Titlebook: Structural Information and Communication Complexity; 30th International C Sergio Rajsbaum,Alkida Balliu,Dennis Olivetti Conference proceedi

LVAD360

Learning Hierarchically-Structured Concepts II: Overlapping Concepts, and Networks with Feedbackbrain-like neural networks, how these representations might be used to recognize the concepts, and how these representations might be learned. In Lynch and Mallmann-Trenn (Neural Networks, 2021), we considered simple tree-structured concepts and feed-forward layered networks. Here we extend the mode

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Lockless Blockchain Sharding with Multiversion Control among multiple clusters of nodes. Shards require less storage capacity and communication and computation cost per node than the existing whole blockchain networks, and they operate in parallel to maximize performance. However, existing sharding solutions use locks for transaction isolation which lo

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Self-adjusting Linear Networks with Ladder Demand Graphe mapping of communication requests into the network topology. SANs can reduce routing costs for frequently communicating node pairs by paying a cost for adjusting the embedding. This is particularly beneficial when the demand has structure, which the network can adapt to. Demand can be represented

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Compatibility of Convergence Algorithms for Autonomous Mobile Robots (Extended Abstract)and operates in Look-Compute-Move cycles, i.e., identifies the robots’ positions, computes the destination by the target function, and then moves there. Robots can have different target functions. Let . and . be a set of target functions and a problem, respectively. If the robots whose target functi

CRP743

: A BFT Protocol with Provable Performance Under Attackions. At its core, . parallelizes the execution of requests by allowing all replicas to act as leaders independently. Leader parallelization distributes the load over all replicas. Consequently, . fully utilizes all correct replicas’ processing power and increases throughput by overcoming the single

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