375 citations · 375 across the 7 of their papers we have counts for
9 papers
What a Reporting Convention Hides: A Matched-Budget Audit of Quantum Natural Gradient with an Exactly Computed Metric
Lu Wei, Yufeng Wang, Haibin Ling
Several published comparisons of variational quantum optimizers time only runs that reach a target loss, or read the verdict at a single target. Either convention could decide whet…
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…
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…
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…
Provable Speech Attributes Conversion via Latent Independence
Jonathan Svirsky, Ofir Lindenbaum, Uri Shaham
Conditional generation and disentangled representation learning are central to controlled generation across audio, vision, and multimodal domains. However, despite strong empirical…
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…
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…
Generalizable and Robust Spectral Method for Multi-view Representation Learning
Amitai Yacobi, Ofir Lindenbaum, Uri Shaham
Multi-view representation learning (MvRL) has garnered substantial attention in recent years, driven by the increasing demand for applications that can effectively process and anal…
Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization
Uri Shaham, Yutaro Yamada, Sahand Negahban
We propose a general framework for increasing local stability of Artificial Neural Nets (ANNs) using Robust Optimization (RO). We achieve this through an alternating minimization-m…