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ICTAI
2005
IEEE
15 years 10 months ago
Hybrid Learning Neuro-Fuzzy Approach for Complex Modeling Using Asymmetric Fuzzy Sets
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
Chunshien Li, Kuo-Hsiang Cheng, Jiann-Der Lee
SCHEDULING
2010
116views more  SCHEDULING 2010»
15 years 2 months ago
Characterizing sets of jobs that admit optimal greedy-like algorithms
The “ Priority Algorithm” is a model of computation introduced by Borodin, Nielsen and Rackoff [BNR03] which formulates a wide class of greedy algorithms. For an arbitrary se...
Periklis A. Papakonstantinou, Charles Rackoff
ICASSP
2008
IEEE
15 years 11 months ago
Blind optimization of algorithm parameters for signal denoising by Monte-Carlo SURE
We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein’s Unbiased Risk Estimate (SURE) which provides a means of assessing ...
Sathish Ramani, Thierry Blu, Michael Unser
WWW
2010
ACM
15 years 11 months ago
Optimal rare query suggestion with implicit user feedback
Query suggestion has been an effective approach to help users narrow down to the information they need. However, most of existing studies focused on only popular/head queries. Si...
Yang Song, Li-wei He
FOCS
2005
IEEE
15 years 10 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys