collaborators

7 papers

cs.LG2026

A Harmonic Mean Formulation of Average Reward Reinforcement Learning in SMDPs

Erel Shtossel, Alicia Vidler, Uri Shaham +1

Recent research has revived and amplified interest in algorithms for undiscounted average reward reinforcement learning in infinite-horizon, non-episodic (continuing) tasks. Semi-M…

cs.LG2026

PRISM: PRIor from corpus Statistics for topic Modeling

Tal Ishon, Yoav Goldberg, Uri Shaham

Topic modeling seeks to uncover latent semantic structure in text, with LDA providing a foundational probabilistic framework. While recent methods often incorporate external knowle…

cs.LG2026

Unsupervised Ensemble Learning Through Deep Energy-based Models

Ariel Maymon, Yanir Buznah, Uri Shaham

Unsupervised ensemble learning emerged to address the challenge of combining multiple learners' predictions without access to ground truth labels or additional data. This paradigm…

cs.CV2025

Learning Shared Representations from Unpaired Data

Amitai Yacobi, Nir Ben-Ari, Ronen Talmon +1

Learning shared representations is a primary area of multimodal representation learning. The current approaches to achieve a shared embedding space rely heavily on paired samples f…

cs.SD2025

Provable Speech Attributes Conversion via Latent Independence

Jonathan Svirsky, Ofir Lindenbaum, Uri Shaham

While signal conversion and disentangled representation learning have shown promise for manipulating data attributes across domains such as audio, image, and multimodal generation,…

cs.LG2025

Generalizable Spectral Embedding with an Application to UMAP

Nir Ben-Ari, Amitai Yacobi, Uri Shaham

Spectral Embedding (SE) is a popular method for dimensionality reduction, applicable across diverse domains. Nevertheless, its current implementations face three prominent drawback…