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» Machine-Learning Applications of Algorithmic Randomness
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JCO
2010
101views more  JCO 2010»
13 years 6 months ago
Separator-based data reduction for signed graph balancing
Abstract Polynomial-time data reduction is a classical approach to hard graph problems. Typically, particular small subgraphs are replaced by smaller gadgets. We generalize this ap...
Falk Hüffner, Nadja Betzler, Rolf Niedermeier
EUROPAR
2009
Springer
13 years 5 months ago
A Least-Resistance Path in Reasoning about Unstructured Overlay Networks
Unstructured overlay networks for peer-to-peer applications combined with stochastic algorithms for clustering and resource location are attractive due to low-maintenance costs and...
Giorgos Georgiadis, Marina Papatriantafilou
JMLR
2010
104views more  JMLR 2010»
13 years 2 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
ICASSP
2011
IEEE
12 years 12 months ago
A clustering based framework for dictionary block structure identification
Sparse representations over redundant dictionaries offer an efficient paradigm for signal representation. Recently block-sparsity has been put forward as a prior condition for so...
Ender M. Eksioglu
CORR
2010
Springer
180views Education» more  CORR 2010»
13 years 8 months ago
Dependability in Aggregation by Averaging
Abstract. Aggregation is an important building block of modern distributed applications, allowing the determination of meaningful properties (e.g. network size, total storage capac...
Paulo Jesus, Carlos Baquero, Paulo Sérgio A...