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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
Approximate pattern matching with k-mismatches in packed ...
Emanuele Giaquinta, Szymon Grabowski, Kimmo Fredriksson · 2012-11-23 · via cs.DS updates on arXiv.org

Given strings $P$ of length $m$ and $T$ of length $n$ over an alphabet of size $σ$, the string matching with $k$-mismatches problem is to find the positions of all the substrings in $T$ that are at Hamming distance at most $k$ from $P$. If $T$ can be read only one character at the time the best known bounds are $O(n\sqrt{k\log k})$ and $O(n + n\sqrt{k/w}\log k)$ in the word-RAM model with word length $w$. In the RAM models (including $AC^0$ and word-RAM) it is possible to read up to $\floor{w / \log σ}$ characters in constant time if the characters of $T$ are encoded using $\ceil{\log σ}$ bits. The only solution for $k$-mismatches in packed text works in $O((n \logσ/\log n)\ceil{m \log (k + \log n / \logσ) / w} + n^{\varepsilon})$ time, for any $\varepsilon > 0$. We present an algorithm that runs in time $O(\frac{n}{\floor{w/(m\logσ)}} (1 + \log \min(k,σ) \log m / \logσ))$ in the $AC^0$ model if $m=O(w / \logσ)$ and $T$ is given packed. We also describe a simpler variant that runs in time $O(\frac{n}{\floor{w/(m\logσ)}}\log \min(m, \log w / \logσ))$ in the word-RAM model. The algorithms improve the existing bound for $w = Ω(\log^{1+ε}n)$, for any $ε> 0$. Based on the introduced technique, we present algorithms for several other approximate matching problems.