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  • title: Robust Forecasting for Robotic Control: A Game-Theoretic Approach
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            Robust Forecasting for Robotic Control: A Game-Theoretic Approach
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            Robust Forecasting for Robotic Control: A Game-Theoretic Approach

            Dec 2, 2022

            Speakers

            SA

            Shubhankar Agarwal

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            DF

            David Fridovich-Keil

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            SPC

            Sandeep P. Chinchali

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            About

            Modern robots require accurate forecasts to make optimal decisions in the real world. For example, self-driving cars need an accurate forecast of other agents' future actions to plan safe trajectories. Current methods rely heavily on historical time series to accurately predict the future. However, relying entirely on the observed history is problematic since it could be corrupted by noise, have outliers, or not completely represent all possible outcomes. We propose a novel framework for generat…

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            NeurIPS 2022

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