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Scale-Free Compact Routing Schemes in Networks of Low Doubling Dimension

We consider compact routing schemes in networks of low doubling dimension, where the doubling dimension is the least value α such that any ball... (more)

Distributed Algorithms for End-to-End Packet Scheduling in Wireless Ad Hoc Networks

Packet scheduling is a particular challenge in wireless networks due to interference from nearby transmissions. A distance-2 interference model serves... (more)

Fast Constructions of Lightweight Spanners for General Graphs

It is long known that for every weighted undirected n-vertex m-edge graph G = (V, E, ω), and every integer k ⩾ 1, there exists a ((2k... (more)

The Two-Edge Connectivity Survivable-Network Design Problem in Planar Graphs

Consider the following problem: given a graph with edge costs and a subset Q of vertices, find a minimum-cost subgraph in which there are two... (more)

LIMITS and Applications of Group Algebras for Parameterized Problems

The fastest known randomized algorithms for several parameterized problems use reductions to the k-MlD problem: detection of multilinear monomials of... (more)

Approximating Semi-matchings in Streaming and in Two-Party Communication

We study the streaming complexity and communication complexity of approximating unweighted semi-matchings. A semi-matching in a bipartite graph G... (more)

Optimal Orthogonal Graph Drawing with Convex Bend Costs

Traditionally, the quality of orthogonal planar drawings is quantified by the total number of bends or the maximum number of bends per edge. However,... (more)

A Simple and Efficient Algorithm for Computing Market Equilibria

We give a new mathematical formulation of market equilibria in exchange economies using an indirect utility function: the function of prices and... (more)

Families with Infants

Assume that a group of n people is going to an excursion and our task is to seat them into buses with several constraints each saying that a pair of people does not want to see each other in the same bus. This is a well-known graph coloring problem (with n being the number of vertices) and it can be solved in O*(2n) time by the... (more)

A Constant Factor Approximation Algorithm for Fault-Tolerant k-Median

In this article, we consider the fault-tolerant k-median problem and give the first constant factor approximation algorithm for it. In the... (more)

On the Expected Complexity of Voronoi Diagrams on Terrains

We investigate the combinatorial complexity of geodesic Voronoi diagrams on polyhedral terrains using a probabilistic analysis. Aronov et al. [2008]... (more)

All-Or-Nothing Generalized Assignment with Application to Scheduling Advertising Campaigns

We study a variant of the generalized assignment problem (gap), which we label all-or-nothing gap... (more)

NEWS

In Memoriam: David S. Johnson

http://dl.acm.org/citation.cfm?id=2907073

About TALG

The ACM Transactions on Algorithms (TALG) publishes original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis.

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Forthcoming Articles
Maximizing k-Submodular Functions and Beyond

We consider the maximization problem in the value oracle model of functions defined on k-tuples of sets that are submodular in every orthant and r-wise monotone, where k>=2 and 1<=r<=k. We give an analysis of a deterministic greedy algorithm that shows that any such function can be approximated to a factor of 1/(1+r). For r = k, we give an analysis of a randomised greedy algorithm that shows that any such function can be approximated to a factor of 1/(1+Sqrt(k/2)). In the case of k=r=2, the considered functions correspond precisely to bisubmodular functions, in which case we obtain an approximation guarantee of 1/2. We show that, as in the case of submodular functions, this result is the best possible in both the value query model, and under the assumption that NP!=RP. Extending a result of Ando et al., we show that for any k>=3 submodularity in every orthant and pairwise monotonicity (i.e. r=2) precisely characterize k-submodular functions. Consequently, we obtain an approximation guarantee of 1/3 (and thus independent of k) for the maximization problem of k-submodular functions.

Data Structures for Path Queries

Nearest-Neighbor Searching Under Uncertainty II

Nearest-neighbor (NN) search, which returns the nearest neighbor of a query point in a set of points, is an important and widely studied problem in many fields, and it has wide range of applications. In many of them, such as sensor databases, location-based services, face recognition, and mobile data, the location of data is imprecise. We therefore study nearest neighbor queries in a probabilistic framework in which the location of each input point is specified as a probability density function. We present efficient algorithms for (i) computing all points that are nearest neighbors of a query point with nonzero probability; (ii) estimating, within a specified additive error, the probability of a point being the nearest neighbor of a query point; (iii) using it to return the point that maximizes the probability being the nearest neighbor, or all the points with probabilities greater than some threshold to be the NN.

Adaptive and Approximate Orthogonal Range Counting

We present three new results on one of the most basic problems in geometric data structures, 2-D orthogonal range counting. All the results are in the $w$-bit word RAM model. - It is well known that there are linear-space data structures for 2-D orthogonal range counting with worst-case optimal query time O(log n / loglog n). We give an O(n loglog n)-space adaptive data structure that improves the query time to O(loglog n+log k / loglog n), where k is the output count. When k=O(1), our bounds match the state of the art for the 2-D orthogonal range emptiness problem [Chan, Larsen, and Patrascu, SoCG 2011]. - We give an O(n loglog n)-space data structure for approximate 2-D orthogonal range counting that can compute a (1+delta)-factor approximation to the count in O(loglog n) time for any fixed constant delta>0. Again, our bounds match the state of the art for the 2-D orthogonal range emptiness problem. - Lastly, we consider the 1-D range selection problem, where a query in an array involves finding the kth least element in a given subarray. This problem is closely related to 2-D 3-sided orthogonal range counting. Recently, Jorgensen and Larsen [SODA 2011] presented a linear-space adaptive data structure with query time O(loglog n + log k / loglog n). We give a new linear-space structure that improves the query time to O(1 + log k / loglog n), exactly matching the lower bound proved by Jorgensen and Larsen.

Compressed Cache-Oblivious String B-tree

Improved Approximation Algorithms for Matroid and Knapsack Median Problems and Applications

We consider the {\em matroid median} problem~\cite{KrishnaswamyKNSS11}, wherein we are given a set of facilities with opening costs and a matroid on the facility-set, and clients with demands and connection costs, and we seek to open an independent set of facilities and assign clients to open facilities so as to minimize the sum of the facility-opening and client-connection costs. We give a simple 8-approximation algorithm for this problem based on LP-rounding, which improves upon the 16-approximation in~\cite{KrishnaswamyKNSS11}. We illustrate the power and versatility of our techniques by deriving: (a) an 8-approximation for the {\em two-matroid median} problem, a generalization of matroid median that we introduce involving two matroids; and (b) a 24-approximation algorithm for {\em matroid median with penalties}, which is a vast improvement over the 360-approximation obtained in~\cite{KrishnaswamyKNSS11}. We show that a variety of seemingly disparate facility-location problems considered in the literature---data placement problem, mobile facility location, $k$-median forest, metric uniform minimum-latency {\footnotesize \textsf{UFL}}---in fact reduce to the matroid median or two-matroid median problems, and thus obtain {\em improved} approximation guarantees for all these problems. Our techniques also yield an improvement for the knapsack median problem.

Inapproximability of the Multi-level Uncapacitated Facility Location Problem

Tight lower bound for the channel assignment problem

We study the complexity of the Channel Assignment problem. An open problem asks whether Channel Assignment admits an $O(c^n)$-time algorithm, for a constant $c$ independent of the weights on the edges. We answer this question in the negative i.e. we show that there is no $2^{o(n\log n)}$-time algorithm solving Channel Assignment unless the Exponential Time Hypothesis fails. Note that the currently best known algorithm works in time $O^*(n!) = 2^{O(n\log n)}$ so our lower bound is tight.

Tabulating Pseudoprimes and Tabulating Liars

This paper presents new algorithms for two problems related to the Miller-Rabin-Selfridge primality test. The first problem is to tabulate strong pseudoprimes to a fixed base $a$. Tabulating up to $x$ requires $O(x)$ multiplications, where previous methods required $O(x \log{x})$ multiplications. The second problem is to find all strong liars and witnesses, given a fixed odd composite $n$. This appears to be unstudied, and an algorithm is presented that requires $O(n (\log\log{n})^2)$ multiplications. Although interesting in their own right, a notable application is the search for sets of composites with no reliable witness.

Deletion Without Rebalancing in Binary Search Trees

We address the vexing issue of deletions in balanced trees. Rebalancing after a deletion is generally more complicated than rebalancing after an insertion. Textbooks neglect deletion rebalancing, and many B-tree-based database systems do not do it. We describe a relaxation of AVL trees in which rebalancing is done after insertions but not after deletions, yet access time remains logarithmic in the number of insertions. For many applications of balanced trees, our structure offers performance competitive with that of classical balanced trees. With the addition of periodic rebuilding, the performance of our structure is theoretically superior to that of many if not all classic balanced tree structures. Our structure needs lglg(m) + 1 bits of balance information per node, where m is the number of insertions and lg is the base-two logarithm, or lglg(n) + O(1) with periodic rebuilding, where n is the number of nodes. An insertion takes up to two rotations and O(1) amortized time, the same as in standard AVL trees. Using an analysis that relies on an exponential potential function, we show that rebalancing steps occur with a frequency that is exponentially small in the height of the affected node. Our techniques apply to other types of balanced trees, notably B-trees, as we show in a companion paper, and in particular red-black trees, which can be viewed as a special case of B-trees.

Smoothed Analysis of the 2-Opt Algorithm for the General TSP

2-Opt is a simple local search heuristic for the traveling salesperson problem, which performs very well in experiments both with respect to running time and solution quality. In contrast to this, there are instances on which 2-Opt may need an exponential number of steps to reach a local optimum. To understand why 2-Opt usually finds local optima quickly in experiments, we study its expected running time in the model of smoothed analysis, which can be considered as a less pessimistic variant of worst-case analysis in which the adversarial input is subject to a small amount of random noise. In our probabilistic input model an adversary chooses an arbitrary graph~$G$ and additionally a probability density function for each edge according to which its length is chosen. We prove that in this model the expected number of local improvements is~$O(mn\phi(\log m)^3\cdot 4^{3\sqrt{\ln{m}}})=m^{1+o(1)}n\phi$, where~$n$ and~$m$ denote the number of vertices and edges of~$G$, respectively, and~$\phi$ denotes an upper bound on the density functions.

Space-Constrained Interval Selection

We study streaming algorithms for the interval selection problem: finding a maximum cardinality subset of disjoint intervals on the line. A deterministic $2$-approximation streaming algorithm for this problem is developed, together with an algorithm for the special case of proper intervals, achieving improved approximation ratio of $3/2$. We complement these upper bounds by proving that they are essentially best possible in the streaming setting: it is shown that an approximation ratio of $2 - \epsilon$ (or $3 / 2 - \epsilon$ for proper intervals) cannot be achieved unless the space is linear in the input size. In passing, we also answer an open question of Adler and Azar (J.\ Scheduling 2003) regarding the space complexity of constant-competitive randomized preemptive online algorithms for the same problem.

Semi-Streaming Set Cover

This paper studies the set cover problem under the semi-streaming model. The underlying set system is formalized in terms of a hypergraph $G = (V, E)$ whose edges arrive one-by-one and the goal is to construct an edge cover $F \subseteq E$ with the objective of minimizing the cardinality (cost in the weighted case) of $F$. We consider a parameterized relaxation of this problem, where given some $0 \leq \epsilon < 1$, the goal is to construct an edge $(1 - \epsilon)$-cover, namely, a subset of edges incident to all but an $\epsilon$-fraction of the vertices (or their benefit in the weighted case). The key limitation imposed on the algorithm is that its space is limited to (poly)logarithmically many bits per vertex. Our main result is an asymptotically tight trade-off between $\epsilon$ and the approximation ratio: We design a semi-streaming algorithm that on input hypergraph $G$, constructs a succinct data structure $\mathcal{D}$ such that for every $0 \leq \epsilon < 1$, an edge $(1 - \epsilon)$-cover that approximates the optimal edge \mbox{($1$-)cover} within a factor of $f(\epsilon, n)$ can be extracted from $\mathcal{D}$ (efficiently and with no additional space requirements), where \[ f(\epsilon, n) = \left\{ \begin{array}{ll} O (1 / \epsilon), & \text{if } \epsilon > 1 / \sqrt{n} \\ O (\sqrt{n}), & \text{otherwise} \end{array} \right. \, . \] In particular for the traditional set cover problem we obtain an $O(\sqrt{n})$-approximation. This algorithm is proved to be best possible by establishing a family (parameterized by $\epsilon$) of matching lower bounds.

Sparse Fault-Tolerant BFS Structures

A {\em fault-tolerant} structure for a network is required to continue functioning following the failure of some of the network's edges or vertices. This paper considers {\em breadth-first search (BFS)} spanning trees, and addresses the problem of designing a sparse {\em fault-tolerant} BFS structure, or {\em FT-BFS structure} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the surviving part $T'$ of $T$ still contains a BFS spanning tree for (the surviving part of) $G$. Our main results are as follows. We present an algorithm that for every $n$-vertex graph $G$ and source node $s$ constructs a (single edge failure) FT-BFS structure rooted at $s$ with $O(n \cdot \min\{Depth(s), \sqrt{n}\})$ edges, where $Depth(s)$ is the depth of the BFS tree rooted at $s$. This result is complemented by a matching lower bound. We then consider {\em fault-tolerant multi-source BFS structures}, or {\em FT-MBFS structure} for short, aiming to provide (following a failure) a BFS tree rooted at each source $s\in S$ for some subset of sources $S\subseteq V$. Finally, we propose an $O(\log n)$ approximation algorithm for constructing FT-BFS and FT-MBFS structures.

An Improved Approximation Algorithm for the Edge-Disjoint Paths Problem with Congestion Two

Approximation Algorithms for Movement Repairmen

Agnostic learning in permutation invariant domains

2-Edge Connectivity in Directed Graphs

Edge and vertex connectivity are fundamental concepts in graph theory. While they have been thoroughly studied in the case of undirected graphs, surprisingly not much has been investigated for directed graphs. In this paper we study 2-edge connectivity problems in directed graphs and, in particular, we consider the computation of the following natural relation: We say that two vertices v and w are 2-edge-connected if there are two edge-disjoint paths from v to w and two edge-disjoint paths from w to v. This relation partitions the vertices into blocks such that all vertices in the same block are 2-edge-connected. Differently from the undirected case, those blocks do not correspond to the 2-edge-connected components of the graph. The main result of this paper is an algorithm for computing the 2-edge-connected blocks of a directed graph in linear time. Besides being asymptotically optimal, our algorithm improves significantly over previous bounds. Once the 2-edge-connected blocks are available, we can test in constant time if two vertices are 2-edge-connected. Additionally, when two query vertices v and w are not 2-edge-connected, we can produce in constant time a witness of this property. We are also able to compute in linear time a sparse certificate for this relation, i.e., a subgraph of the input graph that has O(n) edges and maintains the same 2-edge-connected blocks as the input graph, where n is the number of vertices.

A Linear-Size Logarithmic Stretch Path-Reporting Distance Oracle for General Graphs

Given an $n$-vertex undirected graph $G = (V,E)$ and a parameter $k = 1,2,\ldots$, Thorup-Zwick's distance oracle has size $O(k n^{1+1/k})$, and upon a query $(u,v)$ it constructs a path $\Pi$ between $u$ and $v$ of length $\delta(u,v)$ such that $d_G(u,v) \le \delta(u,v) \le (2k-1) d_G(u,v)$. The query time of this oracle is $O(k)$ (in addition to the length of the returned path), and it was subsequently improved to $O(1)$ \cite{WN12,C14}. A major drawback of the oracle of Thorup and Zwick is that its space is $\Omega(n \cdot \log n)$. Mendel and Naor devised an oracle with space $O(n^{1+1/k})$ and stretch $O(k)$, but their oracle can only report distance estimates and not actual paths. In this paper we devise a path-reporting distance oracle with size $O(n^{1+1/k})$, stretch $O(k)$ and query time $O(n^\eps)$, for an arbitrarily small $\eps > 0$. Another variant of our oracle has size $O(n \log\log n)$, polylogarithmic stretch, and query time $O(\log\log n)$. For unweighted graphs we devise a distance oracle with multiplicative stretch $O(1)$, additive stretch $O(\beta(k))$, for a function $\beta()$, space $O(n^{1+1/k} \cdot \beta)$, and query time $O(n^\eps)$, for an arbitrarily small constant $\eps >0$. The tradeoff between multiplicative stretch and size in these oracles is far below girth conjecture threshold (which is stretch $2k-1$ and size $O(n^{1+1/k})$). An important novel tool that we develop on the way to these results is a {distance-preserving path-reporting oracle}. We believe that this oracle is of independent interest.

How good is multi-pivot quicksort?

Multi-Pivot Quicksort refers to variants of classical quicksort where in the partitioning step k pivots are used to split the input into k + 1 segments. For many years, multi-pivot quicksort was regarded as impractical, but in 2009 a 2-pivot approach by Yaroslavskiy, Bentley, and Bloch was chosen as the standard sorting algorithm in Sun's Java 7. In 2014 at ALENEX, Kushagra et al. introduced an even faster algorithm that uses three pivots. This paper studies what possible advantages multi-pivot quicksort might offer in general. The contributions are as follows: Natural comparison-optimal algorithms for multi-pivot quicksort are devised and analyzed. The analysis shows that the benefits of using multiple pivots with respect to the average comparison count are marginal and these strategies are inferior to simpler strategies such as the well known median-of-k approach. A substantial part of the partitioning cost is caused by rearranging elements. A rigorous analysis of an algorithm for rearranging elements in the partitioning step is carried out, observing mainly how often array cells are accessed during partitioning. The algorithm behaves best if 3 or 5 pivots are used. Experiments show that this translates into good cache behavior and is closest to predicting observed running times of multi-pivot quicksort algorithms. Finally, it is studied how choosing pivots from a sample affects sorting cost.

On the Tradeoff between Stability and Fit

In computing, as in many aspects of life, changes incur cost. Many optimization problems are formulated as a one-time instance starting from scratch. However, a common case that arises is when we already have a set of prior assignments, and must decide how to respond to a new set of constraints, given that each change from the current assignment comes at a price. That is, we would like to maximize the fitness or efficiency of our system, but we need to balance it with the changeout cost from the previous state. We provide a precise formulation for this tradeoff and analyze the resulting {\em stable extensions} of some fundamental problems in measurement and analytics. Our main technical contribution is a stable extension of PPS (probability proportional to size) weighted random sampling, with applications to monitoring and anomaly detection problems. We also provide a general framework that applies to top-k, minimum spanning tree, and assignment. In both cases, we are able to provide exact solutions, and discuss efficient incremental algorithms that can find new solutions as the input changes.

Better Balance by Being Biased: A 0.8776-Approximation for Max Bisection

Dynamic Facility Location via Exponential Clocks

The dynamic facility location problem is a generalization of the classic facility location problem proposed by Eisenstat, Mathieu, and Schabanel to model the dynamics of evolving social/infrastructure networks. The generalization lies in that the distance metric between clients and facilities changes over time. This leads to a trade-off between optimizing the classic objective function and the "stability" of the solution: there is a switching cost charged every time a client changes the facility to which it is connected. While the standard linear program (LP) relaxation for the classic problem naturally extends to this problem, traditional LP-rounding techniques do not, as they are often sensitive to small changes in the metric resulting in frequent switches. We present a new LP-rounding algorithm for facility location problems, which yields the first constant approximation algorithm for the dynamic facility location problem. Our algorithm installs competing exponential clocks on the clients and facilities, and connect every client by the path that repeatedly follows the smallest clock in the neighborhood. The use of exponential clocks gives rise to several properties that distinguish our approach from previous LP-roundings for facility location problems. In particular, we use no clustering and we allow clients to connect through paths of arbitrary lengths. In fact, the clustering-free nature of our algorithm is crucial for applying our LP-rounding approach to the dynamic problem.

Bibliometrics

Publication Years 2005-2016
Publication Count 515
Citation Count 2957
Available for Download 515
Downloads (6 weeks) 1318
Downloads (12 Months) 15669
Downloads (cumulative) 201734
Average downloads per article 392
Average citations per article 6
First Name Last Name Award
Lars Arge ACM Distinguished Member (2009)
Moses S Charikar ACM Paris Kanellakis Theory and Practice Award (2012)
Anne Condon ACM Doctoral Dissertation Award
Series Winner (1988) ACM Doctoral Dissertation Award
Series Winner (1988)
Graham R. Cormode ACM Distinguished Member (2013)
Constantinos Daskalakis ACM Doctoral Dissertation Award (2008)
Xiaotie Deng ACM Senior Member (2006)
Martin Dietzfelbinger ACM Distinguished Member (2011)
Pedro F Felzenszwalb ACM Grace Murray Hopper Award (2013)
Michael T Goodrich ACM Distinguished Member (2006)
Leonidas J Guibas ACM AAAI Allen Newell Award (2007)
Venkatesan Guruswami ACM Doctoral Dissertation Award (2002)
Piotr Indyk ACM Paris Kanellakis Theory and Practice Award (2012)
Charles E Leiserson ACM-IEEE CS Ken Kennedy Award (2014)
ACM Paris Kanellakis Theory and Practice Award (2013)
ACM Doctoral Dissertation Award (1982)
Kurt Mehlhorn ACM Paris Kanellakis Theory and Practice Award (2010)
Mukesh Mohania ACM Distinguished Member (2011)
Noam Nissan ACM Doctoral Dissertation Award
Series Winner (1990) ACM Doctoral Dissertation Award
Series Winner (1990)
Omer Reingold ACM Grace Murray Hopper Award (2005)
Sandeep K Shukla ACM Distinguished Member (2012)
ACM Senior Member (2007)
David Steurer ACM Doctoral Dissertation Award
Honorable Mention (2011) ACM Doctoral Dissertation Award
Honorable Mention (2011)
Madhu Sudan ACM Doctoral Dissertation Award (1993)
Subhash Suri ACM Distinguished Member (2007)
Robert E Tarjan ACM Paris Kanellakis Theory and Practice Award (1999)
ACM A. M. Turing Award (1986)
Salil P Vadhan ACM Doctoral Dissertation Award (2000)
Jeffrey S Vetter ACM Distinguished Member (2012)
ACM Gordon Bell Prize
Performance (2010)
Jennifer L Welch ACM Distinguished Member (2012)

First Name Last Name Paper Counts
MohammadTaghi Hajiaghayi 11
Dániel Marx 11
Guy Kortsarz 9
Erik Demaine 8
Uri Zwick 8
Robert Tarjan 7
Mikkel Thorup 7
Samir Khuller 7
Gonzalo Navarro 6
Magnús Halldórsson 6
Pankaj Agarwal 6
Zeev Nutov 6
Haim Kaplan 6
Moshe Lewenstein 6
Noga Alon 6
Ke Yi 5
David Eppstein 5
David Peleg 5
Chandra Chekuri 5
Andrzej Pelc 5
Kirk Pruhs 5
Hadas Shachnai 5
Micha Sharir 5
Raphael Yuster 5
Joseph Naor 5
Inge Gørtz 5
Venkatesh Raman 5
Saket Saurabh 5
Yossi Azar 5
Shay Solomon 5
S Muthukrishnan 5
Liam Roditty 5
Maxim Sviridenko 5
Nikhil Bansal 5
Anupam Gupta 5
Rohit Khandekar 4
Telikepalli Kavitha 4
Thore Husfeldt 4
Glencora Borradaile 4
Fedor Fomin 4
Dana Ron 4
Ashish Goel 4
Daniel Lokshtanov 4
Oren Weimann 4
Baruch Schieber 4
Timothy Chan 4
Graham Cormode 4
Guy Even 4
Viswanath Nagarajan 4
Sudipto Guha 4
Mohammad Salavatipour 4
Philip Klein 4
Susanne Albers 4
Michael Elkin 4
Ignaz Rutter 4
Kurt Mehlhorn 4
Sariel Har-Peled 4
Asaf Levin 4
Andrew McGregor 3
Adi Rosén 3
Dror Rawitz 3
Artur Czumaj 3
Alberto Marchetti-Spaccamela 3
Surender Baswana 3
Daniel Berend 3
Harald Räcke 3
Stephen Alstrup 3
Edward Reingold 3
Rob Van Stee 3
Leah Epstein 3
Sanjeev Khanna 3
Julia Chuzhoy 3
Amotz Bar-Noy 3
Dimitrios Thilikos 3
Marek Cygan 3
Harold Gabow 3
Christian Sohler 3
Boris Aronov 3
Pat Morin 3
Gabriel Scalosub 3
Srinivasa Satti 3
Meng He 3
Shai Gutner 3
George Karakostas 3
Baruch Awerbuch 3
Fabrizio Grandoni 3
Wojciech Szpankowski 3
Amol Deshpande 3
Amos Korman 3
Jeff Edmonds 3
Laurent Alonso 3
Kazuo Iwama 3
Sergio Cabello 3
Marek Chrobak 3
Amit Chakrabarti 3
Rajiv Gandhi 3
David Johnson 3
Danny Segev 3
Stefan Kratsch 3
Zoya Svitkina 3
Dimitrios Michail 3
Paolo Ferragina 3
Refael Hassin 3
Philip Bille 3
Ramamoorthi Ravi 3
Martín Farach-Colton 3
Amin Saberi 3
Yuval Rabani 3
Joseph Cheriyan 3
Seth Pettie 3
Morteza Zadimoghaddam 3
Lisa Hellerstein 3
Ola Svensson 2
Tami Tamir 2
Anne Driemel 2
Djamal Belazzougui 2
Adrian Vetta 2
Dilys Thomas 2
John Iacono 2
Kunihiko Sadakane 2
Holeung Chan 2
Dina Sokol 2
Teofilo Gonzalez 2
Jérémy Barbay 2
Roy Schwartz 2
Milan Ružić 2
Antoine Vigneron 2
R Sritharan 2
Andréa Richa 2
Leen Stougie 2
Konstantin Makarychev 2
Rajeev Raman 2
Dariusz Kowalski 2
Katarzyna Paluch 2
Jochen Könemann 2
Holger Dell 2
Cristopher Moore 2
Magnus Wahlström 2
Berthold Vöcking 2
Loukas Georgiadis 2
Andreas Björklund 2
Michael Bender 2
Svante Janson 2
Christoph Ambühl 2
Hiroki Yanagisawa 2
Tobias Jacobs 2
Alfredo Viola 2
Conrado Martínez 2
Don Coppersmith 2
Atri Rudra 2
Zachary Friggstad 2
Stefan Langerman 2
Amihood Amir 2
Joan Boyar 2
Joseph Leung 2
Peter Korteweg 2
Camil Demetrescu 2
Giuseppe Italiano 2
Joe Sawada 2
Alex Kesselman 2
Clifford Stein 2
Kamesh Munagala 2
Venkatesan Guruswami 2
HoLeung Chan 2
Thomas Erlebach 2
MohammadHossein Bateni 2
Irene Finocchi 2
Hans Bodlaender 2
Vijay Kumar 2
Bernhard Haeupler 2
Carmit Hazay 2
Bundit Laekhanukit 2
Thomas Sauerwald 2
Lisa Fleischer 2
Rina Panigrahy 2
An Zhu 2
Lisa Zhang 2
Veli Mäkinen 2
Takwah Lam 2
Lapchi Lau 2
Hamid Mahini 2
Pierre Fraigniaud 2
Subhash Suri 2
James Aspnes 2
Éva Tardos 2
Ioannis Caragiannis 2
Claire Mathieu 2
Hamid Nazerzadeh 2
Yury Makarychev 2
Alexandr Andoni 2
Matthew Andrews 2
Michael Drmota 2
Bodo Manthey 2
Dimitris Fotakis 2
Michele Flammini 2
Helmut Prodinger 2
Eduardo Laber 2
Konstantinos Panagiotou 2
Jie Gao 2
Jesper Nederlof 2
Kenichi Kawarabayashi 2
MohammadTaghi Hajiaghayi 2
Christophe Paul 2
Ulrich Meyer 2
Petr Kolman 2
Iftah Gamzu 2
Somnath Sikdar 2
Ioannis Koutis 2
Roberto Grossi 2
Benjamin Raichel 2
Angelika Steger 2
Mingyang Kao 2
Anastasios Sidiropoulos 2
Shanghua Teng 2
Jon Feldman 2
Mikko Koivisto 2
Ignasi Sau 2
Christos Kaklamanis 2
Klaus Jansen 2
Martin Skutella 2
Tomás Feder 2
Cyril Gavoille 2
Julián Mestre 2
Luca Becchetti 2
Mohammad Mahdian 2
Jiří Sgall 2
Chaitanya Swamy 2
Dieter Kratsch 2
Geevarghese Philip 2
Thomas Bläsius 2
Dekel Tsur 2
Yoann Dieudonné 2
Suresh Venkatasubramanian 2
Lars Arge 2
Ittai Abraham 2
Vincenzo Bonifaci 2
Alexander Russell 2
Allan Borodin 2
Yishay Mansour 2
Ramakrishna Thurimella 2
Kenneth Clarkson 2
Goran Konjevod 2
Jittat Fakcharoenphol 2
John Hershberger 2
Yonatan Aumann 2
Adam Meyerson 2
Shay Mozes 2
Joan Feigenbaum 2
Shuichi Miyazaki 2
Theis Rauhe 2
Lapkei Lee 1
Bruce Maggs 1
Mathieu Liedloff 1
Ioan Todinca 1
Łukasz Kowalik 1
Wei Chen 1
Estrella Eisenberg 1
Alexander Wolff 1
Georg Baier 1
Ondřej Pangrác 1
Bernhard Von Stengel 1
Marcelo Mydlarz 1
F Shepherd 1
Assaf Naor 1
TamáS Fleiner 1
Benjamin Moseley 1
Yngve Villanger 1
Avinatan Hassidim 1
Ronald Graham 1
Martin Dietzfelbinger 1
Seth Gilbert 1
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J Munro 1
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Eunjung Kim 1
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Éric Fusy 1
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Ron Adany 1
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Haitao Wang 1
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Gianni Franceschini 1
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Tzuchin Lin 1
Qianping Gu 1
Yevgen Voronenko 1
Huahuai Chern 1
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Michael Goodrich 1
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Christian Scheideler 1
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Jiong Guo 1
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Funda Ergün 1
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N Narayanaswamy 1
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Venkatesh Natarajan 1
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Yijie Han 1
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Ying Xu 1
Louis Ibarra 1
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Amir Sapir 1
Atlas IV 1
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Himanshu Gupta 1
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Shi Li 1
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Siuwing Cheng 1
Hjalte VildhØj 1
Csaba Tóth 1
Donglin Xia 1
Rajesh Chitnis 1
MohammadAmin Fazli 1
Sina Sadeghabad 1
MohammadAli Safari 1
Jan Kratochvíl 1
M Ramanujan 1
Dannyziyi Chen 1
Richard Cole 1
Frank Ruskey 1
Shay Kutten 1
Gagan Aggarwal 1
Shimon Shahar 1
Hung Yu 1
Hisao Tamaki 1
Markus Püschel 1
M Paal 1
Lene Favrholdt 1
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Gilad Tsur 1
Tomasz Nowicki 1
Karsten Tiemann 1
Avner Magen 1
Sandeep Sen 1
Justus Schwartz 1
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Rohan Fernandes 1
David Fernández-Baca 1
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Valerie King 1
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Greg Little 1
Satish Rao 1
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Prasad Raghavendra 1
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Yusuke Kobayashi 1
Oded Lachish 1
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François Nicolas 1
Nishanth Chandran 1
Mohammad Safari 1
Jens Vygen 1
Shakhar Smorodinsky 1
Mihai Bǎdoiu 1
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Francis Chin 1
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Piyush Kurur 1
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Jaikumar Radhakrishnan 1
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Balaji Raghavachari 1
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Ge Nong 1
Sivan Toledo 1
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Irit Katriel 1
Hu Zhang 1
Nicole Megow 1
Erich Kaltofen 1
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Stefan Hougardy 1
Micah Adler 1
Martin Aumüller 1
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Alex Levin 1
Frank Staals 1
Jeremy Fineman 1
T Chan 1
Martin Hoefer 1
Benjamin Aminof 1
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Danny Hermelin 1
StéPhan Thomassé 1
Philip Klein 1
Alexander Golovnev 1
Ryan Williams 1
Johannes Fischer 1
Jérémie Chalopin 1
Yann Disser 1
Vít Jelínek 1
Aaron Williams 1
Krishnaram Kenthapadi 1
Daniel Lemire 1
Mark De Berg 1
Ron Levy 1
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Hsienkuei Hwang 1
Gad Landau 1
Shmuel Safra 1
Martin Gairing 1
Kasturi Varadarajan 1
Niv Buchbinder 1
Vanbang Le 1
Alessandro Panconesi 1
Steve Oudot 1
Nir Ailon 1
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Jianer Chen 1
Songjian Lu 1
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Anke Truß 1
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Roberto De Prisco 1
Sandy Irani 1
Wojciech Jawor 1
Tali Kaufman 1
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Eric Chen 1
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Yuli Ye 1
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Anne Condon 1
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David Pritchard 1
Eli Upfal 1
Ulrich Schwarz 1
Friedhelm Heide 1
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Danny Raz 1

Affiliation Paper Counts
Meiji University 1
Medical University of South Carolina 1
National Taiwan Ocean University 1
Georgetown University 1
Shanghai Jiaotong University 1
University College Cork 1
University of Tokyo 1
Rensselaer Polytechnic Institute 1
Indian Institute of Technology, Madras 1
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Institute for Advanced Studies 1
Oracle Corporation 1
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University of Leoben 1
Siemens AG 1
Ludwig Maximilian University of Munich 1
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NICTA 1
The University of Georgia 1
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Utah State University 1
Michigan State University 1
Korea Advanced Institute of Science & Technology 1
University of Wisconsin Madison 1
University of Electro-Communications 1
University of the Saarland 1
Sobolev Institute of Mathematics of Siberian Branch of the RAS 1
Google Switzerland GmbH 1
NEC Deutschland GmbH 1
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 1
ORT Braude - College of Engineering 1
Intertrust Technologies Corporation 1
Microsoft Research Cambridge 1
VMware, Inc 1
Laboratoire d'Analyse et Modelisation de Systemes pour l'Aide a la Decision 1
SRI International 1
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University of Michigan 1
Universite Pierre et Marie Curie 1
University of Glasgow 1
University of Stellenbosch 1
Center for Communications Research 1
National Technical University of Athens 1
Toyohashi University of Technology 1
Vanderbilt University 1
Zhejiang University 1
IBM Tokyo Research Laboratory 1
Iowa State University 1
Dalian University of Technology 1
University of G. d'Annunzio Chieti and Pescara 1
J. Craig Venter Institute 1
Ecole Normale Superieure de Lyon 1
Los Alamos National Laboratory 1
University of Western Macedonia 1
National Institutes of Health, Bethesda 1
University of Missouri-Kansas City 1
Sandia National Laboratories, New Mexico 1
Laboratoire d'Informatique, de Robotique et de Microelectronique de Montpellier LIRMM 1
Technical University in Braunschweig 1
Malmo University 1
University of Sao Paulo 1
Vrije Universiteit Amsterdam 1
Hong Kong Polytechnic University 1
Birkbeck University of London 1
Linkoping University 1
Universite Paris 13 1
University of Colorado at Denver 1
Kyushu University 1
BRICS Basic Research in Computer Science 1
National Chiao Tung University Taiwan 1
Lubeck University 1
University of Texas at Austin 1
INRIA Institut National de Rechereche en Informatique et en Automatique 1
Indian Institute of Technology, Bombay 1
Hong Kong Baptist University 1
University of California, Davis 1
Dalle Molle Institute for Artificial Intelligence 1
Federal University of Parana 1
Florida International University 1
University of Witwatersrand 1
Holon Institute of Technology 1
Academia Sinica Taiwan 1
University of New Brunswick 1
University of Tubingen 1
Aegean University 1
George Mason University 1
Universite Bordeaux 1 1
Boston University 1
University of Wisconsin Milwaukee 1
Saint Petersburg Department of Steklov Institute of Mathematics, Russian Academy of Sciences 1
Brandenburg University of Technology Cottbus 1
Hewlett-Packard 1
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Johannes Kepler University Linz 1
University of Durham 1
Pennsylvania State University 2
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Mentor Graphics Corporation 2
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Graz University of Technology 2
Royal Holloway University of London 2
West Virginia University 2
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Kasetsart University 2
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University of Freiburg 2
Microsoft 2
Universite Paul Verlaine - Metz 2
St. Louis University 2
Research Organization of Information and Systems National Institute of Informatics 2
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University of Aarhus 2
Universite d'Orleans 2
Technical University of Ilmenau 2
Temple University 2
Free University of Berlin 2
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Tata Institute of Fundamental Research 2
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Indian Institute of Technology, Delhi 2
University of Puerto Rico 2
Universidad de la Republica 2
Microsoft Research Asia 2
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Aalto University 2
Ecole Normale Superieure 3
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Helsinki Institute for Information Technology 3
Royal Institute of Technology 3
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Johns Hopkins University 3
Nanyang Technological University 3
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Johann Wolfgang Goethe University of Frankfurt 3
Harvard University 3
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IBM Research 3
Oregon State University 3
Ecole Polytechnique 3
Texas A and M University 3
University of Connecticut 3
New Jersey Institute of Technology 3
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University of Sydney 3
Laboratoire d'Informatique de l'Ecole Polytechnique 3
Shandong University 3
University of Ljubljana 3
Academy of Sciences of the Czech Republic (Avcr.Cz) 3
University at Buffalo, State University of New York 3
York University Canada 3
University of Iceland 3
Toyota Technological Institute at Chicago 3
King Abdullah University of Science and Technology 3
Aix Marseille Universite 3
Chinese University of Hong Kong 4
University of Victoria 4
IBM India Research Laboratory New Delhi 4
Arizona State University 4
Yale University 4
City University of New York 4
University of Salerno 4
Universitat Politecnica de Catalunya 4
Roma Tre University 4
Indian Institute of Science 4
AT&T Inc. 4
INRIA Lorraine 4
National Tsing Hua University 4
University of Southern Denmark 4
Georgia Institute of Technology 4
University of Twente 4
Universite Montpellier 2 Sciences et Techniques 4
Computer and Automation Research Institute Hungarian Academy of Sciences 4
Virginia Tech 4
University of Athens 4
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Karlsruhe Institute of Technology, Campus South 4
Budapest University of Technology and Economics 4
University of Dortmund 4
University of New Mexico 4
Reykjavik University 4
Illinois Institute of Technology 5
Cornell University 5
Alcatel-Lucent Bell Labs 5
IBM Almaden Research Center 5
Purdue University 5
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Hungarian Academy of Sciences 5
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Yahoo Research Labs 5
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MIT Computer Science and Artificial Intelligence Laboratory 6
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Hebrew University of Jerusalem 9
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IBM 9
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University of Bergen 9
University of Alberta 10
Hong Kong University of Science and Technology 11
Brown University 11
Eindhoven University of Technology 11
Princeton University 13
The University of Hong Kong 13
Rutgers University-Camden campus 13
Institute of Mathematical Sciences India 14
University of Roma La Sapienza 14
Microsoft Research 15
Weizmann Institute of Science Israel 16
University of Haifa 18
Google Inc. 18
AT&T Laboratories Florham Park 18
IBM Thomas J. Watson Research Center 18
University of Maryland 19
Stanford University 21
Bar-Ilan University 23
Ben-Gurion University of the Negev 23
Max Planck Institute for Informatics 25
Carnegie Mellon University 25
University of Waterloo 27
Massachusetts Institute of Technology 27
Technion - Israel Institute of Technology 30
Tel Aviv University 69

ACM Transactions on Algorithms (TALG)
Archive


2016
Volume 12 Issue 3, June 2016
Volume 12 Issue 2, February 2016
Volume 12 Issue 1, February 2016 Special Issue on SODA'12 and Regular Papers

2015
Volume 11 Issue 4, June 2015
Volume 11 Issue 3, January 2015

2014
Volume 11 Issue 2, November 2014
Volume 11 Issue 1, October 2014
Volume 10 Issue 4, August 2014
Volume 10 Issue 3, June 2014
Volume 10 Issue 2, February 2014
Volume 10 Issue 1, January 2014

2013
Volume 9 Issue 4, September 2013
Volume 9 Issue 3, June 2013 Special Issue on SODA'11
Volume 9 Issue 2, March 2013

2012
Volume 9 Issue 1, December 2012
Volume 8 Issue 4, September 2012
Volume 8 Issue 3, July 2012
Volume 8 Issue 2, April 2012
Volume 8 Issue 1, January 2012

2011
Volume 7 Issue 4, September 2011
Volume 7 Issue 3, July 2011
Volume 7 Issue 2, March 2011

2010
Volume 7 Issue 1, November 2010
Volume 6 Issue 4, August 2010
Volume 6 Issue 3, June 2010
Volume 6 Issue 2, March 2010

2009
Volume 6 Issue 1, December 2009
Volume 5 Issue 4, October 2009
Volume 5 Issue 3, July 2009
Volume 5 Issue 2, March 2009

2008
Volume 5 Issue 1, November 2008
Volume 4 Issue 4, August 2008
Volume 4 Issue 3, June 2008
Volume 4 Issue 2, May 2008
Volume 4 Issue 1, March 2008

2007
Volume 3 Issue 4, November 2007
Volume 3 Issue 3, August 2007
Volume 3 Issue 2, May 2007
Volume 3 Issue 1, February 2007

2006
Volume 2 Issue 4, October 2006
Volume 2 Issue 3, July 2006
Volume 2 Issue 2, April 2006
Volume 2 Issue 1, January 2006

2005
Volume 1 Issue 2, October 2005
Volume 1 Issue 1, July 2005
 
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