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JMLR
2008
209views more  JMLR 2008»
14 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
CJ
1999
126views more  CJ 1999»
14 years 9 months ago
Source Level Static Branch Prediction
The ability to predict the directions of branches, especially conditional branches, is an important problem in modern computer architecture and advanced compilers. Many static and...
W. F. Wong
AI
1998
Springer
14 years 9 months ago
GAS, A Concept on Modeling Species in Genetic Algorithms
This paper introduces a niching technique called GAS (S stands for species) which dynamically creates a subpopulation structure (taxonomic chart) using a radius function instead of...
Márk Jelasity, József Dombi
CODES
2006
IEEE
15 years 3 months ago
Data reuse driven energy-aware MPSoC co-synthesis of memory and communication architecture for streaming applications
The memory subsystem of a complex multiprocessor systemson-chip (MPSoC) is an important contributor to the chip power consumption. The selection of memory architecture, as well as...
Ilya Issenin, Nikil Dutt
NIPS
2007
14 years 11 months ago
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Charlie Frogner, Avi Pfeffer