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Found 3 papers, 1 papers with code
Adaptive t-Momentum-based Optimization for Unknown Ratio of Outliers in Amateur Data in Imitation Learning
In order to allow the imitators to effectively learn from imperfect demonstrations, we propose to employ the robust t-momentum optimization algorithm.
Deep unfolding-based output feedback control design for linear systems with input saturation
In this paper, we propose a deep unfolding-based framework for the output feedback control of systems with input saturation.
TAdam: A Robust Stochastic Gradient Optimizer
Machine learning algorithms aim to find patterns from observations, which may include some noise, especially in robotics domain.
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