Publications by Mikhail Kapralov

Online Matching with General Arrivals

Ola Nils Anders Svensson, Mikhail Kapralov, Buddhima Ruwanmini Gamlath Gamlath Ralalage, Andreas Maggiori, David Wajc

The online matching problem was introduced by Karp, Vazirani and Vazirani nearly three decades ago. In that seminal work, they studied this problem in bipartite graphs with vertices arriving only on one side, and presented optimal deterministic and randomi ...

IEEE COMPUTER SOC2019

An Optimal Space Lower Bound for Approximating MAX-CUT

Mikhail Kapralov

We consider the problem of estimating the value of MAX-CUT in a graph in the streaming model of computation. At one extreme, there is a trivial 2-approximation for this problem that uses only O(log n) space, namely, count the number of edges and output hal ...

ASSOC COMPUTING MACHINERY2019

Efficiently Learning Fourier Sparse Set Functions

Andreas Krause, Mikhail Kapralov, Amir Zandieh

Learning set functions is a key challenge arising in many domains, ranging from sketching graphs to black-box optimization with discrete parameters. In this paper we consider the problem of efficiently learning set functions that are defined over a ground ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

The Sketching Complexity of Graph and Hypergraph Counting

Mikhail Kapralov, John Michael Goddard Kallaugher

Subgraph counting is a fundamental primitive in graph processing, with applications in social network analysis (e.g., estimating the clustering coefficient of a graph), database processing and other areas. The space complexity of subgraph counting has been ...

IEEE COMPUTER SOC2018

Testing Graph Clusterability: Algorithms and Lower Bounds

Mikhail Kapralov, Aidasadat Mousavifar, Ashish Hari Chiplunkar

We consider the problem of testing graph cluster structure: given access to a graph G = (V, E), can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph? This is a generali ...

IEEE COMPUTER SOC2018

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Mikhail Kapralov

Graph Chatbot

Chat with Graph Search

Online Matching with General Arrivals

An Optimal Space Lower Bound for Approximating MAX-CUT

Efficiently Learning Fourier Sparse Set Functions

The Sketching Complexity of Graph and Hypergraph Counting

Testing Graph Clusterability: Algorithms and Lower Bounds

An Adaptive Sublinear-Time Block Sparse Fourier Transform

The Sketching Complexity of Graph and Hypergraph Counting

Efficiently Learning Fourier Sparse Set Functions

An Adaptive Sublinear-Time Block Sparse Fourier Transform

An Optimal Space Lower Bound for Approximating MAX-CUT

Online Matching with General Arrivals

Testing Graph Clusterability: Algorithms and Lower Bounds