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» Learning network structure from passive measurements
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CORR
2012
Springer
185views Education» more  CORR 2012»
13 years 7 months ago
Bayesian network learning with cutting planes
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
James Cussens
ICDE
2007
IEEE
115views Database» more  ICDE 2007»
16 years 1 months ago
SPRITE: A Learning-Based Text Retrieval System in DHT Networks
In this paper, we propose SPRITE (Selective PRogressive Index Tuning by Examples), a scalable system for text retrieval in a structured P2P network. Under SPRITE, each peer is res...
Yingguang Li, H. V. Jagadish, Kian-Lee Tan
HICSS
2005
IEEE
160views Biometrics» more  HICSS 2005»
15 years 5 months ago
Using Content and Process Scaffolds to Support Collaborative Discourse in Asynchronous Learning Networks
Discourse, a form of collaborative learning [44], is one of the most widely used methods of teaching and learning in the online environment. Particularly in large courses, discour...
I. Wong-Bushby, Starr Roxanne Hiltz, Michael Biebe...
SIGCOMM
2009
ACM
15 years 6 months ago
Every microsecond counts: tracking fine-grain latencies with a lossy difference aggregator
Many network applications have stringent end-to-end latency requirements, including VoIP and interactive video conferencing, automated trading, and high-performance computing—wh...
Ramana Rao Kompella, Kirill Levchenko, Alex C. Sno...
DAGM
2007
Springer
15 years 3 months ago
Efficient Learning of Neural Networks with Evolutionary Algorithms
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Nils T. Siebel, Jochen Krause, Gerald Sommer