3 papers
cs.LG2021
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…
cs.LG2020
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…
cs.CV2018
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…