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» A Practical Method for the Sparse Resultant
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CEC
2003
IEEE
15 years 11 months ago
Learning DFA: evolution versus evidence driven state merging
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Simon M. Lucas, T. Jeff Reynolds
CVPR
2007
IEEE
15 years 10 months ago
Inferring 3D Volumetric Shape of Both Moving Objects and Static Background Observed by a Moving Camera
We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that th...
Chang Yuan, Gérard G. Medioni
NIPS
2008
15 years 7 months ago
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computation...
Ben Calderhead, Mark Girolami, Neil D. Lawrence
SIGPRO
2010
135views more  SIGPRO 2010»
15 years 4 months ago
A short note on compressed sensing with partially known signal support
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
Laurent Jacques
BMCBI
2008
155views more  BMCBI 2008»
15 years 6 months ago
Extending pathways based on gene lists using InterPro domain signatures
Background: High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly...
Florian Hahne, Alexander Mehrle, Dorit Arlt, Annem...