collaborators

11 papers

cs.LG2026

Query Feedback and Teaching for Stable and Certifiable Language Generation

Farnam Mansouri, Alireza F. Pour, Grigoris Velegkas +1

Language generation in the limit studies whether a learner observing an enumeration of an unknown target language can eventually generate only valid, previously unseen elements. We…

math.CO2026

Burning Signed Graphs

Shaun Fallat, Himanshu Gupta, Kamyar Khodamoradi +1

We introduce and analyze a new model of graph burning, in which two competing fires (coloured yellow and green) ignite vertices of a given signed graph and propagate along its edge…

cs.FL2026

Learning Shuffle Ideals with Membership Queries and Contrastive Examples

S. Mahmoud Mousawi, Pierluigi San Pietro, Sandra Zilles

This paper studies learning of shuffle ideals with membership queries as well as with contrastive queries---a form of membership query that reveals not only whether a selected word…

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.FL2025

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.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…

cs.LG2025

Formal Models of Active Learning from Contrastive Examples

Farnam Mansouri, Hans U. Simon, Adish Singla +2

Machine learning can greatly benefit from providing learning algorithms with pairs of contrastive training examples -- typically pairs of instances that differ only slightly, yet h…

cs.LG2025

Common Benchmarks Undervalue the Generalization Power of Programmatic Policies

Amirhossein Rajabpour, Kiarash Aghakasiri, Sandra Zilles +1

Algorithms for learning programmatic representations for sequential decision-making problems are often evaluated on out-of-distribution (OOD) problems, with the common conclusion t…