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The goal of the data warehousing project at Stanford (the WHIPS project) is to develop algorithms and tools for the eecient collection and integration of information from heterogeneous and autonomous sources, including legacy sources. In this paper we give a brief overview of the WHIPS project, and we describe some of the research problems being addressed in the initial phase of the project.
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Pointer swizzling at page fault time is a novel address translation mechanism that exploits conventional address translation hardware. It can support huge address spaces eeciently without long hardware addresses; such large address spaces are attractive for persistent object stores, distributed shared memories, and shared address space operating systems. This swizzling scheme can be used to pro...
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Fingerprinting schemes deter people from illegally redistributing digital data by enabling the original merchant of the data to identify the original buyer of a redistributed copy. So-called traitor-tracing schemes have the same goal for keys used to decrypt information that is broadcast in encrypted form. Recently, asymmetric fingerprinting and traitor-tracing schemes were introduced. Here, on...
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Alignment Stefan Wermter International Computer Science Institute 1947 Center Street Berkeley, CA 94704-1198 USA [email protected] Joseph Chen University of Hamburg Computer Science Department Vogt-K olln-Stra e 30 D-22527 Hamburg, Germany [email protected] Abstract 1We examine phrase alignment in a hybrid connectionist framework. We describe the architecture and the learn...
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We deene and exercise the expected value of computation as a fundamental component of reeection about alternative inference strategies. We present a portion of Protos research focused on the interlacing of reeection and action under scarce resources, and discuss how the techniques have been applied in a high-stakes medical domain. The work centers on endowing a computational agent with the abil...
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An accurate retrieval system is essential to the performance of any case-based reasoning (CBR) system. This paper describes a new retrieval method in which both feature similarity and adaptation knowledge are used to guide retrieval. A system can only improve its performance by learning and CBR systems learn mainly by storing newly adapted cases. The system has better opportunities to learn use...
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volume 0 issue None
pages 63- 98
publication date 2020-02
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