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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
Peer to Peer Optimistic Collaborative Editing on XML-like...
2009-01-27 · via cs.DS updates on arXiv.org

Collaborative editing consists in editing a common document shared by several independent sites. This may give rise to conficts when two different users perform simultaneous uncompatible operations. Centralized systems solve this problem by using locks that prevent some modifications to occur and leave the resolution of confict to users. On the contrary, peer to peer (P2P) editing doesn't allow locks and the optimistic approach uses a Integration Transformation IT that reconciliates the conficting operations and ensures convergence (all copies are identical on each site). Two properties TP1 and TP2, relating the set of allowed operations Op and the transformation IT, have been shown to ensure the correctness of the process. The choice of the set Op is crucial to define an integration operation that satisfies TP1 and TP2. Many existing algorithms don't satisfy these properties and are indeed incorrect i.e. convergence is not guaranteed. No algorithm enjoying both properties is known for strings and little work has been done for XML trees in a pure P2P framework (that doesn't use time-stamps for instance). We focus on editing unranked unordered labeled trees, so-called XML-like trees that are considered for instance in the Harmony pro ject. We show that no transformation satisfying TP1 and TP2 can exist for a first set of operations but we show that TP1 and TP2 hold for a richer set of operations. We show how to combine our approach with any convergent editing process on strings (not necessarily based on integration transformation) to get a convergent process.