no code implementations • 16 Oct 2024 • Ameet Gadekar, Aristides Gionis, Suhas Thejaswi
For disjoint groups, our algorithm runs in polynomial time, while for overlapping groups, we present a fixed-parameter tractable algorithm, where the exponential runtime depends only on the number of groups and centers.
1 code implementation • 10 Jun 2024 • Eleni Straitouri, Suhas Thejaswi, Manuel Gomez Rodriguez
In this paper, our goal is to control how frequently a decision support system based on prediction sets may cause harm, by design.
1 code implementation • 27 May 2024 • Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez-Rodriguez
Then, we show that the problem of finding the optimal prediction sets under which the human experts achieve the highest average accuracy is NP-hard.
no code implementations • 24 May 2024 • Seungeon Lee, Nina Corvelo Benz, Suhas Thejaswi, Manuel Gomez-Rodriguez
Then, we develop a post-processing algorithm that, given placement decisions made by a default policy on a pool of refugees and their employment outcomes, solves an inverse~matching problem to minimally modify the predictions made by a given classifier.
1 code implementation • 27 Feb 2024 • Ivi Chatzi, Eleni Straitouri, Suhas Thejaswi, Manuel Gomez Rodriguez
Using pairwise comparisons made by humans in the LMSYS Chatbot Arena platform and pairwise comparisons made by three strong large language models, we empirically demonstrate the effectivity of our framework and show that the rank-sets constructed using only pairwise comparisons by the strong large language models are often inconsistent with (the distribution of) human pairwise preferences.
no code implementations • 10 Jan 2024 • Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Aristides Gionis
We present parameterized approximation algorithms with approximation ratios $1+ \frac{2}{e}$, $1+\frac{8}{e}$ and $3$ for diversity-aware $k$-median, diversity-aware $k$-means and diversity-aware $k$-supplier, respectively.
1 code implementation • 7 Jun 2023 • Antonis Matakos, Bruno Ordozgoiti, Suhas Thejaswi
The problem of column subset selection asks for a subset of columns from an input matrix such that the matrix can be reconstructed as accurately as possible within the span of the selected columns.
1 code implementation • 20 Jan 2020 • Suhas Thejaswi, Aristides Gionis, Juho Lauri
In particular, given a vertex-colored temporal graph and a multiset of colors as a query, we search for temporal paths in the graph that contain the colors specified in the query.