2 citations · 4 across the 15 of their papers we have counts for
6 papers · 1 filter
Towards Human-AI Complementarity in Matching Tasks
Adrian Arnaiz-Rodriguez, Nina Corvelo Benz, Suhas Thejaswi +2
Data-driven algorithmic matching systems promise to help human decision makers make better matching decisions in a wide variety of high-stakes application domains, such as healthca…
Fair Clustering for Data Summarization: Improved Approximation Algorithms and Complexity Insights
Ameet Gadekar, Aristides Gionis, Suhas Thejaswi
Data summarization tasks are often modeled as -clustering problems, where the goal is to choose data points, called cluster centers, that best represent the dataset by minim…
Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets
Eleni Straitouri, Suhas Thejaswi, Manuel Gomez Rodriguez
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…
Towards Human-AI Complementarity with Prediction Sets
Giovanni De Toni, Nastaran Okati, Suhas Thejaswi +2
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, t…
Prediction-Powered Ranking of Large Language Models
Ivi Chatzi, Eleni Straitouri, Suhas Thejaswi +1
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 prefer…
Fair Column Subset Selection
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…