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125
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ICONIP
1998
15 years 4 months ago
Computing Iterative Roots with Neural Networks
Many real processes are composed of a n-fold repetition of some simpler process. If the whole process can be modelled with a neural network, we present a method to derive a model ...
Lars Kindermann
119
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PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
15 years 1 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
146
Voted
INFOCOM
2010
IEEE
15 years 2 months ago
Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks
—In Multi-User MIMO networks, receivers decode multiple concurrent signals using Successive Interference Cancellation (SIC). With SIC a weak target signal can be deciphered in th...
Ece Gelal, Konstantinos Pelechrinis, Tae-Suk Kim, ...
112
Voted
HIS
2007
15 years 5 months ago
Exploration of Pareto Frontier Using a Fuzzy Controlled Hybrid Line Search
This paper proposes a new approach for multicriteria optimization which aggregates the objective functions and uses a line search method in order to locate an approximate efficien...
Crina Grosan, Ajith Abraham
170
Voted
CVPR
2012
IEEE
13 years 6 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis