Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Thejaswi, Suhas"'
Data summarization tasks are often modeled as $k$-clustering problems, where the goal is to choose $k$ data points, called cluster centers, that best represent the dataset by minimizing a clustering objective. A popular objective is to minimize the m
Externí odkaz:
http://arxiv.org/abs/2410.12913
Decision support systems based on prediction sets help humans solve multiclass classification tasks by narrowing down the set of potential label values to a subset of them, namely a prediction set, and asking them to always predict label values from
Externí odkaz:
http://arxiv.org/abs/2406.06671
Autor:
De Toni, Giovanni, Okati, Nastaran, Thejaswi, Suhas, Straitouri, Eleni, Gomez-Rodriguez, Manuel
Decision support systems based on prediction sets have proven to be effective at helping human experts solve classification tasks. Rather than providing single-label predictions, these systems provide sets of label predictions constructed using confo
Externí odkaz:
http://arxiv.org/abs/2405.17544
Resettlement agencies have started to adopt data-driven algorithmic matching to match refugees to locations using employment rate as a measure of utility. Given a pool of refugees, data-driven algorithmic matching utilizes a classifier to predict the
Externí odkaz:
http://arxiv.org/abs/2407.13052
Large language models are often ranked according to their level of alignment with human preferences -- a model is better than other models if its outputs are more frequently preferred by humans. One of the popular ways to elicit human preferences uti
Externí odkaz:
http://arxiv.org/abs/2402.17826
In this work, we study diversity-aware clustering problems where the data points are associated with multiple attributes resulting in intersecting groups. A clustering solution need to ensure that a minimum number of cluster centers are chosen from e
Externí odkaz:
http://arxiv.org/abs/2401.05502
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. A natural extension is to consider a setting where t
Externí odkaz:
http://arxiv.org/abs/2306.04489
We study a variant of classical clustering formulations in the context of algorithmic fairness, known as diversity-aware clustering. In this variant we are given a collection of facility subsets, and a solution must contain at least a specified numbe
Externí odkaz:
http://arxiv.org/abs/2112.07030
We introduce a novel problem for diversity-aware clustering. We assume that the potential cluster centers belong to a set of groups defined by protected attributes, such as ethnicity, gender, etc. We then ask to find a minimum-cost clustering of the
Externí odkaz:
http://arxiv.org/abs/2106.11696
We study a family of reachability problems under waiting-time restrictions in temporal and vertex-colored temporal graphs. Given a temporal graph and a set of source vertices, we find the set of vertices that are reachable from a source via a time-re
Externí odkaz:
http://arxiv.org/abs/2010.08423