collaborators

8 papers

cs.FL2026

Positive Characteristic Sets for Relational Pattern Languages

S. Mahmoud Mousawi, Sandra Zilles

In the context of learning formal languages, data about an unknown target language L is given in terms of a set of (word,label) pairs, where a binary label indicates whether or not…

cs.AI2026

On the Semantics of Primary Cause in Hybrid Dynamic Domains

Shakil M. Khan, Asim Mehmood, Sandra Zilles

Reasoning about actual causes of observed effects is fundamental to the study of rationality. This important problem has been studied since the time of Aristotle, with formal mathe…

cs.LG2026

Active learning from positive and unlabeled examples

Farnam Mansouri, Sandra Zilles, Shai Ben-David

Learning from positive and unlabeled data (PU learning) is a weakly supervised variant of binary classification in which the learner receives labels only for (some) positively labe…

cs.LG2026

Learning Half-Spaces from Perturbed Contrastive Examples

Aryan Alavi Razavi Ravari, Farnam Mansouri, Yuxin Chen +3

We study learning under a two-step contrastive example oracle, as introduced by Mansouri et. al. (2025), where each queried (or sampled) labeled example is paired with an additiona…

cs.LG2025

Distance-based Learning of Hypertrees

Shaun Fallat, Kamyar Khodamoradi, David Kirkpatrick +3

We study the problem of learning hypergraphs with shortest-path queries (SP-queries), and present the first provably optimal online algorithm for a broad and natural class of hyper…

cs.CC2025

The Computational Complexity of Almost Stable Clustering with Penalties

Kamyar Khodamoradi, Farnam Mansouri, Sandra Zilles

We investigate the complexity of stable (or perturbation-resilient) instances of and clustering problems in metrics with smal…