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» On the Complexity of Function Learning
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SIGPRO
2011
209views Hardware» more  SIGPRO 2011»
14 years 7 months ago
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
A. Rakotomamonjy
121
Voted
ICML
2006
IEEE
16 years 1 months ago
Combining discriminative features to infer complex trajectories
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
David A. Ross, Simon Osindero, Richard S. Zemel
92
Voted
NIPS
2008
15 years 2 months ago
Simple Local Models for Complex Dynamical Systems
We present a novel mathematical formalism for the idea of a "local model" of an uncontrolled dynamical system, a model that makes only certain predictions in only certai...
Erik Talvitie, Satinder Singh
84
Voted
MM
2005
ACM
134views Multimedia» more  MM 2005»
15 years 6 months ago
Formulating context-dependent similarity functions
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
Gang Wu, Edward Y. Chang, Navneet Panda
119
Voted
TFS
2008
129views more  TFS 2008»
14 years 11 months ago
A Functional-Link-Based Neurofuzzy Network for Nonlinear System Control
Abstract--This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural netw...
Cheng-Hung Chen, Cheng-Jian Lin, Chin-Teng Lin