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20202022
most citedOnline Page Migration with ML Advice

5 citations · 11 across the 3 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.DS2020

New Partitioning Techniques and Faster Algorithms for Approximate Interval Scheduling

Spencer Compton, Slobodan Mitrović, Ronitt Rubinfeld

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping…

cs.LG2020

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

Marwa El Halabi, Slobodan Mitrović, Ashkan Norouzi-Fard +2

Submodular maximization has become established as the method of choice for the task of selecting representative and diverse summaries of data. However, if datapoints have sensitive…

cs.DS2020★ 5 cited

Online Page Migration with ML Advice

Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrović +1

We consider online algorithms for the {\em page migration problem} that use predictions, potentially imperfect, to improve their performance. The best known online algorithms for t…

cs.DS2020

Fully Dynamic Algorithm for Constrained Submodular Optimization

Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard +2

The task of maximizing a monotone submodular function under a cardinality constraint is at the core of many machine learning and data mining applications, including data summarizat…

cs.DS2020

Massively Parallel Algorithms for Distance Approximation and Spanners

Amartya Shankha Biswas, Michal Dory, Mohsen Ghaffari +2

Over the past decade, there has been increasing interest in distributed/parallel algorithms for processing large-scale graphs. By now, we have quite fast algorithms -- usually subl…

cs.DS2020

Massively Parallel Algorithms for Small Subgraph Counting

Amartya Shankha Biswas, Talya Eden, Quanquan C. Liu +2

Over the last two decades, frameworks for distributed-memory parallel computation, such as MapReduce, Hadoop, Spark and Dryad, have gained significant popularity with the growing p…