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90,485
SCRIBE: A large-scale and decentralized application-level multicast infrastructure
- IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (JSAC
, 2002
"... This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet, ..."
Abstract
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Cited by 658 (29 self)
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This paper presents Scribe, a scalable application-level multicast infrastructure. Scribe supports large numbers of groups, with a potentially large number of members per group. Scribe is built on top of Pastry, a generic peer-to-peer object location and routing substrate overlayed on the Internet
Query evaluation techniques for large databases
- ACM COMPUTING SURVEYS
, 1993
"... Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On ..."
Abstract
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Cited by 767 (11 self)
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Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem
Automatic Acquisition of Hyponyms from Large Text Corpora
, 1992
"... We describe a method for the automatic acquisition of the hyponymy lexical relation from unrestricted text. Two goals motivate the approach: (i) avoidante of the need for pre-encoded knowledge and (ii) applicability across a wide range of text. We identify a set of lexico-syntactic patterns that are ..."
Abstract
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Cited by 1261 (4 self)
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algorithm is implemented and the results are used to augment and critique the structure of a large hand-built thesaurus. Extensions and applications to areas such as information retrieval are suggested.
Making Large-Scale SVM Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract
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Cited by 1861 (17 self)
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and computational results developed for SV M light V2.0, which make large-scale SVM training more practical. The results give guidelines for the application of SVMs to large domains.
Automatically characterizing large scale program behavior
, 2002
"... Understanding program behavior is at the foundation of computer architecture and program optimization. Many pro-grams have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ramifications for many architectural and com-pile ..."
Abstract
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Cited by 778 (41 self)
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-piler techniques, from thread scheduling, to feedback directed optimizations, to the way programs are simulated. However, in order to take advantage of time-varying behavior, we.must first develop the analytical tools necessary to automatically and efficiently analyze program behavior over large sections
Imagenet: A large-scale hierarchical image database
- In CVPR
, 2009
"... The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such data can be harnessed and organized remains a critical problem. We introduce her ..."
Abstract
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Cited by 840 (28 self)
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datasets. Constructing such a large-scale database is a challenging task. We describe the data collection scheme with Amazon Mechanical Turk. Lastly, we illustrate the usefulness of ImageNet through three simple applications in object recognition, image classification and automatic object clustering. We
Large margin methods for structured and interdependent output variables
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract
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Cited by 624 (12 self)
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that solves the optimization problem in polynomial time for a large class of problems. The proposed method has important applications in areas such as computational biology, natural language processing, information retrieval/extraction, and optical character recognition. Experiments from various domains
Scalable Application Layer Multicast
, 2002
"... We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data deliv ..."
Abstract
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Cited by 731 (21 self)
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We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data
A Field Study of the Software Design Process for Large Systems
- Communications of the ACM
, 1988
"... The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three lgf these problems-the thin spread of application domain knowledge, fluctuating and conflicting requirements, and communication ..."
Abstract
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Cited by 685 (2 self)
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The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three lgf these problems-the thin spread of application domain knowledge, fluctuating and conflicting requirements
Making Large-Scale Support Vector Machine Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract
-
Cited by 628 (1 self)
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algorithmic and computational results developed for SVM light V2.0, which make large-scale SVM training more practical. The results give guidelines for the application of SVMs to large domains.
Results 1 - 10
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90,485