3 papers
cs.LG2026
Optimistic Gradient Learning with Hessian Corrections for High-Dimensional Black-Box Optimization
Yedidya Kfir, Elad Sarafian, Sarit Kraus +1
Black-box algorithms are designed to optimize functions without relying on their underlying analytical structure or gradient information, making them essential when gradients are i…
cs.CL2024
Data-driven Coreference-based Ontology Building
Shir Ashury-Tahan, Amir David Nissan Cohen, Nadav Cohen +2
While coreference resolution is traditionally used as a component in individual document understanding, in this work we take a more global view and explore what can we learn about…
cs.SI2024
Exploring individual differences through network topology
Yuval Samoilov-Katz, Yoram Louzoun, Lev Muchnik +1
Social animals, including humans, have a broad range of personality traits, which can be used to predict individual behavioral responses and decisions. Current methods to quantify…