Results 221 to 230 of about 492,566 (255)
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On greedy randomized block Kaczmarz method for consistent linear systems
, 2021The randomized block Kaczmarz method aims to solve linear system A x = b by iteratively projecting the current estimate to the solution space of a subset of the constraints.
Yong Liu, Chuanqing Gu
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Information Sciences, 2021
In this paper we discuss incomplete data sets with missing attribute values interpreted as “do not care” conditions. For data mining, we use two types of probabilistic approximations, global and saturated. Such approximations are constructed from two types of granules, characteristic sets and maximal consistent blocks. We present results of experiments
Patrick G. Clark +3 more
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In this paper we discuss incomplete data sets with missing attribute values interpreted as “do not care” conditions. For data mining, we use two types of probabilistic approximations, global and saturated. Such approximations are constructed from two types of granules, characteristic sets and maximal consistent blocks. We present results of experiments
Patrick G. Clark +3 more
openaire +1 more source
Characteristic Sets and Generalized Maximal Consistent Blocks in Mining Incomplete Data
Information Sciences, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patrick G. Clark +3 more
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International Journal of Approximate Reasoning
Bin Pang, Ju-Sheng Mi, Wei-Zhi Wu
exaly +2 more sources
Bin Pang, Ju-Sheng Mi, Wei-Zhi Wu
exaly +2 more sources
2018
We discuss two interpretations of missing attribute values, lost values and “do not care” conditions. Both interpretations may be used for data mining based on characteristic sets. On the other hand, maximal consistent blocks were originally defined for incomplete data sets with “do not care” conditions, using only lower and upper approximations.
Patrick G. Clark +3 more
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We discuss two interpretations of missing attribute values, lost values and “do not care” conditions. Both interpretations may be used for data mining based on characteristic sets. On the other hand, maximal consistent blocks were originally defined for incomplete data sets with “do not care” conditions, using only lower and upper approximations.
Patrick G. Clark +3 more
openaire +1 more source
Complexity of Rule Sets Induced by Characteristic Sets and Generalized Maximal Consistent Blocks
2018We study mining incomplete data sets with two interpretations of missing attribute values, lost values and “do not care” conditions. For data mining we use characteristic sets and generalized maximal consistent blocks. Additionally, we use three types of probabilistic approximations, lower, middle and upper, so altogether we apply six approaches to ...
Patrick G. Clark +4 more
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IEEE Transactions on Signal Processing, 2019
This paper deals with adaptive radar detection of targets in the presence of Gaussian disturbance sharing a block-diagonal covariance structure. The problem is formulated according to a very general signal model, which contains the point-like, range ...
Mengjiao Tang +4 more
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This paper deals with adaptive radar detection of targets in the presence of Gaussian disturbance sharing a block-diagonal covariance structure. The problem is formulated according to a very general signal model, which contains the point-like, range ...
Mengjiao Tang +4 more
semanticscholar +1 more source
Structure and functional expression of a member of the low voltage-activated calcium channel family.
Science, 1993T. Soong +5 more
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Proton block of the pore underlies the inhibition of hERG cardiac K+ channels during acidosis.
American Journal of Physiology - Cell Physiology, 2012Aaron C. Van Slyke +6 more
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