Consider G as a graph with n vertices and k as a non-negative integer. A set of vertices D in graph G is considered a k-dominating set (or a k-tuple dominating set, or a total k-dominating set) if the condition |NG(v)...
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In the 3-Hitting Set problem, the input is a hypergraph G such that the size of every hyperedge of G is at most 3, and an integers k, and the goal is to decide whether there is a set S of at most k vertices such that ...
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We introduce a new replicable boosting algorithm which significantly improves the sample complexity compared to previous algorithms. The algorithm works by doing two layers of majority voting, using an improved versio...
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An explicit algorithm is given for the computation of the Hausdorff dimension of the closure of a regular branch group in terms of an arbitrary branch structure. We implement this algorithm in GAP and apply it to a fa...
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In this paper, we propose a fast and convergent algorithm to solve unassigned distance geometry problems (uDGP). Technically, we construct a novel quadratic measurement model by leveraging 0-norm instead of 1-norm in ...
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We present the first nearly-optimal bounds on the consensus time for the well-known synchronous consensus dynamics, specifically 3-Majority and 2-Choices, for an arbitrary number of opinions. In synchronous consensus ...
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This paper investigates the issue of robust relative orbit synchronization control for spacecraft cluster subjects to space perturbation. First, the relative orbit dynamics of the leader-follower spacecraft cluster is...
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This paper investigates the issue of robust relative orbit synchronization control for spacecraft cluster subjects to space perturbation. First, the relative orbit dynamics of the leader-follower spacecraft cluster is established. Combined with P-type learning algorithm and sliding mode control (SMC) strategy, a novel distributed learning SMC (LSMC) strategy with the consensus algorithm is explored such that all the follower spacecrafts converge to the target relative position and their velocities tend to the leader spacecraft. The distributed P-type learning algorithm is used to update and compensate space perturbation for all the follower spacecrafts. The proposed LSMC approach has the potential to achieve higher control accuracy than the traditional SMC one while it has the lower computation burden than the distributed adaptive SMC one. The stability analysis of the proposed distributed LSMC strategy is provided in detail. Finally, a numerical example is simulated to illustrate the effectiveness and superiority of the proposed distributed LSMC-based relative orbit synchronization control for spacecraft cluster.
We present a fast algorithm for maximizing monotone submodular function over a matroid constraint. It is a (1-1/e-ϵ) approximation algorithm with nearly-linear time complexity, where ϵ>0. We improve the complexity ...
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We study the problem of federated learning (FL) in the presence of stragglers, the devices that are intermittently connected to the central server. Although under the newly developed semi-decentralized federated learn...
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ISBN:
(数字)9798350348934
ISBN:
(纸本)9798350348941
We study the problem of federated learning (FL) in the presence of stragglers, the devices that are intermittently connected to the central server. Although under the newly developed semi-decentralized federated learning (SFL) framework, gradient coding (GC) can be applied to evade the stragglers by letting them relay their locally computed gradients to the central server via non-stragglers, the communication burden of GC in SFL is very heavy. To overcome this drawback, motivated by the communication-optimal exact consensus algorithm (CECA) proposed in the literature, we propose a new communicationefficient semi-decentralized method (COFFEE) in SFL. In each round of COFFEE, the devices take a certain number of steps towards consensus in a decentralized manner with high communication efficiency, and each of them acquires the average of its own gradient and the gradients of its previous neighbors. After that, the non-straggler devices send the obtained average results to the server, which aggregates the received vectors to yield the global model update. The learning performance of the proposed method is analyzed through convergence analysis. Finally, we run simulations to show the superiority of COFFEE over the baseline method, i.e., GC in SFL.
Since primary nodes play a critical leadership role in PBFT (Practical Byzantine Fault Tolerance) consensus algorithm, it is mandatory to perform an update process for eliminating the malicious primary nodes so as to ...
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ISBN:
(数字)9798331506209
ISBN:
(纸本)9798331506216
Since primary nodes play a critical leadership role in PBFT (Practical Byzantine Fault Tolerance) consensus algorithm, it is mandatory to perform an update process for eliminating the malicious primary nodes so as to maintain the security level of PBFT. As it is convenient to calculate node reputations, most of existing updating schemes select the node with the highest reputation as the primary node in every consensus round. However, the round-by-round reputation update mechanism inevitably increases the communication overhead and consensus latency. To reduce the number of update times, we propose an algorithm based on an adaptive reputation mechanism, named Commit Block PBFT or CBPBFT for short. In this mechanism, a node’s reputation is determined by the number of its committed blocks during the most recent period as a primary node. As the reputation update adaptively occurs according to the number of blocks committed by the primary node, the mechanism significantly decreases the frequency of reputation updates, and hence increases the consensus performance. Experimental results show that, CBPBFT reduces the probability of a Byzantine node gaining leadership by 15% and decreases communication latency by 15% to 32% in comparison with the state-of-the art.
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