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NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 4 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
ENGL
2008
85views more  ENGL 2008»
15 years 22 days ago
Prediction of Concentration Profiles of Dispersed Particles through Horizontal Cylindrical Channels
Deposition of dispersed and ultradispersed solid particles in cylindrical channels has received considerable attention due to its practical significance and direct application in i...
Herbert Loria Molina, Pedro Pereira-Almao, Carlos ...
102
Voted
PPOPP
2005
ACM
15 years 6 months ago
Teleport messaging for distributed stream programs
In this paper, we develop a new language construct to address one of the pitfalls of parallel programming: precise handling of events across parallel components. The construct, te...
William Thies, Michal Karczmarek, Janis Sermulins,...
ISCA
1993
IEEE
117views Hardware» more  ISCA 1993»
15 years 4 months ago
Evaluation of Release Consistent Software Distributed Shared Memory on Emerging Network Technology
We evaluate the e ect of processor speed, network bandwidth, and software overhead on the performance of release-consistent software distributed shared memory. We examine ve di er...
Sandhya Dwarkadas, Peter J. Keleher, Alan L. Cox, ...
93
Voted
PLISP
1989
15 years 4 months ago
Speculative Computation in Multilisp
Speculative computing is a technique to improve the execution time of certain applications by starting some computations before it is known that the computations are required. A s...
Randy B. Osborne