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116
Voted
NIPS
2003
15 years 5 months ago
2003
In models that define probabilities via energies, maximum likelihood learning typically involves using Markov Chain Monte Carlo to sample from the model’s distribution. If the ...
153
Voted
JIISIC
2001
15 years 5 months ago
2001
We have developed a distributed DSS capable to working in a dynamic way. That is, when a domain of an organization needs a new kind of information, the system looks for this infor...
149
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NLPRS
2001
Springer
15 years 8 months ago
2001
Springer
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
108
Voted
CORR
2010
Springer
15 years 2 months ago
2010
Springer
Abstract—We introduce a new class of exact MinimumBandwidth Regenerating (MBR) codes for distributed storage systems, characterized by a low-complexity uncoded repair process tha...
140
Voted
LICS
2005
IEEE
15 years 9 months ago
2005
IEEE
We provide a uniform solution to the problem of synthesizing a finite-state distributed system. An instance of the synthesis problem consists of a system architecture and a tempo...