118 citations · 453 across the 15 of their papers we have counts for
31 papers
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…
Efficient Self-Supervised Data Collection for Offline Robot Learning
Shadi Endrawis, Gal Leibovich, Guy Jacob +2
A practical approach to robot reinforcement learning is to first collect a large batch of real or simulated robot interaction data, using some data collection policy, and then lear…
Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization
Carmel Rabinovitz, Niko Grupen, Aviv Tamar
Robotic tasks such as manipulation with visual inputs require image features that capture the physical properties of the scene, e.g., the position and configuration of objects. Rec…
Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder
Tal Daniel, Aviv Tamar
The recently introduced introspective variational autoencoder (IntroVAE) exhibits outstanding image generations, and allows for amortized inference using an image encoder. The main…
Online Safety Assurance for Deep Reinforcement Learning
Noga H. Rotman, Michael Schapira, Aviv Tamar
Recently, deep learning has been successfully applied to a variety of networking problems. A fundamental challenge is that when the operational environment for a learning-augmented…
Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores
Tzvika Geft, Aviv Tamar, Ken Goldberg +1
To compute robust 2D assembly plans, we present an approach that combines geometric planning with a deep neural network. We train the network using the Box2D physics simulator with…