Results 261 to 270 of about 541,185 (309)
Powder Spreading Dynamics and Process Optimization at a Heterogeneous Interface for Z-Direction Multi-Material Laser Powder Bed Fusion. [PDF]
Materials (Basel)Xiang Z, Ma S, Han F, Wang J.
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Concrete Mesostructure Modeling via Random Radius Field and Rigid Body Dynamics Packing. [PDF]
Materials (Basel)Zhang Z +5 more
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IEEE Transactions on Reliability, 2005 Our paper proposes an implementable procedure for using the method of quasi-random sequences in software debug testing. In random testing, the sequence of tests (if considered as points in an n-dimensional unit hypercube) will give rise to regions where there are clusters of points, as well as underpopulated regions.
Tsong Yueh Chen, Robert G. Merkel
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Quasi-Randomness and Algorithmic Regularity for Graphs with General Degree Distributions [PDF]
SIAM Journal on Computing, 2010 We deal with two intimately related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to express how much a given graph “resembles” a random one.
Noga Alon, Amin Coja-Oghlan, Hiep Han
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Journal of Graph Theory, 1991
AbstractWe introduce a large class of tournament properties, all of which are shared by almost all random tournaments. These properties, which we term “quasi‐random,” have the property that tournaments possessing any one of the properties must of necessity possess them all.
Fan R. K. Chung, Ronald L. Graham
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AbstractWe introduce a large class of tournament properties, all of which are shared by almost all random tournaments. These properties, which we term “quasi‐random,” have the property that tournaments possessing any one of the properties must of necessity possess them all.
Fan R. K. Chung, Ronald L. Graham
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Communication Complexity and Quasi Randomness
SIAM Journal on Discrete Mathematics, 1993Summary: The multiparty communication complexity concerns the least number of bits that must be exchanged among a number of players to collaboratively compute a Boolean function \(f(x_ 1,\dots,x_ k)\), while each player knows at most \(t\) inputs for some fixed ...
Fan R. K. Chung, Prasad Tetali
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Combinatorica, 2002
Let \(G_{1/2}(n)\) denote a random graph with \(n\) vertices in which each pair is selected to be an edge independently with probability \(1/2\). Almost all of them satisfy several basic properties which turn out to be equivalent. Families of graphs satisfying this equivalence class of properties are called quasi-random, see e.g. \textit{F. R. K. Chung}
Fan R. K. Chung, Ronald L. Graham
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Let \(G_{1/2}(n)\) denote a random graph with \(n\) vertices in which each pair is selected to be an edge independently with probability \(1/2\). Almost all of them satisfy several basic properties which turn out to be equivalent. Families of graphs satisfying this equivalence class of properties are called quasi-random, see e.g. \textit{F. R. K. Chung}
Fan R. K. Chung, Ronald L. Graham
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Reinforced quasi-random forest
Pattern Recognition, 2019Abstract We propose a reinforced quasi-random forest for classification task. Reinforcement is performed iteratively by adding new trees to the forest. Our method assigns an importance to each of the attributes and identifies the attributes that causes the mis-classification of data points during training.
Angshuman Paul, Dipti Prasad Mukherjee
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