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cs.LG2024
Active Exploration via Autoregressive Generation of Missing Data
Tiffany Tianhui Cai, Hongseok Namkoong, Daniel Russo +1
We pose uncertainty quantification and exploration in online decision-making as a problem of training and generation from an autoregressive sequence model, an area experiencing rap…
cs.LG2024
On the Limited Representational Power of Value Functions and its Links to Statistical (In)Efficiency
David Cheikhi, Daniel Russo
Identifying the trade-offs between model-based and model-free methods is a central question in reinforcement learning. Value-based methods offer substantial computational advantage…