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» New Algorithms for Learning in Presence of Errors
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TSP
2011
197views more  TSP 2011»
13 years 3 months ago
Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
INFOVIS
2002
IEEE
14 years 1 months ago
Visualizing Data with Bounded Uncertainty
Visualization is a powerful way to facilitate data analysis, but it is crucial that visualization systems explicitly convey the presence, nature, and degree of uncertainty to user...
Chris Olston, Jock D. Mackinlay
ICANN
2005
Springer
14 years 2 months ago
A Neural Network Model for Inter-problem Adaptive Online Time Allocation
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Matteo Gagliolo, Jürgen Schmidhuber
NIPS
2004
13 years 10 months ago
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale
Protein interactions typically arise from a physical interaction of one or more small sites on the surface of the two proteins. Identifying these sites is very important for drug ...
Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koll...
PKDD
2009
Springer
147views Data Mining» more  PKDD 2009»
14 years 3 months ago
Kernel Polytope Faces Pursuit
Abstract. Polytope Faces Pursuit (PFP) is a greedy algorithm that approximates the sparse solutions recovered by 1 regularised least-squares (Lasso) [4,10] in a similar vein to (Or...
Tom Diethe, Zakria Hussain