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cs.LG2022
Beyond the Edge of Stability via Two-step Gradient Updates
Lei Chen, Joan Bruna
Gradient Descent (GD) is a powerful workhorse of modern machine learning thanks to its scalability and efficiency in high-dimensional spaces. Its ability to find local minimisers i…
cs.LG2022★ 4 cited
When does return-conditioned supervised learning work for offline reinforcement learning?
David Brandfonbrener, Alberto Bietti, Jacob Buckman +2
Several recent works have proposed a class of algorithms for the offline reinforcement learning (RL) problem that we will refer to as return-conditioned supervised learning (RCSL).…