Skip to content

Author

S. Mahabadi

4 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Oct 2026

Random Fourier Features in Near-Linear Time

Random Fourier features approximate a shift-invariant kernel in $\mathbb{R}^d$, such as the Gaussian kernel $\exp(-\tfrac12\|x-y\|_2^2)$, using independent samples from its spectral measure to construct an unbiased estimator for the kernel value with subgaussian concentration. However, generating $m$ such features requ...

S. Mahabadi, Sandeep Silwal, Tal Wagner · 0 citations
Preprint Oct 2026

Improved Sublinear Algorithms for Maximal Independent Set and Metric Steiner Forest

In this work we consider the Maximal Independent Set (MIS) problem and the metric Steiner Forest problem in the sublinear time setting, under the adjacency/distance matrix query model. First, we give an algorithm that estimates the size of an MIS up to a multiplicative factor of $(1+\eps)$ using $\tO(n^{4/3}/\eps^2)$ q...

S. Mahabadi, Jakub Tarnawski · 0 citations
Preprint Sep 2026

Local Search for Fair Max-Min Diversification

Given $n$ points in a metric space, Max-Min diversification asks for a subset of $k$ points maximizing the minimum pairwise distance between the selected points. This is arguably the most fundamental notion of diversity with applications across a wide range of domains. We consider this problem under partition constrain...

S. Mahabadi, Shyam Narayanan, Varun Sivashankar · 0 citations
Preprint Sep 2026

Hardness of Online Directed Steiner Network

This work gives an $\exp\!\bigl(\Omega(\sqrt{\log n})\bigr)$ bound on the competitive ratio, which holds even for randomized algorithms against an oblivious adversary, and on unit-cost DAGs.

Gary Hoppenworth, Yao-Wei Long, S. Mahabadi et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.