College Admissions and the Stability of Marriage

Whether sexual selection alone can drive the evolution of assortative mating in the presence of gene flow is a long-standing question in evolutionary biology. Here, we report a role for pairing dynamics of individuals when mate choice is mutual, which is sufficient for the evolution of assortative mating by sexual selection alone in the presence of gene flow. Through behavioural observation, individual-based simulation and population genetic analysis, we evaluate the pairing dynamics of coral reef fish in the genus Hypoplectrus (Serranidae), and the role these dynamics can play for the evolution of assortative mating. When mate choice is mutual and the stability of mating pairs is critical for reproductive success, the evolution of assortative mating in the presence of gene flow is not only possible, but is also a robust evolutionary outcome.

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“…Gale & Shapley [28] showed that , figure 2e,f ). Even when assortative mating is fixed after about 300 generations, i.e.…”

Section: Discussionmentioning

confidence: 93%

Pairing dynamics and the origin of species

2011

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“…In cLink, we reuse the adaptive filter implemented in SLINT+ [4]. This filter follows the idea of the stable marriage problem [25]. A pair of instances (x, y) is co-referent if its matching score mS core(x, y), satisfies the conditional statement of Eq.…”

Section: Co-reference Filtermentioning

confidence: 99%

Linked Data Entity Resolution System Enhanced by Configuration Learning Algorithm

Nguyen

Ichise

2016

IEICE Trans. Inf. & Syst.

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SUMMARY Linked data entity resolution is the detection of instances that reside in different repositories but co-describe the same topic. The quality of the resolution result depends on the appropriateness of the configuration, including the selected matching properties and the similarity measures. Because such configuration details are currently set differently across domains and repositories, a general resolution approach for every repository is necessary. In this paper, we present cLink, a system that can perform entity resolution on any input effectively by using a learning algorithm to find the optimal configuration. Experiments show that cLink achieves high performance even when being given only a small amount of training data. cLink also outperforms recent systems, including the ones that use the supervised learning approach.

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“…The firm proposing deferred acceptance algorithm was proposed by Gale and Shapley in 1962 and has solved many problems such as National Resident/ Hospital program, college admission [23], roommate market and so on [11]. The weak-optimal channel allocation mechanism that can maximize the overall utility with lower computation complexity is obtained by this algorithm.…”

Section: Proposed Algorithmmentioning

confidence: 99%