4 citations · 8 across the 9 of their papers we have counts for
5 papers · 1 filter
Learning Normal Representations for Blood Biomarkers
Aashna P. Shah, Michelle M. Li, Yash Lal +9
Blood-based biomarkers underpin clinical diagnosis and management, yet their interpretation relies largely on fixed population reference intervals that ignore stable, intra-patient…
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM Performance
Seffi Cohen, Niv Goldshlager, Nurit Cohen-Inger +2
Large Language Models (LLMs) have shown remarkable capabilities across various natural language processing tasks but often struggle to excel uniformly in diverse or complex domains…
FairTTTS: A Tree Test Time Simulation Method for Fairness-Aware Classification
Nurit Cohen-Inger, Lior Rokach, Bracha Shapira +1
Algorithmic decision-making has become deeply ingrained in many domains, yet biases in machine learning models can still produce discriminatory outcomes, often harming unprivileged…
BiasGuard: Guardrailing Fairness in Machine Learning Production Systems
Nurit Cohen-Inger, Seffi Cohen, Neomi Rabaev +2
As machine learning (ML) systems increasingly impact critical sectors such as hiring, financial risk assessments, and criminal justice, the imperative to ensure fairness has intens…
Boosting Anomaly Detection Using Unsupervised Diverse Test-Time Augmentation
Seffi Cohen, Niv Goldshlager, Lior Rokach +1
Anomaly detection is a well-known task that involves the identification of abnormal events that occur relatively infrequently. Methods for improving anomaly detection performance h…