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    FLAIRS
    2003
    225views Artificial Intelligence» more  FLAIRS 2003»
    Advantages of Brahms for Specifying and Implementing a Multiagent Human-Robotic Exploration System
    13 years 8 months ago
    Advantages of Brahms for Specifying and Implementing a Multiagent Human-Robotic Exploration System
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    We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut’s spac...
    William J. Clancey, Maarten Sierhuis, Charis Kaski...
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    SDM
    2003
    SIAM
    184views Data Mining» more  SDM 2003»
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    13 years 8 months ago
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
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    The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
    Levent Ertöz, Michael Steinbach, Vipin Kumar
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    DSL
    1997
    100views Programming Languages» more  DSL 1997»
    Experience with a Language for Writing Coherence Protocols
    13 years 8 months ago
    Experience with a Language for Writing Coherence Protocols
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    In this paper we describe our experience with Teapot [7], a domain-specific language for writing cache coherence protocols. Cache coherence is of concern when parallel and distrib...
    Satish Chandra, James R. Larus, Michael Dahlin, Br...
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    IJCAI
    1997
    170views Artificial Intelligence» more  IJCAI 1997»
    Is Nonparametric Learning Practical in Very High Dimensional Spaces?
    13 years 8 months ago
    Is Nonparametric Learning Practical in Very High Dimensional Spaces?
    Download  www.cs.colorado.edu
    Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
    Gregory Z. Grudic, Peter D. Lawrence
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    BIOINFORMATICS
    2010
    127views more  BIOINFORMATICS 2010»
    Analyzing taxonomic classification using extensible Markov models
    13 years 7 months ago
    Analyzing taxonomic classification using extensible Markov models
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    Motivation: As next generation sequencing is rapidly adding new genomes, their correct placement in the taxonomy needs verification. However, the current methods for confirming cl...
    Rao M. Kotamarti, Michael Hahsler, Douglas Raiford...
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