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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
Small Uncolored and Colored Choice Dictionaries
Torben Hagerup · 2018-09-20 · via cs.DS updates on arXiv.org

A choice dictionary can be initialized with a parameter $n\in\mathbb{N}$ and subsequently maintains an initially empty subset $S$ of $\{1,\ldots,n\}$ under insertion, deletion, membership queries and an operation $\textit{choice}$ that returns an arbitrary element of $S$. The choice dictionary is fundamental in space-efficient computing and has numerous applications. The best previous choice dictionary can be initialized with $n$ and $t\in\mathbb{N}$ and subsequently executes all operations in $O(t)$ time and occupies $n+O(n({t/w})^t+\log n)$ bits on a word RAM with a word length of $w=Ω(\log n)$ bits. We describe a new choice dictionary that executes all operations in constant time and, in addition to the space needed to store the integer $n$, occupies only $n+1$ bits, which is shown to be optimal if $w=o(n)$. A generalization of the choice dictionary called a colored choice dictionary is initialized with $c\in\mathbb{N}$ in addition to $n$ and subsequently maintains a semipartition $(S_0,\ldots,S_{c-1})$ of $\{1,\ldots,n\}$ under the operations $\textit{setcolor}(j,\ell)$, which moves $\ell$ from its current subset to $S_j$, $\textit{color}(\ell)$, which returns the unique $j\in\{0,\ldots,c-1\}$ with $\ell\in S_j$, and $\textit{choice}(j)$, which returns an arbitrary element of $S_j$. We describe new colored choice dictionaries that, if initialized with constant $c$, execute $\textit{setcolor}$, $\textit{color}$ and $\textit{choice}$ in constant time and occupy $n\log_2\!c+1$ bits plus the space needed to store $n$ if $c$ is a power of 2, and at most $n\log_2\!c+n^ε$ bits in general, for arbitrary fixed $ε>0$. We also study the possibility of iterating over the set $S$ or over $S_j$ for given $j\in\{0,\ldots,c-1\}$ and an application of this to breadth-first search.