Max-min matching problems with multiple assignments

Dondeti, V. Reddy; Emmons, Hamilton

doi:10.1007/bf02190106

Cited by 6 publications

(3 citation statements)

References 9 publications

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“…We conducted patch-to-patch matching that minimized this distance metric by using a variant of the classic Hungarian assignment algorithm (Bourgeois and Lassalle 1971) that allows many-to-one assignments (Dondeti and Emmons 1996), because individual subject patches were sometimes spatially discontinuous (e.g., the medial patches of the Cingulo-opercular system in Fig. 2A).…”

Section: Template Matching For System Identification In Individual Su...mentioning

confidence: 99%

Individual Variability of the System-Level Organization of the Human Brain

Gordon

Laumann²,

Adeyemo³

et al. 2015

Cereb. Cortex

182

268

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Recent functional magnetic resonance imaging-based resting-state functional connectivity analyses of group average data have characterized large-scale systems that represent a high level in the organizational hierarchy of the human brain. These systems are likely to vary spatially across individuals, even after anatomical alignment, but the characteristics of this variance are unknown. Here, we characterized large-scale brain systems across two independent datasets of young adults. In these individuals, we were able to identify brain systems that were similar to those described in the group average, and we observed that individuals had consistent topological arrangement of the system features present in the group average. However, the size of system features varied across individuals in systematic ways, such that expansion of one feature of a given system predicted expansion of other parts of the system. Individual-specific systems also contained unique topological features not present in group average systems; some of these features were consistent across a minority of individuals. These effects were observed even after controlling for data quality and for the accuracy of anatomical registration. The variability characterized here has important implications for cognitive neuroscience investigations, which often assume the functional equivalence of aligned brain regions across individuals.

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Section: Template Matching For System Identification In Individual Su...mentioning

confidence: 99%

Individual Variability of the System-Level Organization of the Human Brain

Gordon

Laumann²,

Adeyemo³

et al. 2015

Cereb. Cortex

182

268

View full text Add to dashboard Cite

show abstract

“…Particularly, the mathematical formulation of the assignment problem corresponds to a weighted perfect bipartite matching problem. Hence, the global optimal channel assignment solution (i.e., α (i) j ) can be found using the Hungarian algorithm, which has a polynomial-time [13]) and codes are readily available for its implementation [14].…”

Section: Proposed Algorithmmentioning

confidence: 99%

Channel Assignment and Access Protocols for Spectrum-Agile Networks with Single-Transceiver Radios

Krunz

2011

Networking 2011

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Many spectrum access/sharing algorithms for cognitive radio networks (CRNs) have been designed assuming multiple transceivers per CR user. However, in practice, such an assumption may not hold due to hardware cost. In this paper, we address the problem of assigning channels to CR transmissions, assuming one transceiver per CR. The primary goal of our design is to maximize the number of feasible concurrent CR transmissions with respect to both spectrum assignment and transmission power. Energy conservation is also treated, but as a secondary objective. The problem is posed as a utility maximization problem subject to target rate demand and interference constraints. For multi-transceiver CRNs, this optimization problem is known to be NPhard. However, under the practical setting of a single transceiver per CR user, we show that this problem can be optimally solved in polynomial time. Specifically, we present a centralized algorithm for the channel assignment problem based on bipartite matching. We then integrate this algorithm into distributed MAC protocols. First, we consider a singlehop CRN, for which we introduce a CSMA-like MAC protocol that uses an access window (AW) for exchanging control information prior to data transmissions. This approach allows us to realize a centralized algorithm in a distributed manner. We then develop a distributed MAC protocol (WFC-MAC) for a multi-hop CRN. WFC-MAC improves the CRN throughput through a novel distributed channel assignment that relies only on information provided by the two communicating users. We compare the performance of our schemes with CSMA/CA variants. The results show that our schemes significantly decrease the blocking rate of CR transmissions, and hence improves the network throughput.

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“…Based on the concepts of equity [25], the metrics of proportion fairness (PF) and max-min fairness (MMF) [33] have been respectively proposed. PF and MMF have been widely used for computation network and transportation [9,17,36]. Their formal formulations in the provider fair recommendation scenario will be explained in Section 3.…”

Section: Introductionmentioning

confidence: 99%

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

Chen

et al. 2023

Proceedings of the ACM Web Conference 2023

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Max-min matching problems with multiple assignments

Cited by 6 publications

References 9 publications

Individual Variability of the System-Level Organization of the Human Brain

Individual Variability of the System-Level Organization of the Human Brain

Channel Assignment and Access Protocols for Spectrum-Agile Networks with Single-Transceiver Radios

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

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