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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
Distributed elections in an Archimedean ring of processors
2009-05-28 · via cs.DS updates on arXiv.org

Unlimited asynchronism is intolerable in real physically distributed computer systems. Such systems, synchronous or not, use clocks and timeouts. Therefore the magnitudes of elapsed absolute time in the system need to satisfy the axiom of Archimedes. Under this restriction of asynchronicity logically time-independent solutions can be derived which are nonetheless better (in number of message passes) than is possible otherwise. The use of clocks by the individual processors, in elections in a ring of asynchronous processors without central control, allows a deterministic solution which requires but a linear number of message passes. To obtain the result it has to be assumed that the clocks measure finitely proportional absolute time-spans for their time units, that is, the magnitudes of elapsed time in the ring network satisfy the axiom of Archimedes. As a result, some basic subtilities associated with distributed computations are highlighted. For instance, the known nonlinear lower bound on the required number of message passes is cracked. For the synchronous case, in which the necessary assumptions hold a fortiori, the method is -asymptotically- the most efficient one yet, and of optimal order of magnitude. The deterministic algorithm is of -asymptotically- optimal bit complexity, and, in the synchronous case, also yields an optimal method to determine the ring size. All of these results improve the known ones.