collaborators

5 papers

cs.LG2026

A Goal-Set Characterization of Task Composition in the Boolean Task Algebra

Eduardo Terrés-Caballero, Herke van Hoof

The Boolean Task Algebra (BTA) provides a principled framework for zero-shot task composition in reinforcement learning by equipping goal-reaching tasks with Boolean operations. We…

cs.LG2026

Gradient-Based Program Synthesis with Neurally Interpreted Languages

Matthew V. Macfarlane, Clément Bonnet, Herke van Hoof +1

A central challenge in program induction has long been the trade-off between symbolic and neural approaches. Symbolic methods offer compositional generalisation and data efficiency…

cs.IR2026

The Unfairness of Multifactorial Bias in Recommendation

Masoud Mansoury, Jin Huang, Mykola Pechenizkiy +2

Popularity bias and positivity bias are two prominent sources of bias in recommender systems. Both arise from input data, propagate through recommendation models, and lead to unfai…

cs.LG2025

Data Augmentation for Instruction Following Policies via Trajectory Segmentation

Niklas Höpner, Ilaria Tiddi, Herke van Hoof

The scalability of instructable agents in robotics or gaming is often hindered by limited data that pairs instructions with agent trajectories. However, large datasets of unannotat…

cs.LG2025

Bridge the Inference Gaps of Neural Processes via Expectation Maximization

Qi Wang, Marco Federici, Herke van Hoof

The neural process (NP) is a family of computationally efficient models for learning distributions over functions. However, it suffers from under-fitting and shows suboptimal perfo…