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NIPS
2008
15 years 8 months ago
Scalable Algorithms for String Kernels with Inexact Matching
We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
CGF
2008
99views more  CGF 2008»
15 years 7 months ago
Polyhedral Finite Elements Using Harmonic Basis Functions
Finite element simulations in computer graphics are typically based on tetrahedral or hexahedral elements, which enables simple and efficient implementations, but in turn requires...
Sebastian Martin, Peter Kaufmann, Mario Botsch, Ma...
CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 7 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
CORR
2008
Springer
179views Education» more  CORR 2008»
15 years 7 months ago
Distributed Parameter Estimation in Sensor Networks: Nonlinear Observation Models and Imperfect Communication
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...
Soummya Kar, José M. F. Moura, Kavita Raman...
CORR
2006
Springer
130views Education» more  CORR 2006»
15 years 7 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...