Search Results for author: Ron Dorfman

Found 5 papers, 3 papers with code

Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers

no code implementations5 Feb 2024 Ron Dorfman, Naseem Yehya, Kfir Y. Levy

Byzantine-robust learning has emerged as a prominent fault-tolerant distributed machine learning framework.

DoCoFL: Downlink Compression for Cross-Device Federated Learning

no code implementations1 Feb 2023 Ron Dorfman, Shay Vargaftik, Yaniv Ben-Itzhak, Kfir Y. Levy

Many compression techniques have been proposed to reduce the communication overhead of Federated Learning training procedures.

Federated Learning

Adapting to Mixing Time in Stochastic Optimization with Markovian Data

1 code implementation9 Feb 2022 Ron Dorfman, Kfir Y. Levy

We consider stochastic optimization problems where data is drawn from a Markov chain.

Stochastic Optimization

Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies

1 code implementation NeurIPS 2021 Ron Dorfman, Idan Shenfeld, Aviv Tamar

Consider the following instance of the Offline Meta Reinforcement Learning (OMRL) problem: given the complete training logs of $N$ conventional RL agents, trained on $N$ different tasks, design a meta-agent that can quickly maximize reward in a new, unseen task from the same task distribution.

Meta Reinforcement Learning reinforcement-learning +1

Offline Meta Learning of Exploration

1 code implementation NeurIPS 2021 Ron Dorfman, Idan Shenfeld, Aviv Tamar

Consider the following instance of the Offline Meta Reinforcement Learning (OMRL) problem: given the complete training logs of $N$ conventional RL agents, trained on $N$ different tasks, design a meta-agent that can quickly maximize reward in a new, unseen task from the same task distribution.

Meta-Learning Meta Reinforcement Learning

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