Danny Krizanc, Pat Morin, Michiel Smid
We consider algorithms for preprocessing labelled lists and trees so that, for any two nodes u and v we can answer queries of the form: What is the mode or median label in the sequence of labels on the path from u to v.
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Distribution-Free Testing of Decision Lists with a Sublinear Number of Queries
该研究提出首个决策列表无分布测试的次线性查询算法，证明其测试比学习更易，同时给出该类测试器的查询及样本复杂度下界。
This work shows that the following problems are equivalent, both in theory and in practice: - median filtering: given an $n$-element vector, compute the sliding window median with window size $k$, - piecewise sorting: given an $n$-element vector, divide it in $n/k$ blocks of length $k$ and sort each block. By prior work, median filtering is known to be at least as hard as piecewise sorting: with a single median filter operation we can sort $Θ(n/k)$ blocks of length $Θ(k)$. The present work shows that median filtering is also as easy as piecewise sorting: we can do median filtering with one pie…
We consider the following problem: given an unsorted array of $n$ elements, and a sequence of intervals in the array, compute the median in each of the subarrays defined by the intervals. We describe a simple algorithm which uses O(n) space and needs $O(n\log k + k\log n)$ time to answer the first $k$ queries. This improves previous algorithms by a logarithmic factor and matches a lower bound for $k=O(n)$. Since the algorithm decomposes the range of element values rather than the array, it has natural generalizations to higher dimensional problems -- it reduces a range median query to a logari…
In this paper we present novel algorithmic techniques with a O(H(N)+N/H(N)) time complexity for performing several types of queries and updates on general rooted trees, binary search trees and lists of size N. For rooted trees we introduce a new compressed super-node tree representation which can be used for efficiently addressing a wide range of applications. For binary search trees we discuss the idea of globally rebuilding the entire tree in a fully balanced manner whenever the height of the tree exceeds the value of a conveniently chosen function of the number of tree nodes. In the end of …
Let $h\colon\mathbb{Z}^+\to\mathbb{Z}^+\setminus\{1\}$ be any function such that $h(n)$ and $\lceil n^{1/h(n)}\rceil$ are computable from $n$ in $O(h(n)\cdot n^{1+1/h(n)})$ time. We show that given any $n$-point metric space $(M,d)$, the problem of finding $\mathop{\mathrm{argmin}}_{i\in M}\,\sum_{j\in M}\,d(i,j)$ (breaking ties arbitrarily) has a deterministic, $O(h(n)\cdot n^{1+1/h(n)})$-time, $O(n^{1+1/h(n)})$-query, $(2\,h(n))$-approximation and nonadaptive algorithm. Our proofs modify those of Chang~\cite{Cha15, Cha15CMCT} with the following improvements: (1) We improve Chang's~\cite{Cha1…
Given an $n$-point metric space $(M,d)$, {\sc metric $1$-median} asks for a point $p\in M$ minimizing $\sum_{x\in M}\,d(p,x)$. We show that for each computable function $f\colon \mathbb{Z}^+\to\mathbb{Z}^+$ satisfying $f(n)=ω(1)$, {\sc metric $1$-median} has a deterministic, $o(n)$-query, $o(f(n)\cdot\log n)$-approximation and nonadaptive algorithm. Previously, no deterministic $o(n)$-query $o(n)$-approximation algorithms are known for {\sc metric $1$-median}. On the negative side, we prove each deterministic $O(n)$-query algorithm for {\sc metric $1$-median} to be not $(δ\log n)$-approximate …
We define a new interactive differentially private mechanism -- the median mechanism -- for answering arbitrary predicate queries that arrive online. Relative to fixed accuracy and privacy constraints, this mechanism can answer exponentially more queries than the previously best known interactive privacy mechanism (the Laplace mechanism, which independently perturbs each query result). Our guarantee is almost the best possible, even for non-interactive privacy mechanisms. Conceptually, the median mechanism is the first privacy mechanism capable of identifying and exploiting correlations among …
We perform experimental studies on data structures that answer path median, path counting, and path reporting queries in weighted trees. These query problems generalize the well-known range median query problem in arrays, as well as the $2d$ orthogonal range counting and reporting problems in planar point sets, to tree structured data. We propose practical realizations of the latest theoretical results on path queries. Our data structures, which use tree extraction, heavy-path decomposition and wavelet trees, are implemented in both succinct and pointer-based form. Our succinct data structures…
Let $H$ be an undirected graph. In the List $H$-Homomorphism Problem, given an undirected graph $G$ with a list constraint $L(v) \subseteq V(H)$ for each variable $v \in V(G)$, the objective is to find a list $H$-homomorphism $f:V(G) \to V(H)$, that is, $f(v) \in L(v)$ for every $v \in V(G)$ and $(f(u),f(v)) \in E(H)$ whenever $(u,v) \in E(G)$. We consider the following problem: given a map $f:V(G) \to V(H)$ as an oracle access, the objective is to decide with high probability whether $f$ is a list $H$-homomorphism or \textit{far} from any list $H$-homomorphisms. The efficiency of an algorithm…
We show how to use a balanced wavelet tree as a data structure that stores a list of numbers and supports efficient {\em range quantile queries}. A range quantile query takes a rank and the endpoints of a sublist and returns the number with that rank in that sublist. For example, if the rank is half the sublist's length, then the query returns the sublist's median. We also show how these queries can be used to support space-efficient {\em coloured range reporting} and {\em document listing}.
The dynamic partial sorting problem asks for an algorithm that maintains lists of numbers under the link, cut and change value operations, and queries the sorted sequence of the $k$ least numbers in one of the lists. We first solve the problem in $O(k\log (n))$ time for queries and $O(\log (n))$ time for updates using the tournament tree data structure, where $n$ is the number of elements in the lists. We then introduce a layered tournament tree data structure and solve the same problem in $O(\log_φ^* (n) k\log (k))$ time for queries and $O\left(\log (n)\cdot\log^2\log (n)\right)$ for updates,…
The problem of Text Indexing is a fundamental algorithmic problem in which one wishes to preprocess a text in order to quickly locate pattern queries within the text. In the ever evolving world of dynamic and on-line data, there is also a need for developing solutions to index texts which arrive on-line, i.e. a character at a time, and still be able to quickly locate said patterns. In this paper, a new solution for on-line indexing is presented by providing an on-line suffix tree construction in $O(\log \log n + \log\log |Σ|)$ worst-case expected time per character, where $n$ is the size of th…
Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensors, however, have significant power constraint (battery life), making communication very expensive. Another important issue in the context of sensor-based information systems is that individual sensor readings are inherently unreliable. In order to address these two aspects, sensor database systems like TinyDB and Cougar enable in-network data aggregation to reduce the communication cost and improve reliability. The existing data aggregation techniques, however, are limited to relative…
In the classical binary search in a path the aim is to detect an unknown target by asking as few queries as possible, where each query reveals the direction to the target. This binary search algorithm has been recently extended by [Emamjomeh-Zadeh et al., STOC, 2016] to the problem of detecting a target in an arbitrary graph. Similarly to the classical case in the path, the algorithm of Emamjomeh-Zadeh et al. maintains a candidates' set for the target, while each query asks an appropriately chosen vertex-- the "median"--which minimises a potential $Φ$ among the vertices of the candidates' set.…
We present bundled references, a new building block to provide linearizable range query operations for highly concurrent linked data structures. Bundled references allow range queries to traverse a path through the data structure that is consistent with the target atomic snapshot and is made of the minimal amount of nodes that should be accessed to preserve linearizability. We implement our technique into a skip list, a binary search tree, and a linked list data structure. Our evaluation reveals that in mixed workloads, our design improves upon the state-of-the-art techniques by 3.9x for a ski…
In this paper, we present a framework based on a simple data structure and parameterized algorithms for the problems of finding items in an unsorted list of linearly ordered items based on their rank (selection) or value (search). As a side-effect of answering these online selection and search queries, we progressively sort the list. Our algorithms are based on Hoare's Quickselect, and are parameterized based on the pivot selection method. For example, if we choose the pivot as the last item in a subinterval, our framework yields algorithms that will answer q<=n unique selection and/or search …
We present bundled references, a new building block to provide linearizable range query operations for highly concurrent lock-based linked data structures. Bundled references allow range queries to traverse a path through the data structure that is consistent with the target atomic snapshot. We demonstrate our technique with three data structures: a linked list, skip list, and a binary search tree. Our evaluation reveals that in mixed workloads, our design can improve upon the state-of-the-art techniques by 1.2x-1.8x for a skip list and 1.3x-3.7x for a binary search tree. We also integrate our…
Datasets are often reused to perform multiple statistical analyses in an adaptive way, in which each analysis may depend on the outcomes of previous analyses on the same dataset. Standard statistical guarantees do not account for these dependencies and little is known about how to provably avoid overfitting and false discovery in the adaptive setting. We consider a natural formalization of this problem in which the goal is to design an algorithm that, given a limited number of i.i.d.~samples from an unknown distribution, can answer adaptively-chosen queries about that distribution. We present …
Data structure for node connectivity and cut queries
本文提出一种紧凑数据结构，支持无向图中 $k$-有界节点连通性查询和最小割查询，在 $O(kn)$ 空间内实现 $O(1)$ 查询时间，并推广了 Pettie-Yin 的结果。
For any $ε\in (0,1)$, a $(1+ε)$-approximate range mode query asks for the position of an element whose frequency in the query range is at most a factor $(1+ε)$ smaller than the true mode. For this problem, we design an $O(n/ε)$ bit data structure supporting queries in $O(\lg(1/ε))$ time. This is an encoding data structure which does not require access to the input sequence; we prove the space cost is asymptotically optimal for constant $ε$. Our solution improves the previous best result of Greve et al. (Cell Probe Lower Bounds and Approximations for Range Mode, ICALP'10) by reducing the space …
We show that any quantum algorithm searching an ordered list of n elements needs to examine at least 1/12 log n-O(1) of them. Classically, log n queries are both necessary and sufficient. This shows that quantum algorithms can achieve only a constant speedup for this problem. Our result improves lower bounds of Buhrman and de Wolf(quant-ph/9811046) and Farhi, Goldstone, Gutmann and Sipser (quant-ph/9812057).
We design quantum algorithms for maximum matching. Working in the query model, in both adjacency matrix and adjacency list settings, we improve on the best known algorithms for general graphs, matching previously obtained results for bipartite graphs. In particular, for a graph with $n$ nodes and $m$ edges, our algorithm makes $O(n^{7/4})$ queries in the matrix model and $O(n^{3/4}(m+n)^{1/2})$ queries in the list model. Our approach combines Gabow's classical maximum matching algorithm [Gabow, Fundamenta Informaticae, '17] with the guessing tree method of Beigi and Taghavi [Beigi and Taghavi,…
Robust Max Selection
提出不可靠比较下的鲁棒最大值选择模型，给出最小输出集及确定性查询复杂度界，并设计近最优随机两阶段算法。
Wavelet trees are widely used in the representation of sequences, permutations, text collections, binary relations, discrete points, and other succinct data structures. We show, however, that this still falls short of exploiting all of the virtues of this versatile data structure. In particular we show how to use wavelet trees to solve fundamental algorithmic problems such as {\em range quantile} queries, {\em range next value} queries, and {\em range intersection} queries. We explore several applications of these queries in Information Retrieval, in particular {\em document retrieval} in hier…
Link-cut trees have been introduced by D.D. Sleator and R.E. Tarjan (Journal of Computer and System Sciences, 1983) with the aim of efficiently maintaining a forest of vertex-disjoint dynamic rooted trees under cut and link operations. These operations respectively disconnect a subtree from a tree, and join two trees by an edge. Additionally, link-cut trees allow to change the root of a tree and to perform a number of updates and queries on cost values defined on the arcs of the trees. All these operations are performed in $O(\log\, n)$ amortized or worst-case time, depending on the implementa…
We engineer an algorithm to solve the approximate dictionary matching problem. Given a list of words $\mathcal{W}$, maximum distance $d$ fixed at preprocessing time and a query word $q$, we would like to retrieve all words from $\mathcal{W}$ that can be transformed into $q$ with $d$ or less edit operations. We present data structures that support fault tolerant queries by generating an index. On top of that, we present a generalization of the method that eases memory consumption and preprocessing time significantly. At the same time, running times of queries are virtually unaffected. We are ab…
We study the problem of estimating the size of maximum matching and minimum vertex cover in sublinear time. Denoting the number of vertices by $n$ and the average degree in the graph by $\bar{d}$, we obtain the following results for both problems: * A multiplicative $(2+ε)$-approximation that takes $\tilde{O}(n/ε^2)$ time using adjacency list queries. * A multiplicative-additive $(2, εn)$-approximation in $\tilde{O}((\bar{d} + 1)/ε^2)$ time using adjacency list queries. * A multiplicative-additive $(2, εn)$-approximation in $\tilde{O}(n/ε^{3})$ time using adjacency matrix queries. All three re…
Wait-free Trees with Asymptotically-Efficient Range Queries
针对现有并发树不支持高效聚合范围查询的问题，提出基于交递帮助的无等待元数据维护机制，实现兼具渐近效率与可扩展性的无等待平衡二叉搜索树，实验验证了其加速效果。
This is an algorithm for finding neighbors when the objects can freely move and have no predefined position. The query consists in finding neighbors for a center location and a given radius. Space is discretized in cubic cells. This algorithm introduces a direct spherical indexing that gives the list of all cells making up the query sphere, for any radius and any center location. It can additionally take in account both cyclic and non-cyclic regions of interest. Finding only the K nearest neighbors naturally benefits from the spherical indexing by minimally running through the sphere from cent…
In previous work, the author introduced the B-treap, a uniquely represented B-tree analogue, and proved strong performance guarantees for it. However, the B-treap maintains complex invariants and is very complex to implement. In this paper we introduce the B-skip-list, which has most of the guarantees of the B-treap, but is vastly simpler and easier to implement. Like the B-treap, the B-skip-list may be used to construct strongly history-independent index structures and filesystems; such constructions reveal no information about the historical sequence of operations that led to the current log…
Metric Clustering and MST with Strong and Weak Distance Oracles
本文研究在包含强（精确）和弱（可能被破坏）距离预言机的度量空间中的优化问题，提出了针对聚类和最小生成树（MST）的近似算法与匹配下界，在仅使用极少强预言机查询下实现与基线相当的解质量。
Faster Estimation of the Average Degree of a Graph Using Random Edges and Structural Queries
本文研究图平均度的亚线性估计，利用随机边和对查询等结构查询，在标准模型下实现 $\widetilde{O}(n^{1/4})$ 查询的近乎最优算法，并证明在 $n$ 未知时结构查询无帮助。
Estimating the distribution and quantiles of data is a foundational task in data mining and data science. We study algorithms which provide accurate results for extreme quantile queries using a small amount of space, thus helping to understand the tails of the input distribution. Namely, we focus on two recent state-of-the-art solutions: $t$-digest and ReqSketch. While $t$-digest is a popular compact summary which works well in a variety of settings, ReqSketch comes with formal accuracy guarantees at the cost of its size growing as new observations are inserted. In this work, we provide insigh…
Learning-Augmented Search Data Structures
研究整合机器学习建议改进传统搜索数据结构，提出学习增强的跳表和KD树，在预言机可能出错时仍保证接近最优的期望搜索时间并具鲁棒性，且在合成与真实数据集上优于传统结构。
We investigate sublinear-time algorithms that take partially erased graphs represented by adjacency lists as input. Our algorithms make degree and neighbor queries to the input graph and work with a specified fraction of adversarial erasures in adjacency entries. We focus on two computational tasks: testing if a graph is connected or $\varepsilon$-far from connected and estimating the average degree. For testing connectedness, we discover a threshold phenomenon: when the fraction of erasures is less than $\varepsilon$, this property can be tested efficiently (in time independent of the size of…
Datasets are often used multiple times and each successive analysis may depend on the outcome of previous analyses. Standard techniques for ensuring generalization and statistical validity do not account for this adaptive dependence. A recent line of work studies the challenges that arise from such adaptive data reuse by considering the problem of answering a sequence of "queries" about the data distribution where each query may depend arbitrarily on answers to previous queries. The strongest results obtained for this problem rely on differential privacy -- a strong notion of algorithmic stabi…
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