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ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 3 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 3 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
INFOCOM
2005
IEEE
14 years 1 months ago
Non-uniform random membership management in peer-to-peer networks
Abstract— Existing random membership management algorithms provide each node with a small, uniformly random subset of global participants. However, many applications would beneď¬...
Ming Zhong, Kai Shen, Joel I. Seiferas
AMC
2006
104views more  AMC 2006»
13 years 7 months ago
Three counterexamples refuting Kieu's plan for "quantum adiabatic hypercomputation"; and some uncomputable quantum mechanical ta
-- Tien D. Kieu, in 10 papers posted to the quant-ph section of the xxx.lanl.gov preprint archive [some of which were also published in printed journals such as Proc. Royal Soc. A ...
Warren D. Smith
ALT
2008
Springer
14 years 4 months ago
Prequential Randomness
This paper studies Dawid’s prequential framework from the point of view of the algorithmic theory of randomness. The main result is that two natural notions of randomness coincid...
Vladimir Vovk, Alexander Shen