about

A Case for End System Multicast

by Yang-hua Chu, Sanjay G. Rao, Srinivasan Seshan, Hui Zhang - in Proceedings of ACM Sigmetrics , 2000
"... Abstract — The conventional wisdom has been that IP is the natural protocol layer for implementing multicast related functionality. However, more than a decade after its initial proposal, IP Multicast is still plagued with concerns pertaining to scalability, network management, deployment and suppor ..."
Abstract - Cited by 1290 (24 self) - Add to MetaCart
Abstract — The conventional wisdom has been that IP is the natural protocol layer for implementing multicast related functionality. However, more than a decade after its initial proposal, IP Multicast is still plagued with concerns pertaining to scalability, network management, deployment

Sparse Bayesian Learning and the Relevance Vector Machine

by Michael E. Tipping , 2001
"... This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classification tasks utilising models linear in the parameters. Although this framework is fully general, we illustrate our approach with a particular specialisation that we denote the `relevance vect ..."
Abstract - Cited by 966 (5 self) - Add to MetaCart
vector machine’ (RVM), a model of identical functional form to the popular and state-of-the-art `support vector machine ’ (SVM). We demonstrate that by exploiting a probabilistic Bayesian learning framework, we can derive accurate prediction models which typically utilise dramatically fewer basis

Simultaneous Multithreading: Maximizing On-Chip Parallelism

by Dean M. Tullsen , Susan J. Eggers, Henry M. Levy , 1995
"... This paper examines simultaneous multithreading, a technique permitting several independent threads to issue instructions to a superscalar’s multiple functional units in a single cycle. We present several models of simultaneous multithreading and compare them with alternative organizations: a wide s ..."
Abstract - Cited by 823 (48 self) - Add to MetaCart
This paper examines simultaneous multithreading, a technique permitting several independent threads to issue instructions to a superscalar’s multiple functional units in a single cycle. We present several models of simultaneous multithreading and compare them with alternative organizations: a wide
Next 10 →
Results 1 - 10 of 67,970
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University