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105
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TNN
1998
112views more  TNN 1998»
15 years 3 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
164
Voted
MSWIM
2009
ACM
15 years 10 months ago
A performance evaluation framework for fair solutions in ad hoc networks
Fairness in multihop ad hoc networks has received considerable attention in the literature. Many schemes have been proposed, which attempt to compute the “optimal” bit rates o...
Manos Dramitinos, Rémi Vannier, Isabelle Gu...
103
Voted
AUTOMATICA
2006
66views more  AUTOMATICA 2006»
15 years 3 months ago
Robust residual generation for diagnosis including a reference model for residual behavior
: The main goal when synthesizing robust residual generators, for diagnosis and supervision, is to attenuate influence from model uncertainty on the residual while keeping fault de...
Erik Frisk, Lars Nielsen
146
Voted
ICCV
2009
IEEE
16 years 8 months ago
A Global Perspective on MAP Inference for Low-Level Vision
In recent years the Markov Random Field (MRF) has become the de facto probabilistic model for low-level vision applications. However, in a maximum a posteriori (MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
154
Voted
ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 3 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola