5 citations · 8 across the 5 of their papers we have counts for
6 papers
Structured Prediction with Abstention via the Lovász Hinge
Jessie Finocchiaro, Rafael Frongillo, Enrique Nueve
The Lovász hinge is a convex loss function proposed for binary structured classification, in which k related binary predictions jointly evaluated by a submodular function. Despite…
Three Types of Calibration with Properties and their Semantic and Formal Relationships
Rabanus Derr, Jessie Finocchiaro, Robert C. Williamson
Fueled by discussions around "trustworthiness" and algorithmic fairness, calibration of predictive systems has regained scholars attention. The vanilla definition and understanding…
Bridging Research and Practice Through Conversation: Reflecting on Our Experience
Mayra Russo, Mackenzie Jorgensen, Kristen M. Scott +4
While some research fields have a long history of collaborating with domain experts outside academia, many quantitative researchers do not have natural avenues to meet experts in a…
The Structured Abstain Problem and the Lovász Hinge
Jessie Finocchiaro, Rafael Frongillo, Enrique Nueve
The Lovász hinge is a convex surrogate recently proposed for structured binary classification, in which binary predictions are made simultaneously and the error is judged by a…
Unifying Lower Bounds on Prediction Dimension of Consistent Convex Surrogates
Jessie Finocchiaro, Rafael Frongillo, Bo Waggoner
Given a prediction task, understanding when one can and cannot design a consistent convex surrogate loss, particularly a low-dimensional one, is an important and active area of mac…
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness
Jessie Finocchiaro, Roland Maio, Faidra Monachou +4
Decision-making systems increasingly orchestrate our world: how to intervene on the algorithmic components to build fair and equitable systems is therefore a question of utmost imp…