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pro vyhledávání: '"Liesen, Jarek"'
Autor:
Pignatelli, Eduardo, Liesen, Jarek, Lange, Robert Tjarko, Lu, Chris, Castro, Pablo Samuel, Toni, Laura
As Deep Reinforcement Learning (Deep RL) research moves towards solving large-scale worlds, efficient environment simulations become crucial for rapid experimentation. However, most existing environments struggle to scale to high throughput, setting
Externí odkaz:
http://arxiv.org/abs/2407.19396
Dataset distillation aims to condense large datasets into a small number of synthetic examples that can be used as drop-in replacements when training new models. It has applications to interpretability, neural architecture search, privacy, and contin
Externí odkaz:
http://arxiv.org/abs/2406.15042
Autor:
Liesen, Jarek, Lu, Chris, Lupu, Andrei, Foerster, Jakob N., Sprekeler, Henning, Lange, Robert T.
Reinforcement learning (RL) agents are commonly trained and evaluated in the same environment. In contrast, humans often train in a specialized environment before being evaluated, such as studying a book before taking an exam. The potential of such s
Externí odkaz:
http://arxiv.org/abs/2406.12589