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» A Simple Abstraction for Data Modeling
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UAI
1996
15 years 7 months ago
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
David Maxwell Chickering, David Heckerman
ANSS
2007
IEEE
16 years 26 days ago
Scalable Data Collection Protocols for Wireless Sensor Networks with Multiple Mobile Sinks
Data propagation in wireless sensor networks is usually performed as a multihop process. To deliver a single message, the resources of many sensor nodes are used and a lot of ener...
Athanasios Kinalis, Sotiris E. Nikoletseas
CCGRID
2003
IEEE
15 years 11 months ago
Evaluation of the inter-cluster data transfer on Grid environment
High-performance peer-to-peer transfer between clusters will be fundamental technology base for various Grid middleware, such as large-scale data transfer in DataGrid settings, or...
Shoji Ogura, Satoshi Matsuoka, Hidemoto Nakada
UML
2005
Springer
15 years 12 months ago
Simplifying Transformations of OCL Constraints
Abstract. With the advent of Model Driven Architecture, OCL constraints are no longer necessarily written by humans. They can be part of models that emerge from a chain of transfor...
Martin Giese, Daniel Larsson
TOC
2008
89views more  TOC 2008»
15 years 6 months ago
Norms, XOR Lemmas, and Lower Bounds for Polynomials and Protocols
Abstract: This paper presents a unified and simple treatment of basic questions concerning two computational models: multiparty communication complexity and polynomials over GF(2)....
Emanuele Viola, Avi Wigderson