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Results 1 - 10
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2,617
On the Lower Bound of Local Optimum in k-means Algorithm
, 2006
"... The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, the k-means algorithm is very likely to converge to some local optimum which is much worse than the desired global optimal ..."
Abstract
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Cited by 6 (3 self)
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The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, the k-means algorithm is very likely to converge to some local optimum which is much worse than the desired global
Robust and Locally-Optimum Decentralized Detection with Censoring Sensors
- in 5 th Int. Conf. on Information Fusion
, 2002
"... In this paper, we examine decentralized detection problems in which a send/no-send rate (censoring rate) on the sensor decisions replaces the communication constraint of D-level sensor decisions in canonical parallel decentralized detection problems. Rago et. al. introduced the censoring problem to ..."
Abstract
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Cited by 14 (2 self)
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scenarios. Both a robust formulation of the censoring problem, and a locally-optimum formulation of the censoring problem are considered. We nd conditions under which the robust censoring problem can be solved by designing for the least-favorable distributions from the uncertainty classes. For the locally-optimum
LOCALLY OPTIMUM ESTIMATION IN WIRELESS SENSOR NETWORKS
"... A locally optimum approach for estimating a nonrandom pa-rameter lying in some small neighborhood of a known nom-inal value is considered. Reference is made to a decentral-ized estimation problem in the context of wireless sensor net-works, and particular attention is paid to the design of the quant ..."
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A locally optimum approach for estimating a nonrandom pa-rameter lying in some small neighborhood of a known nom-inal value is considered. Reference is made to a decentral-ized estimation problem in the context of wireless sensor net-works, and particular attention is paid to the design
Local Optimum Based Power Allocation Approach for Spectrum Sharing in Unlicensed Bands
"... Abstract. We present a novel local optimum based power allocation approach for spectrum sharing in unlicensed frequency bands. The proposed technique is based on the idea of dividing the network in a number of smaller sub-networks or clusters. Sum capacity of each cluster is maximized subject to co ..."
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Abstract. We present a novel local optimum based power allocation approach for spectrum sharing in unlicensed frequency bands. The proposed technique is based on the idea of dividing the network in a number of smaller sub-networks or clusters. Sum capacity of each cluster is maximized subject
Locally Optimum Adaptive Signal Processing Algorithms
"... Abstract—We propose a new analytic method for comparing constant gain adaptive signal processing algorithms. Specifically, estimates of the convergence speed of the algorithms allow for the definition of a local measure of performance, called the efficacy, that can be theoretically evaluated. By def ..."
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Abstract—We propose a new analytic method for comparing constant gain adaptive signal processing algorithms. Specifically, estimates of the convergence speed of the algorithms allow for the definition of a local measure of performance, called the efficacy, that can be theoretically evaluated
Sequential Detection of Signals with Locally Optimum Test Statistic
"... Based on local optimality, a novel sequential detection scheme is proposed in this paper. The performance of the proposed scheme is compared with that of the sequential probability ra-tio test (SPRT) and truncated SPRT (TSPRT). The proposed scheme is shown to have higher efficiency, lower complexity ..."
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Based on local optimality, a novel sequential detection scheme is proposed in this paper. The performance of the proposed scheme is compared with that of the sequential probability ra-tio test (SPRT) and truncated SPRT (TSPRT). The proposed scheme is shown to have higher efficiency, lower
Global Data Assimilation by Local Optimum Interpolation
, 1977
"... This is an informal unreviewed manuscript primarily intended for the exchange of information among NMC staff members. ..."
Abstract
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This is an informal unreviewed manuscript primarily intended for the exchange of information among NMC staff members.
Estimating Local Optimums in EM Algorithm over Gaussian Mixture Model
"... EM algorithm is a very popular iterationbased method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the ..."
Abstract
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Cited by 6 (0 self)
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EM algorithm is a very popular iterationbased method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than
Loopy belief propagation for approximate inference: An empirical study. In:
- Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract
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Cited by 676 (15 self)
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tiply connected networks: When loops are present, the network is no longer singly connected and local propaga tion schemes will invariably run into trouble . We believe there are general undiscovered theorems about the performance of belief propagation on loopy DAGs. These theo rems, which may have
Pareto local optimum sets in the biobjective traveling salesman problem: An experimental study
- METAHEURISTICS FOR MULTIOBJECTIVE OPTIMIZATION, LECTURE
, 2004
"... In this article, we study Pareto local optimum sets for the biobjective Traveling Salesman Problem applying straightforward extensions of local search algorithms for the single objective case. The performance of the local search algorithms is illustrated by experimental results obtained for well k ..."
Abstract
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Cited by 22 (5 self)
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In this article, we study Pareto local optimum sets for the biobjective Traveling Salesman Problem applying straightforward extensions of local search algorithms for the single objective case. The performance of the local search algorithms is illustrated by experimental results obtained for well
Results 1 - 10
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2,617
