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» Sequential predictions based on algorithmic complexity
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118
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NIPS
2003
15 years 4 months ago
Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels
Decoding is a strategy that allows us to assess the amount of information neurons can provide about certain aspects of the visual scene. In this study, we develop a method based o...
Ryan Kelly, Tai Sing Lee
NFM
2011
223views Formal Methods» more  NFM 2011»
14 years 9 months ago
Generating Data Race Witnesses by an SMT-Based Analysis
Abstract. Data race is one of the most dangerous errors in multithreaded programming, and despite intensive studies, it remains a notorious cause of failures in concurrent systems....
Mahmoud Said, Chao Wang, Zijiang Yang, Karem Sakal...
135
Voted
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
15 years 4 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand
134
Voted
ICML
2006
IEEE
16 years 3 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
BMCBI
2008
109views more  BMCBI 2008»
15 years 2 months ago
ConStruct: Improved construction of RNA consensus structures
Background: Aligning homologous non-coding RNAs (ncRNAs) correctly in terms of sequence and structure is an unresolved problem, due to both mathematical complexity and imperfect s...
Andreas Wilm, Kornelia Linnenbrink, Gerhard Steger