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cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
Tighter Upper Bounds for the Minimum Number of Calls and ...
V. H. Hovnanyan, H. E. Nahapetyan, Su. S. Poghosyan, V. S. Pogho · 2013-04-20 · via cs.DS updates on arXiv.org

The gossip problem (telephone problem) is an information dissemination problem in which each of $n$ nodes of a communication network has a unique piece of information that must be transmitted to all the other nodes using two-way communications (telephone calls) between the pairs of nodes. During a call between the given two nodes, they exchange the whole information known to them at that moment. In this paper we investigate the $k$-fault-tolerant gossip problem, which is a generalization of the gossip problem, where at most $k$ arbitrary faults of calls are allowed. The problem is to find the minimal number of calls $τ(n,k)$ needed to guarantee the $k$-fault-tolerance. We construct two classes of $k$-fault-tolerant gossip schemes (sequences of calls) and found two upper bounds of $τ(n,k)$, which improve the previously known results. The first upper bound for general even $n$ is $τ(n,k) \leq 1/2 n \lceil\log_2 n\rceil + 1/2 n k$. This result is used to obtain the upper bound for general odd $n$. From the expressions for the second upper bound it follows that $τ(n,k) \leq 2/3 n k + O(n)$ for large $n$. Assuming that the calls can take place simultaneously, it is also of interest to find $k$-fault-tolerant gossip schemes, which can spread the full information in minimal time. For even $n$ we showed that the minimal time is $T(n,k)=\lceil\log_2 n\rceil + k$.