Ev Zisselman
Bio & Research Interests
I'm a PhD student at the Electrical & Computer Engineering (ECE) department at the Technion. I'm a member of the Robot Learning Lab, under the guidance of Prof. Aviv Tamar. I have an M.Sc. from the Technion ECE, advised by Prof. Michael Elad. Previously, I obtained a B.Sc. in Electrical & Computer Engineering and a B.Sc. in Physics from the Technion.
I am interested in designing machine learning algorithms for reliable sequential decision-making in complex environments. My main focus is generalization in deep reinforcement learning, learning from demonstration, exploration, and fast adaptation. I’m also interested in computer vision, deep generative models, and image processing.
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Explore to Generalize in Zero-Shot RL
Ev Zisselman,
Itai Lavie,
Daniel Soudry,
Aviv Tamar,
NeurIPS, 2023
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arXiv
ExpGen uses exploration during test time for zero-shot generalization in reinforcement learning.
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Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability
Aviv Tamar,
Daniel Soudry,
Ev Zisselman,
AAAI, 2022   (Oral)
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arXiv
We develop PAC bounds for Bayesian RL (meta-RL).   A key underlying result is showing algorithmic stability for regularized MDPs.
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Deep Residual Flow for Out of Distribution Detection
Ev Zisselman,
Aviv Tamar,
CVPR, 2020
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arXiv
An expressive density model based on normalizing flows for out of distribution detection.
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Local Block Coordinate Descent (LoBCoD) Algorithm for the CSC Model
Ev Zisselman,
Jeremias Sulam,
Michael Elad,
CVPR, 2020
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arXiv
The Convolutional Sparse Coding (CSC) Model is usfull for various image processing tasks, and has strong connection to Convolutional Neural Networks (CNN).
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Compressed Learning for Image Classification: A Deep Neural Network Approach
Ev Zisselman,
Amir Adler,
Michael Elad,
Handbook of Numerical Analysis, Elsevier, 2018
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An end-to-end deep learning approach for Compressed Learning (CL).
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