activity
20182022
most citedApproximate Triangle Counting via Sampling and Fast Matrix Multiplication

2 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

cs.DS2022

Estimating the Effective Support Size in Constant Query Complexity

Shyam Narayanan, Jakub Tětek

Estimating the support size of a distribution is a well-studied problem in statistics. Motivated by the fact that this problem is highly non-robust (as small perturbations in the d…

cs.DS2022

Sampling an Edge in Sublinear Time Exactly and Optimally

Talya Eden, Shyam Narayanan, Jakub Tětek

Sampling edges from a graph in sublinear time is a fundamental problem and a powerful subroutine for designing sublinear-time algorithms. Suppose we have access to the vertices of…

cs.DS20212 cited

Approximate Triangle Counting via Sampling and Fast Matrix Multiplication

Jakub Tětek

There is a trivial time algorithm for approximate triangle counting where is the number of triangles in the graph and the number of vertices. At the same…

cs.DS2021

CountSketches, Feature Hashing and the Median of Three

Kasper Green Larsen, Rasmus Pagh, Jakub Tětek

In this paper, we revisit the classic CountSketch method, which is a sparse, random projection that transforms a (high-dimensional) Euclidean vector to a vector of dimension $(…

cs.AI2020

Performance of Bounded-Rational Agents With the Ability to Self-Modify

Jakub Tětek, Marek Sklenka, Tomáš Gavenčiak

Self-modification of agents embedded in complex environments is hard to avoid, whether it happens via direct means (e.g. own code modification) or indirectly (e.g. influencing the…

cs.DS20201 cited

Sampling an Edge Uniformly in Sublinear Time

Jakub Tětek

The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have t…