6 citations · 7 across the 5 of their papers we have counts for
5 papers
Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames
Ev Zisselman, Mirco Mutti, Shelly Francis-Meretzki +2
Behavioral cloning is a simple yet effective technique for learning sequential decision-making from demonstrations. Recently, it has gained prominence as the core of foundation mod…
Explore to Generalize in Zero-Shot RL
Ev Zisselman, Itai Lavie, Daniel Soudry +1
We study zero-shot generalization in reinforcement learning-optimizing a policy on a set of training tasks to perform well on a similar but unseen test task. To mitigate overfittin…
Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability
Aviv Tamar, Daniel Soudry, Ev Zisselman
In the Bayesian reinforcement learning (RL) setting, a prior distribution over the unknown problem parameters -- the rewards and transitions -- is assumed, and a policy that optimi…
Deep Residual Flow for Out of Distribution Detection
Ev Zisselman, Aviv Tamar
The effective application of neural networks in the real-world relies on proficiently detecting out-of-distribution examples. Contemporary methods seek to model the distribution of…
A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model
Ev Zisselman, Jeremias Sulam, Michael Elad
The Convolutional Sparse Coding (CSC) model has recently gained considerable traction in the signal and image processing communities. By providing a global, yet tractable, model th…