no code implementations • 19 Dec 2023 • Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia Panettiere, Apostolos Tzimoulis, Nachoem Wijnberg
Building on formal concept analysis (FCA), the starting point of the present work is that different ways to categorize a given set of objects exist, which depend on the choice of the sets of features used to classify them, and different such sets of features may yield better or worse categorizations, relative to the task at hand.
no code implementations • 11 Jul 2023 • Yiwen Ding, Krishna Manoorkar, Apostolos Tzimoulis, Ruoding Wang, Xiaolong Wang
This work extends Halpern and Pearl's causal models for actual causality to a possible world semantics environment.
no code implementations • 4 Jan 2023 • Erman Acar, Andrea De Domenico, Krishna Manoorkar, Mattia Panettiere
These algorithms use a single concept lattice for such a task, meaning that the set of features used for the categorization is fixed.
no code implementations • 31 Oct 2022 • Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia Panettiere, Apostolos Tzimoulis, Nachoem Wijnberg
The framework developed in this paper provides a formal ground to obtain and study explainable categorizations from the data represented as bipartite graphs according to the agendas of different agents in an organization (e. g.~an audit firm), and interaction between these through deliberation.
no code implementations • 14 Aug 2019 • Sabine Frittella, Krishna Manoorkar, Alessandra Palmigiano, Apostolos Tzimoulis, Nachoem M. Wijnberg
In this paper, we generalize the basic notions and results of Dempster-Shafer theory from predicates to formal concepts.