
Streaming Submodular Maximization with Matroid and Matching Constraints
Recent progress in (semi)streaming algorithms for monotone submodular f...
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A QPTAS for stabbing rectangles
We consider the following geometric optimization problem: Given n axisa...
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NearlyTight and Oblivious Algorithms for Explainable Clustering
We study the problem of explainable clustering in the setting first form...
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SemiStreaming Algorithms for Submodular Matroid Intersection
While the basic greedy algorithm gives a semistreaming algorithm with a...
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Fast and Accurate kmeans++ via Rejection Sampling
kmeans++ <cit.> is a widely used clustering algorithm that is easy to i...
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Consistent kClustering for General Metrics
Given a stream of points in a metric space, is it possible to maintain a...
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The PrimalDual method for Learning Augmented Algorithms
The extension of classical online algorithms when provided with predicti...
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Learning Augmented Energy Minimization via Speed Scaling
As power management has become a primary concern in modern data centers,...
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Fair Colorful kCenter Clustering
An instance of colorful kcenter consists of points in a metric space th...
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Robust Algorithms under Adversarial Injections
In this paper, we study streaming and online algorithms in the context o...
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The Oneway Communication Complexity of Submodular Maximization with Applications to Streaming and Robustness
We consider the classical problem of maximizing a monotone submodular fu...
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Beating Greedy for Stochastic Bipartite Matching
We consider the maximum bipartite matching problem in stochastic setting...
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New Notions and Constructions of Sparsification for Graphs and Hypergraphs
A sparsifier of a graph G (Benczúr and Karger; Spielman and Teng) is a s...
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Online Matching with General Arrivals
The online matching problem was introduced by Karp, Vazirani and Vaziran...
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Weighted Matchings via Unweighted Augmentations
We design a generic method for reducing the task of finding weighted mat...
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Beyond 1/2Approximation for Submodular Maximization on Massive Data Streams
Many tasks in machine learning and data mining, such as data diversifica...
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SemiSupervised Algorithms for Approximately Optimal and Accurate Clustering
We study kmeans clustering in a semisupervised setting. Given an oracl...
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On bounded pitch inequalities for the minknapsack polytope
In the minknapsack problem one aims at choosing a set of objects with m...
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Ola Svensson
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